Abstract:

In recent years, synthetic Computed Tomography (CT) images generated from Magnetic Resonance (MR) or Cone Beam Computed Tomography (CBCT) acquisitions have been shown to be comparable to real CT images in terms of dose computation for radiotherapy simulation. However, until now, there has been no independent strategy to assess the quality of each synthetic image in the absence of ground truth. In this work, we propose a Deep Learning (DL)-based framework to predict the accuracy of synthetic CT in terms of Mean Absolute Error (MAE) without the need for a ground truth (GT). The proposed algorithm generates a volumetric map as an output, informing clinicians of the predicted MAE slice-by-slice. A cascading multi-model architecture was used to deal with the complexity of the MAE prediction task. The workflow was trained and tested on two cohorts of head and neck cancer patients with different imaging modalities: 27 MR scans and 33 CBCT. The algorithm evaluation revealed an accurate HU prediction (a median absolute prediction deviation equal to 4 HU for CBCT-based synthetic CTs and 6 HU for MR-based synthetic CTs), with discrepancies that do not affect the clinical decisions made on the basis of the proposed estimation. The workflow exhibited no systematic error in MAE prediction. This work represents a proof of concept about the feasibility of synthetic CT evaluation in daily clinical practice, and it paves the way for future patient-specific quality assessment strategies.

Abstract:

Limited medical image data hinders the training of deep learning (DL) models in the biomedical field. Image augmentation can reduce the data-scarcity problem by generating variations of existing images. However, currently implemented methods require coding, excluding non-programmer users from this opportunity.We therefore present ImageAugmenter, an easy-to-use and open-source module for 3D Slicer imaging computing platform. It offers a simple and intuitive interface for applying over 20 simultaneous MONAI Transforms (spatial, intensity, etc.) to medical image datasets, all without programming.ImageAugmenter makes accessible medical image augmentation, enabling a wider range of users to improve the performance of DL models in medical image analysis by increasing the number of samples available for training.

Abstract:

Monocular depth estimation is an important topic in minimally invasive surgery, providing valuable information for downstream application, like navigation systems. Deep learning for this task requires high amount of training data for an accurate and robust model. Especially in the medical field acquiring ground truth depth information is rarely possible due to patient security and technical limitations. This problem is being tackled by many approaches including the use of syn- thetic data. This leads to the question, how well does the syn- thetic data allow the prediction of depth information on clini- cal data. To evaluate this, the synthetic data is used to train and optimize a U-Net, including hyperparameter tuning and aug- mentation. The trained model is then used to predict the depth on clinical image and analyzed in quality, consistency over the same scene, time and color. The results demonstrate that syn- thetic data sets can be used for training, with an accuracy of over 77% and a RMSE below 10 mm on the synthetic data set, do well on resembling clinical data, but also have limitations due to the complexity of clinical environments. Synthetic data sets are a promising approach allowing monocular depth esti- mation in fields with otherwise lacking data.

Abstract:

Efficient personalized ablation strategies for treating atrial arrhythmias remain challenging. Discrepancies in identifying arrhythmogenic areas using characterization methods, such as late gadolinium enhanced magnetic resonance imaging (LGE-MRI) and electroanatomical mapping, require a comparative analysis of local impedance (LI) and LGE-MRI data. This study aims to analyze correlations as basis for im- provement of treatment strategies. 16 patients undergoing left atrium (LA) ablation with LGE-MRI acquisition and LI data recording were recruited. LGE-MRI data and LI measurements were normalized to patient- and modality-specific blood pool references. A global mean shape was generated based on all patient geometries, and normalized local impedance (LIN) and LGE-MRI image intensity ratio (IIR) data points were co- registered for comparison.Data analysis comprised intra-patient and inter-patient assess- ments, evaluating differences in LIN values among datasets categorized by their IIR. Due to substantial deviations in LIN values, even within the same patient and IIR-category, discern- ing the presence or absence of a correlation was challenging, and no statistically significant correlation could be identified. Our findings underscore the necessity for standardized proto- cols in data acquisition, processing, and comparison, to mini- mize unquantified confounding effects. While immediate substitution of LI for LGE-MRI seems improbable given the significant LIN variations, this preliminary study lays the ground- work for systematic data acquisition. By ensuring data quality, a meaningful comparison between LI and LGE-MRI data can be facilitated, potentially shaping future strategies for atrial ar- rhythmia treatment.

Abstract:

In laparoscopic liver surgery, image-guided navigation systems provide crucial support to surgeons by supply- ing information about tumor and vessel positions. For this purpose, these information from a preoperative CT or MRI scan is overlaid onto the laparoscopic video. One option is performing a registration of preoperative 3D data and 3D reconstructed laparoscopic data. A robust registration is challenging due to factors like limited field of view, liver deformations, and 3D reconstruction errors. Since in reality various influencing factors always intertwine, it is crucial to analyze their combined effects. This paper assesses registration accuracy under various synthetically simulated influences: patch size, spatial dis- placement, Gaussian deformations, holes, and downsampling. The objective is to provide insights into the required quality of the intraoperative 3D surface patches. LiverMatch serves as the feature descriptor, and registration employs the RANSAC algorithm. The results of this paper show that ensuring a large field of view of at least 15-20% of the liver surface is necessary, allowing tolerance for less accurate depth estimation.

Abstract:

The lack of labeled, intraoperative patient data in medical scenarios poses a relevant challenge for machine learning applications. Given the apparent power of machine learning, this study examines how synthetically-generated data can help to reduce the amount of clinical data needed for robust liver surface segmentation in laparoscopic images. Here, we report the results of three experiments, using 525 annotated clinical images from 5 patients alongside 20,000 synthetic photo-realistic images from 10 patient models. The effectiveness of the use of synthetic data is compared to the use of data augmentation, a traditional performance-enhancing technique. For training, a supervised approach employing the U-Net architecture was chosen. The results of these experiments show a progressive increase in accuracy. Our base experiment on clinical data yielded an F1 score of 0.72. Applying data augmentation to this model increased the F1 score to 0.76. Our model pre-trained on synthetic data and fine-tuned with augmented data achieved an F1 score of 0.80, a 4% increase. Additionally, a model evaluation involving k-fold cross validation highlighted the dependency of the result on the test set. These results demonstrate that leveraging synthetic data has the ability of limiting the need for more patient data to increase the segmentation performance.

Abstract:

We investigate the force-frequency relationship (FFR) representation of human ventricular cardiomyocyte models and point out shortcomings, motivated by discrepancies in whole-heart simulations at increased pacing rates. Utilizing the openCARP simulator, simulations across frequencies ranging from 1 Hz to 3 Hz were conducted. Experimental data on healthy human ventricular cardiomyocytes were collected and compared against simulated results. Results show deviations for all models, with Tomek et al. modeling time sensitive biomarkers the best. For example, the ratio of time to peak tension at 2 Hz and 1 Hz is around 85% for experiments, 82% for hybrid data, 95% for Tomek et al., 98% for O’Hara et al. and 138% for ten Tusscher et al. These discrepancies, highlight not only the need for careful selection of ionic models, but also the importance of refining ventricular cardiomyocyte models for advancing in-silico cardiac research.

Abstract:

AIMS: The effective refractory period (ERP) is one of the main electrophysiological properties governing arrhythmia, yet ERP personalization is rarely performed when creating patient-specific computer models of the atria to inform clinical decision-making. This study evaluates the impact of integrating clinical ERP measurements into personalized in silico models on arrhythmia vulnerability. METHODS AND RESULTS: Clinical ERP measurements were obtained in seven patients from multiple locations in the atria. Atrial geometries from the electroanatomical mapping system were used to generate personalized anatomical atrial models. The Courtemanche M. et al. cellular model was adjusted to reproduce patient-specific ERP. Four modeling approaches were compared: homogeneous (A), heterogeneous (B), regional (C), and continuous (D) ERP distributions. Non-personalized approaches (A and B) were based on literature data, while personalized approaches (C and D) were based on patient measurements. Modeling effects were assessed on arrhythmia vulnerability and tachycardia cycle length, with sensitivity analysis on ERP measurement uncertainty. Mean vulnerability was 3.4 ± 4.0%, 7.7 ± 3.4%, 9.0 ± 5.1%, and 7.0 ± 3.6% for scenarios A-D, respectively. Mean tachycardia cycle length was 167.1 ± 12.6 ms, 158.4 ± 27.5 ms, 265.2 ± 39.9 ms, and 285.9 ± 77.3 ms for scenarios A-D, respectively. Incorporating perturbations to the measured ERP in the range of 2, 5, 10, 20, and 50 ms changed the vulnerability of the model to 5.8 ± 2.7%, 6.1 ± 3.5%, 6.9 ± 3.7%, 5.2 ± 3.5%, and 9.7 ± 10.0%, respectively. CONCLUSION: Increased ERP dispersion had a greater effect on re-entry dynamics than on vulnerability. Inducibility was higher in personalized scenarios compared with scenarios with uniformly reduced ERP; however, this effect was reversed when incorporating fibrosis informed by low-voltage areas. Effective refractory period measurement uncertainty up to 20 ms slightly influenced vulnerability. Electrophysiological personalization of atrial in silico models appears essential and requires confirmation in larger cohorts.

Abstract:

The human heart is subject to highly variable amounts of strain during day-to-day activities and needs to adapt to a wide range of physiological demands. This adaptation is driven by an autoregulatory loop that includes both electrical and the mechanical components. In particular, mechanical forces are known to feed back into the cardiac electrophysiology system, which can result in pro- and anti-arrhythmic effects. Despite the widespread use of computational modelling and simulation for cardiac electrophysiology research, the majority of in silico experiments ignore this mechano-electric feedback entirely due to the high computational cost associated with solving cardiac mechanics. In this study, we therefore use an electromechanically coupled whole-heart model to investigate the differential and combined effects of electromechanical feedback mechanisms with a focus on their physiological relevance during sinus rhythm. In particular, we consider troponin-bound calcium, the effect of deformation on the tissue diffusion tensor, and stretch-activated channels. We found that activation of the myocardium was only significantly affected when including deformation into the diffusion term of the monodomain equation. Repolarization, on the other hand, was influenced by both troponin-bound calcium and stretch-activated channels and resulted in steeper repolarization gradients in the atria. The latter also caused afterdepolarizations in the atria. Due to its central role for tension development, calcium bound to troponin affected stroke volume and pressure. In conclusion, we found that mechano-electric feedback changes activation and repolarization patterns throughout the heart during sinus rhythm and lead to a markedly more heterogeneous electrophysiological substrate. KEY POINTS: The electrophysiological and mechanical function of the heart are tightly interrelated by excitation-contraction coupling (ECC) in the forward direction and mechano-electric feedback (MEF) in the reverse direction. While ECC is considered in many state-of-the-art computational models of cardiac electromechanics, less is known about the effect of different MEF mechanisms. Accounting for calcium bound to troponin increases stroke volume and delays repolarization. Geometry-mediated MEF leads to more heterogeneous activation and repolarization with steeper gradients. Both effects combine in an additive way. Non-selective stretch-activated channels as an additional MEF mechanism lead to heterogeneous diastolic transmembrane voltage, higher developed tension and delayed repolarization or afterdepolarizations in highly stretched parts of the atria. The differential and combined effects of these three MEF mechanisms during sinus rhythm activation in a human four-chamber heart model may have implications for arrhythmogenesis, both in terms of substrate (repolarization gradients) and triggers (ectopy).

Abstract:

Objective. 3D-localization of gamma sources has the potential to improve the outcome of radio-guided surgery. The goal of this paper is to analyze the localization accuracy for point-like sources with a single coded aperture camera. Approach. We both simulated and measured a point-like 241Am source at 17 positions distributed within the field of view of an experimental gamma camera. The setup includes a 0.11mm thick Tungsten sheet with a MURA mask of rank 31 and pinholes of 0.08 mm in diameter and a detector based on the photon counting readout circuit Timepix3. Two methods, namely an iterative search including either a symmetric Gaussian fitting or an exponentially modified Gaussian fitting (EMG) and a center of mass method were compared to estimate the 3D source position. Main results. Considering the decreasing axial resolution with source-to-mask distance, the EMG improved the results by a factor of 4 compared to the Gaussian fitting based on the simulated data. Overall, we obtained a mean localization error of 0.77 mm on the simulated and 2.64 mm on the experimental data in the imaging range of 20−100 mm. Significance. This paper shows that despite the low axial resolution, point-like sources in the nearfield can be localized as well as with more sophisticated imaging devices such as stereo cameras. The influence of the source size and the photon count on the imaging and localization accuracy remains an important issue for further research.

Abstract:

Background: Computer models for simulating cardiac electrophysiology are valuable tools for research and clinical applications. Traditional reaction-diffusion (RD) models used for these purposes are computationally expensive. While eikonal models offer a faster alternative, they are not well-suited to study cardiac arrhythmias driven by reentrant activity. The present work extends the diffusion-reaction eikonal alternant model (DREAM), incorporating conduction velocity (CV) restitution for simulating complex cardiac arrhythmias. Methods: The DREAM modifies the fast iterative method to model cyclical behavior, dynamic boundary conditions, and frequency-dependent anisotropic CV. Additionally, the model alternates with an approximated RD model, using a detailed ionic model for the reaction term and a triple-Gaussian to approximate the diffusion term. The DREAM and monodomain models were compared, simulating reentries in 2D manifolds with different resolutions. Results: The DREAM produced similar results across all resolutions, while experiments with the monodomain model failed at lower resolutions. CV restitution curves obtained using the DREAM closely approximated those produced by the monodomain simulations. Reentry in 2D slabs yielded similar results in vulnerable window and mean reentry duration for low CV in both models. In the left atrium, most inducing points identified by the DREAM were also present in the high-resolution monodomain model. DREAM's reentry simulations on meshes with an average edge length of 1600$\mu$m were 40x faster than monodomain simulations at 200$\mu$m. Conclusion: This work establishes the mathematical foundation for using the accelerated DREAM simulation method for cardiac electrophysiology. Cardiac research applications are enabled by a publicly available implementation in the openCARP simulator.

Abstract:

Background and Aims Patients with persistent atrial fibrillation (AF) experience 50% recurrence despite pulmonary vein isolation (PVI), and no consensus is established for second treatments. The aim of our i-STRATIFICATION study is to provide evidence for stratifying patients with AF recurrence after PVI to optimal pharmacological and ablation therapies, through in-silico trials.Methods A cohort of 800 virtual patients, with variability in atrial anatomy, electrophysiology, and tissue structure (low voltage areas, LVA), was developed and validated against clinical data from ionic currents to ECG. Virtual patients presenting AF post-PVI underwent 13 secondary treatments.Results Sustained AF developed in 522 virtual patients after PVI. Second ablation procedures involving left atrial ablation alone showed 55% efficacy, only succeeding in small right atria (<60mL). When additional cavo-tricuspid isthmus ablation was considered, Marshall-Plan sufficed (66% efficacy) for small left atria (<90mL). For bigger left atria, a more aggressive ablation approach was required, such as anterior mitral line (75% efficacy) or posterior wall isolation plus mitral isthmus ablation (77% efficacy). Virtual patients with LVA greatly benefited from LVA ablation in the left and right atria (100% efficacy). Conversely, in the absence of LVA, synergistic ablation and pharmacotherapy could terminate AF. In the absence of ablation, the patient’s ionic current substrate modulated the response to antiarrhythmic drugs, being the inward currents critical for optimal stratification to amiodarone or vernakalant.Conclusion In-silico trials identify optimal strategies for AF treatment based on virtual patient characteristics, evidencing the power of human modelling and simulation as a clinical assisting tool.

Abstract:

Simulation models and artificial intelligence (AI) are largely used to address healthcare and biomedical engineering problems. Both approaches showed promising results in the analysis and optimization of healthcare processes. Therefore, the combination of simulation models and AI could provide a strategy to further boost the quality of health services. In this work, a systematic review of studies applying a hybrid simulation models and AI approach to address healthcare management challenges was carried out. Scopus, Web of Science, and PubMed databases were screened by independent reviewers. The main strategies to combine simulation and AI as well as the major healthcare application scenarios were identified and discussed. Moreover, tools and algorithms to implement the proposed approaches were described. Results showed that machine learning appears to be the most employed AI strategy in combination with simulation models, which mainly rely on agent-based and discrete-event systems. The scarcity and heterogeneity of the included studies suggested that a standardized framework to implement hybrid machine learning-simulation approaches in healthcare management is yet to be defined. Future efforts should aim to use these approaches to design novel intelligent in-silico models of healthcare processes and to provide effective translation to the clinics.

Abstract:

Purpose: Handheld gamma cameras with coded aperture collimators are under inves- tigation for intraoperative imaging in nuclear medicine. Coded apertures are a promis- ing collimation technique for applications such as lymph node localization due to their high sensitivity and the possibility of 3D imaging. We evaluated the axial resolutionand computational performance of two reconstruction methods.Methods: An experimental gamma camera was set up consisting of the pixelated semiconductor detector Timepix3 and MURA mask of rank 31 with round holesof 0.08 mm in diameter in a 0.11 mm thick Tungsten sheet. A set of measurements was taken where a point-like gamma source was placed centrally at 21 different positions within the range of 12–100 mm. For each source position, the detector image was reconstructed in 0.5 mm steps around the true source position, resulting in an image stack. The axial resolution was assessed by the full width at half maximum (FWHM) of the contrast-to-noise ratio (CNR) profile along the z-axis of the stack. Two reconstruction methods were compared: MURA Decoding and a 3D maximum likeli- hood expectation maximization algorithm (3D-MLEM).Results: While taking 4400 times longer in computation, 3D-MLEM yielded a smaller axial FWHM and a higher CNR. The axial resolution degraded from 5.3 mm and 1.8 mm at 12 mm to 42.2 mm and 13.5 mm at 100 mm for MURA Decoding and 3D-MLEM respectively.Conclusion: Our results show that the coded aperture enables the depth estimation of single point-like sources in the near field. Here, 3D-MLEM offered a better axial reso- lution but was computationally much slower than MURA Decoding, whose reconstruc- tion time is compatible with real-time imaging.

Abstract:

Background: The global coronavirus disease 2019 (COVID-19) pandemic has posed substantial challenges for healthcare systems, notably the increased demand for chest computed tomography (CT) scans, which lack automated analysis. Our study addresses this by utilizing artificial intelligence-supported automated computer analysis to investigate lung involvement distribution and extent in COVID-19 patients. Additionally, we explore the association between lung involvement and intensive care unit (ICU) admission, while also comparing computer analysis performance with expert radiologists’ assessments.Methods: A total of 81 patients from an open-source COVID database with confirmed COVID-19 infection were included in the study. Three patients were excluded. Lung involvement was assessed in 78 patients using CT scans, and the extent of infiltration and collapse was quantified across various lung lobes and regions. The associations between lung involvement and ICU admission were analysed. Additionally, the computer analysis of COVID-19 involvement was compared against a human rating provided by radiological experts.Results: The results showed a higher degree of infiltration and collapse in the lower lobes compared to the upper lobes (P<0.05). No significant difference was detected in the COVID-19-related involvement of the left and right lower lobes. The right middle lobe demonstrated lower involvement compared to the right lower lobes (P<0.05). When examining the regions, significantly more COVID-19 involvement was found when comparing the posterior vs. the anterior halves and the lower vs. the upper half of the lungs. Patients, who required ICU admission during their treatment exhibited significantly higher COVID-19 involvement in their lung parenchyma according to computer analysis, compared to patients who remained in general wards. Patients with more than 40% COVID-19 involvement were almost exclusively treated in intensive care. A high correlation was observed between computer detection of COVID-19 affections and the rating by radiological experts.Conclusions: The findings suggest that the extent of lung involvement, particularly in the lower lobes, dorsal lungs, and lower half of the lungs, may be associated with the need for ICU admission in patients with COVID-19. Computer analysis showed a high correlation with expert rating, highlighting its potential utility in clinical settings for assessing lung involvement. This information may help guide clinical decision-making and resource allocation during ongoing or future pandemics. Further studies with larger sample sizes are warranted to validate these findings.

Abstract:

Feature importance methods promise to provide a ranking of features according to importance for a given classification task. A wide range of methods exist but their rankings often disagree and they are inherently difficult to evaluate due to a lack of ground truth beyond synthetic datasets. In this work, we put feature importance methods to the test on real-world data in the domain of cardiology, where we try to distinguish three specific pathologies from healthy subjects based on ECG features comparing to features used in cardiologists' decision rules as ground truth. We found that the SHAP and LIME methods and Chi-squared test all worked well together with the native Random forest and Logistic regression feature rankings. Some methods gave inconsistent results, which included the Maximum Relevance Minimum Redundancy and Neighbourhood Component Analysis methods. The permutation-based methods generally performed quite poorly. A surprising result was found in the case of left bundle branch block, where T-wave morphology features were consistently identified as being important for diagnosis, but are not used by clinicians.

Abstract:

We investigate the properties of static mechanical and dynamic electro-mechanical models for the deformation of the human heart. Numerically this is realized by a staggered scheme for the coupled partial/ordinary differential equation (PDE-ODE) system. First, we consider a static and purely mechanical benchmark configuration on a realistic geometry of the human ventricles. Using a penalty term for quasi-incompressibility, we test different parameters and mesh sizes and observe that this approach is not sufficient for lowest order conforming finite elements. Then, we compare the approaches of active stress and active strain for cardiac muscle contraction. Finally, we compare in a coupled anatomically realistic electro-mechanical model numerical Newmark damping with a visco-elastic model using Rayleigh damping. Nonphysiological oscillations can be better mitigated using viscosity.

Abstract:

Introduction: Photogrammetric surface scans provide a radiation-free option to assess and classify craniosynostosis. Due to the low prevalence of craniosynostosis and high patient restrictions, clinical data is rare. Synthetic data could support or even replace clinical data for the classification of craniosynostosis, but this has never been studied systematically. Methods: We test the combinations of three different synthetic data sources: a statistical shape model (SSM), a generative adversarial network (GAN), and image-based principal component analysis for a convolutional neural network (CNN)-based classification of craniosynostosis. The CNN is trained only on synthetic data, but validated and tested on clinical data. Results: The combination of a SSM and a GAN achieved an accuracy of more than 0.96 and a F1-score of more than 0.95 on the unseen test set. The difference to training on clinical data was smaller than 0.01. Including a second image modality improved classification performance for all data sources. Conclusion: Without a single clinical training sample, a CNN was able to classify head deformities as accurate as if it was trained on clinical data. Using multiple data sources was key for a good classification based on synthetic data alone. Synthetic data might play an important future role in the assessment of craniosynostosis.

Abstract:

PURPOSE: Synthetic realistic-looking bronchoscopic videos are needed to develop and evaluate depth estimation methods as part of investigating vision-based bronchoscopic navigation system. To generate these synthetic videos under the circumstance where access to real bronchoscopic images/image sequences is limited, we need to create various realistic-looking image textures of the airway inner surface with large size using a small number of real bronchoscopic image texture patches. METHODS: A generative adversarial networks-based method is applied to create realistic-looking textures of the airway inner surface by learning from a limited number of small texture patches from real bronchoscopic images. By applying a purely convolutional architecture without any fully connected layers, this method allows the production of textures with arbitrary size. RESULTS: Authentic image textures of airway inner surface are created. An example of the synthesized textures and two frames of the thereby generated bronchoscopic video are shown. The necessity and sufficiency of the generated textures as image features for further depth estimation methods are demonstrated. CONCLUSIONS: The method can generate textures of the airway inner surface that meet the requirements for the texture itself and for the thereby generated bronchoscopic videos, including "realistic-looking," "long-term temporal consistency," "sufficient image features for depth estimation," and "large size and variety of synthesized textures." Besides, it also shows advantages with respect to the easy accessibility to required data source. A further validation of this approach is planned by utilizing the realistic-looking bronchoscopic videos with textures generated by this method as training and test data for some depth estimation networks.

Abstract:

A minimally-invasive manipulator characterized by hyper-redundant kinematics and embedded sensing modules is presented in this work. The bending angles (tilt and pan) of the robot tip are controlled through tendon-driven actuation; the transmission of the actuation forces to the tip is based on a Bowden-cable solution integrating some channels for optical fibers. The viability of the real-time measurement of the feedback control variables, through optoelectronic acquisition, is evaluated for automated bending of the flexible endoscope and trajectory tracking of the tip angles. Indeed, unlike conventional catheters and cannulae adopted in neurosurgery, the proposed robot can extend the actuation and control of snake-like kinematic chains with embedded sensing solutions, enabling real-time measurement, robust and accurate control of curvature, and tip bending of continuum robots for the manipulation of cannulae and microsurgical instruments in neurosurgical procedures. A prototype of the manipulator with a length of 43 mm and a diameter of 5.5 mm has been realized via 3D printing. Moreover, a multiple regression model has been estimated through a novel experimental setup to predict the tip angles from measured outputs of the optoelectronic modules. The sensing and control performance has also been evaluated during tasks involving tip rotations.

Abstract:

Digital twins of patients' hearts are a promising tool to assess arrhythmia vulnerability and to personalize therapy. However, the process of building personalized computational models can be challenging and requires a high level of human interaction. We propose a patient-specific Augmented Atria generation pipeline (AugmentA) as a highly automated framework which, starting from clinical geometrical data, provides ready-to-use atrial personalized computational models. AugmentA identifies and labels atrial orifices using only one reference point per atrium. If the user chooses to fit a statistical shape model to the input geometry, it is first rigidly aligned with the given mean shape before a non-rigid fitting procedure is applied. AugmentA automatically generates the fiber orientation and finds local conduction velocities by minimizing the error between the simulated and clinical local activation time (LAT) map. The pipeline was tested on a cohort of 29 patients on both segmented magnetic resonance images (MRI) and electroanatomical maps of the left atrium. Moreover, the pipeline was applied to a bi-atrial volumetric mesh derived from MRI. The pipeline robustly integrated fiber orientation and anatomical region annotations in 38.4 ± 5.7 s. In conclusion, AugmentA offers an automated and comprehensive pipeline delivering atrial digital twins from clinical data in procedural time.

Abstract:

Cardiovascular diseases account for 17 million deaths per year worldwide. Of these, 25% are categorized as sudden cardiac death, which can be related to ventricular tachycardia (VT). This type of arrhythmia can be caused by focal activation sources outside the sinus node. Catheter ablation of these foci is a curative treatment in order to inactivate the abnormal triggering activity. However, the localization procedure is usually time-consuming and requires an invasive procedure in the catheter lab. To facilitate and expedite the treatment, we present two novel localization support techniques based on convolutional neural networks (CNNs) that address these clinical needs. In contrast to existing methods, our approaches were designed to be independent of the patient-specific geometry and directly applicable to surface ECG signals, while also delivering a binary transmural position. Moreover, one of the method's outputs can be interpreted as several ranked solutions. The CNNs were trained on a dataset containing only simulated data and evaluated both on simulated test data and clinical data. On a novel large and open simulated dataset, the median test error was below 3 mm. The median localization error on the unseen clinical data ranged from 32 mm to 41 mm without optimizing the pre-processing and CNN to the clinical data. Interpreting the output of one of the approaches as ranked solutions, the best median error of the top-3 solutions decreased to 20 mm on the clinical data. The transmural position was correctly detected in up to 82% of all clinical cases. These results demonstrate a proof of principle to utilize CNNs to localize the activation source without the intrinsic need for patient-specific geometrical information. Furthermore, providing multiple solutions can assist physicians in identifying the true activation source amongst more than one possible location. With further optimization to clinical data, these methods have high potential to accelerate clinical interventions, replace certain steps within these procedures and consequently reduce procedural risk and improve VT patient outcomes.

Abstract:

Atrial fibrillation (AF) is one of the most commoncardiac diseases. However, a complete understanding of howto treat patients suffering from AF is still not achieved. Asthe isolation of the pulmonary veins in the left atrium (LA)is the standard treatment for AF, the role of the right atrium(RA) in AF is rarely considered. We investigated the impactof including the RA on arrhythmia vulnerability in silico. Wegenerated a dataset of five mono-atrial (LA) and five bi-atrialmodels with three different electrophysiological (EP) setupseach, regarding different states of AF-induced remodelling.For every model, a pacing protocol was run to induce reen-tries from a set of stimulation points. The average share ofinducing points across all EP setups was 0.0, 0.8 and 6.7 %for the mono-atrial scenario, 0.5, 27.3 and 37.9 % for the bi-atrial scenario. The increase in inducibility of LA stimula-tion points from mono- to bi-atrial scenario was 0.91 ± 2.03%,34.55 ± 14.9 % and 44.2 ± 14.9 %, respectively. In this study,the RA had a marked impact on the results of the vulnerabilityassessment that needs to be further investigated.

Abstract:

The application of machine learning approachesin medical technology is gaining more and more attention.Due to the high restrictions for collecting intraoperative patientdata, synthetic data is increasingly used to support the trainingof artificial neural networks. We present a pipeline to createa statistical shape model (SSM) using 28 segmented clinicalliver CT scans. Our pipeline consists of four steps: data pre-processing, rigid alignment, template morphing, and statisti-cal modeling. We compared two different template morphingapproaches: Laplace-Beltrami-regularized projection (LBRP)and nonrigid iterative closest points translational (N-ICP-T)and evaluated both morphing approaches and their corre-sponding shape model performance using six metrics. LBRPachieved a smaller mean vertex-to-nearest-neighbor distances(2.486±0.897 mm) than N-ICP-T (5.559±2.413 mm). Gen-eralizationand specificity errors for LBRP were consistentlylower than those of N-ICP-T. The first principal componentsof the SSM showed realistic anatomical variations. The perfor-mance of the SSM was comparable to a state-of-the-art model.

Abstract:

Introduction: 3D surface scan-based diagnosis of craniosynostosis is a promising radiation-free alternative to traditional diagnosis using computed tomography. The cra- nial index (CI) and the cranial vault asymmetry index (CVAI) are well-established clinical parameters that are widely used. However, they also have the benefit of being easily adaptable for automatic diagnosis without the need of extensive prepro- cessing.Methods: We propose a multi-height-based classification ap- proach that uses CI and CVAI in different height layers and compare it to the initial approach using only one layer. We use ten-fold cross-validation and test seven different classi- fiers. The dataset of 504 patients consists of three types of craniosynostosis and a control group consisting of healthy and non-synostotic subjects.Results: The multi-height-based approach improved classifica- tion for all classifiers. The k-nearest neighbors classifier scored best with a mean accuracy of 89 % and a mean F1-score of 0.75.Conclusion: Taking height into account is beneficial for the classification. Based on accepted and widely used clinical pa- rameters, this might be a step towards an easy-to-understand and transparent classification approach for both physicians and patients.

Abstract:

Optical Coherence Tomography (OCT) is a stan- dard imaging procedure in ophthalmology. OCT Angiography is a promising extension, allowing for fast and non-invasive imaging of the retinal vasculature analyzing multiple OCT scans at the same place. Local variance is examined and highlighted. Despite its introduction in the clinic, unanswered questions remain when it comes to signal generation. Multi- phase fluids like intralipid, milk-water solutions and human blood cells were applied in phantom studies shedding light on some of the mechanisms. The use of hydrogel beads allows for the generation of alternative blood models for OCT and OCT Angiography. Beads were produced in Hannover, their size was measured and their long term stability was assessed. Then, beads were shipped to Karlsruhe, where OCT imaging resulted in first insights. The hydrogel acts as a diffusion barrier, which enables a clear distinction of bead and fluid when scattering particles were added. Further on, the scattering medium be- low the bead showed increased signal intensity. We conclude that the inside of the bead structure shows enhanced transmis- sion compared to the plasma substitute with dissolved TiO2 surrounding it. Beads were found clumped and deformed af- ter shipping, an issue to be addressed in further investigations. Nevertheless, hydrogel beads are promising as a blood model for OCT Angiography investigations, offering tunable optical parameters within the blood substitute solution.

Abstract:

During cerebral revascularization surgeries, blood flow values help surgeons to monitor the quality of the pro- cedure, e.g., to avoid cerebral hyperperfusion syndrome due to excessively enhanced perfusion. The state-of-the-art technique is the ultrasonic flow probe that has to be placed around the blood vessel. This causes contact between probe and vessel, which, in the worst case, leads to rupture. The recently devel- oped intraoperative indocyanine green (ICG) Quantitative Flu- orescence Angiography (QFA) is an alternative technique that overcomes this risk. However, it has been shown by the devel- oper that the calculated flow has deviations. After determining the bolus transit time as the most sensitive parameter in flow calculation, we propose a new two-step uncertainty reduction method for flow calculation. The first step is to generate more data in each measurement that results in functions of the pa- rameters. Noise can then be reduced in a second step. Two methods for this step are compared. The first method fits the model for each parameter function separately and calculates flow from models, while the second one fits multiple parame- ter functions together. The latter method is proven to perform best by in silico tests. Besides, this method reduces the de- viation of flow comparing to original QFA as expected. Our approach can be generally used in all QFA applications using two-point theory. Further development is possible if number of dimensions of the achieved parameter data are broadened that results in even more data for processing in the second step.

Abstract:

PURPOSE: Depth estimation is the basis of 3D reconstruction of airway structure from 2D bronchoscopic scenes, which can be further used to develop a vision-based bronchoscopic navigation system. This work aims to improve the performance of depth estimation directly from bronchoscopic images by training a depth estimation network on both synthetic and real datasets. METHODS: We propose a cGAN-based network Bronchoscopic-Depth-GAN (BronchoDep-GAN) to estimate depth from bronchoscopic images by translating bronchoscopic images into depth maps. The network is trained in a supervised way learning from synthetic textured bronchoscopic image-depth pairs and virtual bronchoscopic image-depth pairs, and simultaneously, also in an unsupervised way learning from unpaired real bronchoscopic images and depth maps to adapt the model to real bronchoscopic scenes. RESULTS: Our method is tested on both synthetic data and real data. However, the tests on real data are only qualitative, as no ground truth is available. The results show that our network obtains better accuracy in all cases in estimating depth from bronchoscopic images compared to the well-known cGANs pix2pix. CONCLUSIONS: Including virtual and real bronchoscopic images in the training phase of the depth estimation networks can improve depth estimation's performance on both synthetic and real scenes. Further validation of this work is planned on 3D clinical phantoms. Based on the depth estimation results obtained in this work, the accuracy of locating bronchoscopes with corresponding pre-operative CTs will also be evaluated in comparison with the current clinical status.

Abstract:

Mechanistic cardiac electrophysiology models allow for personalized simulations of the electrical activity in the heart and the ensuing electrocardiogram (ECG) on the body surface. As such, synthetic signals possess known ground truth labels of the underlying disease and can be employed for validation of machine learning ECG analysis tools in addition to clinical signals. Recently, synthetic ECGs were used to enrich sparse clinical data or even replace them completely during training leading to improved performance on real-world clinical test data. We thus generated a novel synthetic database comprising a total of 16,900 12 lead ECGs based on electrophysiological simulations equally distributed into healthy control and 7 pathology classes. The pathological case of myocardial infraction had 6 sub-classes. A comparison of extracted features between the virtual cohort and a publicly available clinical ECG database demonstrated that the synthetic signals represent clinical ECGs for healthy and pathological subpopulations with high fidelity. The ECG database is split into training, validation, and test folds for development and objective assessment of novel machine learning algorithms.

Abstract:

AIMS: Electro-anatomical voltage, conduction velocity (CV) mapping, and late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) have been correlated with atrial cardiomyopathy (ACM). However, the comparability between these modalities remains unclear. This study aims to (i) compare pathological substrate extent and location between current modalities, (ii) establish spatial histograms in a cohort, (iii) develop a new estimated optimized image intensity threshold (EOIIT) for LGE-MRI identifying patients with ACM, (iv) predict rhythm outcome after pulmonary vein isolation (PVI) for persistent atrial fibrillation (AF). METHODS AND RESULTS: Thirty-six ablation-naive persistent AF patients underwent LGE-MRI and high-definition electro-anatomical mapping in sinus rhythm. Late gadolinium enhancement areas were classified using the UTAH, image intensity ratio (IIR >1.20), and new EOIIT method for comparison to low-voltage substrate (LVS) and slow conduction areas <0.2 m/s. Receiver operating characteristic analysis was used to determine LGE thresholds optimally matching LVS. Atrial cardiomyopathy was defined as LVS extent ≥5% of the left atrium (LA) surface at <0.5 mV. The degree and distribution of detected pathological substrate (percentage of individual LA surface are) varied significantly (P < 0.001) across the mapping modalities: 10% (interquartile range 0-14%) of the LA displayed LVS <0.5 mV vs. 7% (0-12%) slow conduction areas <0.2 m/s vs. 15% (8-23%) LGE with the UTAH method vs. 13% (2-23%) using IIR >1.20, with most discrepancies on the posterior LA. Optimized image intensity thresholds and each patient's mean blood pool intensity correlated linearly (R2 = 0.89, P < 0.001). Concordance between LGE-MRI-based and LVS-based ACM diagnosis improved with the novel EOIIT applied at the anterior LA [83% sensitivity, 79% specificity, area under the curve (AUC): 0.89] in comparison to the UTAH method (67% sensitivity, 75% specificity, AUC: 0.81) and IIR >1.20 (75% sensitivity, 62% specificity, AUC: 0.67). CONCLUSION: Discordances in detected pathological substrate exist between LVS, CV, and LGE-MRI in the LA, irrespective of the LGE detection method. The new EOIIT method improves concordance of LGE-MRI-based ACM diagnosis with LVS in ablation-naive AF patients but discrepancy remains particularly on the posterior wall. All methods may enable the prediction of rhythm outcomes after PVI in patients with persistent AF.

Abstract:

Purpose: To evaluate the impact of lens opacity on the reliability of optical coherence tomog- raphy angiography metrics and to find a vessel caliber threshold that is reproducible in cataract patients.Methods: A prospective cohort study of 31 patients, examining one eye per patient, by applying 33mm macular optical coherence tomography angiography before (18.94±12.22days) and 3 months (111 ± 23.45 days) after uncomplicated cataract surgery. We extracted superficial (SVC) and deep vascular plexuses (DVC) for further analysis and evaluated changes in image contrast, vessel metrics (perfusion density, flow deficit and vessel-diameter index) and foveal avascular area (FAZ). Results: After surgery, the blood flow signal in smaller capillaries was enhanced as image contrast improved. Signal strength correlated to average lens density defined by objective measurement in Scheimpflug images (Pearson’s r: –.40, p: .027) and to flow deficit (r1⁄4 –.70, p<.001). Perfusion density correlated to the signal strength index (r1⁄4.70, p<.001). Vessel metrics and FAZ area, except for FAZ area in DVC, were significantly different after cataract surgery, but the mean change was approximately 3–6%. A stepwise approach in extracting vessels according to their pixel caliber showed a threshold of > 6 pixels caliber ($20–30 mm) was comparable before and after lens removal.Conclusion: In patients with cataract, OCTA vessel metrics should be interpreted with caution. In addition to signal strength, contrast and pixel properties can serve as supplementary quality met- rics to improve the interpretation of OCTA metrics. Vessels with $20–30 mm in caliber seem to be reproducible.

Abstract:

INTRODUCTION: Improved sinus rhythm (SR) maintenance rates have been achieved in patients with persistent atrial fibrillation (AF) undergoing pulmonary vein isolation plus additional ablation of low voltage substrate (LVS) during SR. However, voltage mapping during SR may be hindered in persistent and long-persistent AF patients by immediate AF recurrence after electrical cardioversion. We assess correlations between LVS extent and location during SR and AF, aiming to identify regional voltage thresholds for rhythm-independent delineation/detection of LVS areas. (1) Identification of voltage dissimilarities between mapping in SR and AF. (2) Identification of regional voltage thresholds that improve cross-rhythm substrate detection. (3) Comparison of LVS between SR and native versus induced AF. METHODS: Forty-one ablation-naive persistent AF patients underwent high-definition (1 mm electrodes; >1200 left atrial (LA) mapping sites per rhythm) voltage mapping in SR and AF. Global and regional voltage thresholds in AF were identified which best match LVS < 0.5 mV and <1.0 mV in SR. Additionally, the correlation between SR-LVS with induced versus native AF-LVS was assessed. RESULTS: Substantial voltage differences (median: 0.52, interquartile range: 0.33-0.69, maximum: 1.19 mV) with a predominance of the posterior/inferior LA wall exist between the rhythms. An AF threshold of 0.34 mV for the entire left atrium provides an accuracy, sensitivity and specificity of 69%, 67%, and 69% to identify SR-LVS < 0.5 mV, respectively. Lower thresholds for the posterior wall (0.27 mV) and inferior wall (0.3 mV) result in higher spatial concordance to SR-LVS (4% and 7% increase). Concordance with SR-LVS was higher for induced AF compared to native AF (area under the curve[AUC]: 0.80 vs. 0.73). AF-LVS < 0.5 mV corresponds to SR-LVS < 0.97 mV (AUC: 0.73). CONCLUSION: Although the proposed region-specific voltage thresholds during AF improve the consistency of LVS identification as determined during SR, the concordance in LVS between SR and AF remains moderate, with larger LVS detection during AF. Voltage-based substrate ablation should preferentially be performed during SR to limit the amount of ablated atrial myocardium.

Abstract:

Machine learning (ML) methods for the analysis of electrocardiography (ECG) data are gaining importance, substantially supported by the release of large public datasets. However, these current datasets miss important derived descriptors such as ECG features that have been devised in the past hundred years and still form the basis of most automatic ECG analysis algorithms and are critical for cardiologists' decision processes. ECG features are available from sophisticated commercial software but are not accessible to the general public. To alleviate this issue, we add ECG features from two leading commercial algorithms and an open-source implementation supplemented by a set of automatic diagnostic statements from a commercial ECG analysis software in preprocessed format. This allows the comparison of ML models trained on clinically versus automatically generated label sets. We provide an extensive technical validation of features and diagnostic statements for ML applications. We believe this release crucially enhances the usability of the PTB-XL dataset as a reference dataset for ML methods in the context of ECG data.

Abstract:

Clonogenic assays are routinely used to evaluate the response of cancer cells to external radiation fields, assess their radioresistance and radiosensitivity, estimate the performance of radiotherapy. However, classic clonogenic tests focus on the number of colonies forming on a substrate upon exposure to ionizing radiation, and disregard other important characteristics of cells such their ability to generate structures with a certain shape. The radioresistance and radiosensitivity of cancer cells may depend less on the number of cells in a colony and more on the way cells interact to form complex networks. In this study, we have examined whether the topology of 2D cancer-cell graphs is influenced by ionizing radiation. We subjected different cancer cell lines, i.e. H4 epithelial neuroglioma cells, H460 lung cancer cells, PC3 bone metastasis of grade IV of prostate cancer and T24 urinary bladder cancer cells, cultured on planar surfaces, to increasing photon radiation levels up to 6 Gy. Fluorescence images of samples were then processed to determine the topological parameters of the cell-graphs developing over time. We found that the larger the dose, the less uniform the distribution of cells on the substrate—evidenced by high values of small-world coefficient (cc), high values of clustering coefficient (cc), and small values of characteristic path length (cpl). For all considered cell lines, 𝑠𝑤>1 for doses higher or equal to 4 Gy, while the sensitivity to the dose varied for different cell lines: T24 cells seem more distinctly affected by the radiation, followed by the H4, H460 and PC3 cells. Results of the work reinforce the view that the characteristics of cancer cells and their response to radiotherapy can be determined by examining their collective behavior—encoded in a few topological parameters—as an alternative to classical clonogenic assays.

Abstract:

Purpose Primary central nervous system lymphoma (PCNSL) is a rare, aggressive form of extranodal non-Hodgkin lym- phoma. To predict the overall survival (OS) in advance is of utmost importance as it has the potential to aid clinical decision-making. Though radiomics-based machine learning (ML) has demonstrated the promising performance in PCNSL, it demands large amounts of manual feature extraction efforts from magnetic resonance images beforehand. deep learning (DL) overcomes this limitation.Methods In this paper, we tailored the 3D ResNet to predict the OS of patients with PCNSL. To overcome the limitation of data sparsity, we introduced data augmentation and transfer learning, and we evaluated the results using r stratified k-fold cross-validation. To explain the results of our model, gradient-weighted class activation mapping was applied.Results We obtained the best performance (the standard error) on post-contrast T1-weighted (T1Gd)—area under curve = 0.81(0.03), accuracy = 0.87(0.07), precision = 0.88(0.07), recall = 0.88(0.07) and F1-score = 0.87(0.07), while compared with ML-based models on clinical data and radiomics data, respectively, further confirming the stability of our model. Also, we observed that PCNSL is a whole-brain disease and in the cases where the OS is less than 1 year, it is more difficult to distinguish the tumor boundary from the normal part of the brain, which is consistent with the clinical outcome. Conclusions All these findings indicate that T1Gd can improve prognosis predictions of patients with PCNSL. To the best of our knowledge, this is the first time to use DL to explain model patterns in OS classification of patients with PCNSL. Future work would involve collecting more data of patients with PCNSL, or additional retrospective studies on different patient populations with rare diseases, to further promote the clinical role of our model.

Abstract:

PURPOSE: Atrial fibrillation is one of the most frequent cardiac arrhythmias in the industrialized world and ablation therapy is the method of choice for many patients. However, ablation scars alter the electrophysiological activation and the mechanical behavior of the affected atria. Different ablation strategies with the aim to terminate atrial fibrillation and prevent its recurrence exist but their impact on the performance of the heart is often neglected. METHODS: In this work, we present a simulation study analyzing five commonly used ablation scar patterns and their combinations in the left atrium regarding their impact on the pumping function of the heart using an electromechanical whole-heart model. We analyzed how the altered atrial activation and increased stiffness due to the ablation scars affect atrial as well as ventricular contraction and relaxation. RESULTS: We found that systolic and diastolic function of the left atrium is impaired by ablation scars and that the reduction of atrial stroke volume of up to 11.43% depends linearly on the amount of inactivated tissue. Consequently, the end-diastolic volume of the left ventricle, and thus stroke volume, was reduced by up to 1.4 and 1.8%, respectively. During ventricular systole, left atrial pressure was increased by up to 20% due to changes in the atrial activation sequence and the stiffening of scar tissue. CONCLUSION: This study provides biomechanical evidence that atrial ablation has acute effects not only on atrial contraction but also on ventricular performance. Therefore, the position and extent of ablation scars is not only important for the termination of arrhythmias but is also determining long-term pumping efficiency. If confirmed in larger cohorts, these results have the potential to help tailoring ablation strategies towards minimal global cardiovascular impairment.

Abstract:

Background and Objective: Planning the optimal ablation strategy for the treatment of complex atrial tachycardia (CAT) is a time consuming task and is error-prone. Recently, directed network mapping, a technology based on graph theory, proved to efficiently identify CAT based solely on data of clinical interventions. Briefly, a directed network was used to model the atrial electrical propagation and reentrant activities were identified by looking for closed-loop paths in the network. In this study, we propose a recommender system, built as an optimization problem, able to suggest the optimal ablation strategy for the treatment of CAT.Methods: The optimization problem modeled the optimal ablation strategy as that one interrupting all reentrant mechanisms while minimizing the ablated atrial surface. The problem was designed on top of directed network mapping. Considering the exponential complexity of finding the optimal solution of the problem, we introduced a heuristic algorithm with polynomial complexity. The proposed algorithm was applied to the data of i) 6 simulated scenarios including both left and right atrial flutter; and ii) 10 subjects that underwent a clinical routine.Results: The recommender system suggested the optimal strategy in 4 out of 6 simulated scenarios. On clinical data, the recommended ablation lines were found satisfactory on 67% of the cases according to the clinician’s opinion, while they were correctly located in 89%. The algorithm made use of only data collected during mapping and was able to process them nearly real-time.Conclusions: The first recommender system for the identification of the optimal ablation lines for CAT, based solely on the data collected during the intervention, is presented. The study may open up interesting scenarios for the application of graph theory for the treatment of CAT.

Abstract:

Primary Central Nervous System Lymphoma (PCNSL) is an aggressive neoplasm with a poor prognosis. Although therapeutic progresses have significantly improved Overall Survival (OS), a number of patients do not respond to HD–MTX-based chemotherapy (15–25%) or experience relapse (25–50%) after an initial response. The reasons underlying this poor response to therapy are unknown. Thus, there is an urgent need to develop improved predictive models for PCNSL. In this study, we investigated whether radiomics features can improve outcome prediction in patients with PCNSL. A total of 80 patients diagnosed with PCNSL were enrolled. A patient sub-group, with complete Magnetic Resonance Imaging (MRI) series, were selected for the stratification analysis. Following radiomics feature extraction and selection, different Machine Learning (ML) models were tested for OS and Progression-free Survival (PFS) prediction. To assess the stability of the selected features, images from 23 patients scanned at three different time points were used to compute the Interclass Correlation Coefficient (ICC) and to evaluate the reproducibility of each feature for both original and normalized images. Features extracted from Z-score normalized images were significantly more stable than those extracted from non-normalized images with an improvement of about 38% on average (p-value < 10−12). The area under the ROC curve (AUC) showed that radiomics-based prediction overcame prediction based on current clinical prognostic factors with an improvement of 23% for OS and 50% for PFS, respectively. These results indicate that radiomics features extracted from normalized MR images can improve prognosis stratification of PCNSL patients and pave the way for further study on its potential role to drive treatment choice.

Abstract:

AIMS: The long-term success rate of ablation therapy is still sub-optimal in patients with persistent atrial fibrillation (AF), mostly due to arrhythmia recurrence originating from arrhythmogenic sites outside the pulmonary veins. Computational modelling provides a framework to integrate and augment clinical data, potentially enabling the patient-specific identification of AF mechanisms and of the optimal ablation sites. We developed a technology to tailor ablations in anatomical and functional digital atrial twins of patients with persistent AF aiming to identify the most successful ablation strategy. METHODS AND RESULTS: Twenty-nine patient-specific computational models integrating clinical information from tomographic imaging and electro-anatomical activation time and voltage maps were generated. Areas sustaining AF were identified by a personalized induction protocol at multiple locations. State-of-the-art anatomical and substrate ablation strategies were compared with our proposed Personalized Ablation Lines (PersonAL) plan, which consists of iteratively targeting emergent high dominant frequency (HDF) regions, to identify the optimal ablation strategy. Localized ablations were connected to the closest non-conductive barrier to prevent recurrence of AF or atrial tachycardia. The first application of the HDF strategy had a success of >98% and isolated only 5-6% of the left atrial myocardium. In contrast, conventional ablation strategies targeting anatomical or structural substrate resulted in isolation of up to 20% of left atrial myocardium. After a second iteration of the HDF strategy, no further arrhythmia episode could be induced in any of the patient-specific models. CONCLUSION: The novel PersonAL in silico technology allows to unveil all AF-perpetuating areas and personalize ablation by leveraging atrial digital twins.

Abstract:

The bidomain model and the finite element method are an established standard to mathematically describe cardiac electrophysiology, but are both suboptimal choices for fast and large-scale simulations due to high computational costs. We investigate to what extent simplified approaches for propagation models (monodomain, reaction-Eikonal and Eikonal) and forward calculation (boundary element and infinite volume conductor) deliver markedly accelerated, yet physiologically accurate simulation results in atrial electrophysiology. <i>Methods:</i> We compared action potential durations, local activation times (LATs), and electrocardiograms (ECGs) for sinus rhythm simulations on healthy and fibrotically infiltrated atrial models. <i>Results:</i> All simplified model solutions yielded LATs and P&#x00A0;waves in accurate accordance with the bidomain results. Only for the Eikonal model with pre-computed action potential templates shifted in time to derive transmembrane voltages, repolarization behavior notably deviated from the bidomain results. ECGs calculated with the boundary element method were characterized by correlation coefficients <inline-formula><tex-math notation="LaTeX">$&gt;$</tex-math></inline-formula>0.9 compared to the finite element method. The infinite volume conductor method led to lower correlation coefficients caused predominantly by systematic overestimations of P&#x00A0;wave amplitudes in the precordial leads. <i>Conclusion:</i> Our results demonstrate that the Eikonal model yields accurate LATs and combined with the boundary element method precise ECGs compared to markedly more expensive full bidomain simulations. However, for an accurate representation of atrial repolarization dynamics, diffusion terms must be accounted for in simplified models. <i>Significance:</i> Simulations of atrial LATs and ECGs can be notably accelerated to clinically feasible time frames at high accuracy by resorting to the Eikonal and boundary element methods.

Abstract:

Background: Progressive atrial fibrotic remodeling has been reported to be associated with atrial cardiomyopathy (ACM) and the transition from paroxysmal to persistent atrial fibrillation (AF). We sought to identify the anatomical/structural and electrophysiological factors involved in atrial remodeling that promote AF persistency.Methods: Consecutive patients with paroxysmal (n = 134) or persistent (n = 136) AF who presented for their first AF ablation procedure were included. Patients underwent left atrial (LA) high-definition mapping (1,835 ± 421 sites/map) during sinus rhythm (SR) and were randomized to training and validation sets for model development and evaluation. A total of 62 parameters from both electro-anatomical mapping and non-invasive baseline data were extracted encompassing four main categories: (1) LA size, (2) extent of low-voltage-substrate (LVS), (3) LA voltages and (4) bi-atrial conduction time as identified by the duration of amplified P-wave (APWD) in a digital 12-lead-ECG. Least absolute shrinkage and selection operator (LASSO) and logistic regression were performed to identify the factors that are most relevant to AF persistency in each category alone and all categories combined. The performance of the developed models for diagnosis of AF persistency was validated regarding discrimination, calibration and clinical usefulness. In addition, HATCH score and C2HEST score were also evaluated for their performance in identification of AF persistency.Results: In training and validation sets, APWD (threshold 151 ms), LA volume (LAV, threshold 94 mL), bipolar LVS area < 1.0 mV (threshold 4.55 cm2) and LA global mean voltage (GMV, threshold 1.66 mV) were identified as best determinants for AF persistency in the respective category. Moreover, APWD (AUC 0.851 and 0.801) and LA volume (AUC 0.788 and 0.741) achieved better discrimination between AF types than LVS extent (AUC 0.783 and 0.682) and GMV (AUC 0.751 and 0.707). The integrated model (combining APWD and LAV) yielded the best discrimination performance between AF types (AUC 0.876 in training set and 0.830 in validation set). In contrast, HATCH score and C2HEST score only achieved AUC < 0.60 in identifying individuals with persistent AF in current study.Conclusion: Among 62 electro-anatomical parameters, we identified APWD, LA volume, LVS extent, and mean LA voltage as the four determinant electrophysiological and structural factors that are most relevant for AF persistency. Notably, the combination of APWD with LA volume enabled discrimination between paroxysmal and persistent AF with high accuracy, emphasizing their importance as underlying substrate of persistent AF.

Abstract:

The KCNQ1 gene encodes the α-subunit of the cardiac voltage-gated potassium (Kv) channel KCNQ1, also denoted as Kv7.1 or KvLQT1. The channel assembles with the ß-subunit KCNE1, also known as minK, to generate the slowly activating cardiac delayed rectifier current IKs, a key regulator of the heart rate dependent adaptation of the cardiac action potential duration (APD). Loss-of-function variants in KCNQ1 cause the congenital Long QT1 (LQT1) syndrome, characterized by delayed cardiac repolarization and a QT interval prolongation in the surface electrocardiogram (ECG). Autosomal dominant loss-of-function variants in KCNQ1 result in the LQT syndrome called Romano-Ward syndrome (RWS), while autosomal recessive variants affecting function, lead to Jervell and Lange-Nielsen syndrome (JLNS), associated with deafness. The aim of this study was the characterization of novel KCNQ1 variants identified in patients with RWS to widen the spectrum of known LQT1 variants, and improve the interpretation of the clinical relevance of variants in the KCNQ1 gene. We functionally characterized nine human KCNQ1 variants using the voltage-clamp technique in Xenopus laevis oocytes, from which we report seven novel variants. The functional data was taken as input to model surface ECGs, to subsequently compare the functional changes with the clinically observed QTc times, allowing a further interpretation of the severity of the different LQTS variants. We found that the electrophysiological properties of the variants correlate with the severity of the clinically diagnosed phenotype in most cases, however, not in all. Electrophysiological studies combined with in silico modelling approaches are valuable components for the interpretation of the pathogenicity of KCNQ1 variants, but assessing the clinical severity demands the consideration of other factors that are included, for example in the Schwartz score.

Abstract:

Life-threatening cardiac arrhythmias require immediate defibrillation. For state-of-the-art shock treatments, a high field strength is required to achieve a sufficient success rate for terminating the complex spiral wave (rotor) dynamics underlying cardiac fibrillation. However, such high energy shocks have many adverse side effects due to the large electric currents applied. In this study, we show, using 2D simulations based on the Fenton-Karma model, that also pulses of relatively low energy may terminate the chaotic activity if applied at the right moment in time. In our simplified model for defibrillation, complex spiral waves are terminated by local perturbations corresponding to conductance heterogeneities acting as virtual electrodes in the presence of an external electric field. We demonstrate that time series of the success rate for low energy shocks exhibit pronounced peaks which correspond to short intervals in time during which perturbations aiming at terminating the chaotic fibrillation state are (much) more successful. Thus, the low energy shock regime, although yielding very low temporal average success rates, exhibits moments in time for which success rates are significantly higher than the average value shown in dose-response curves. This feature might be exploited in future defibrillation protocols for achieving high termination success rates with low or medium pulse energies.

Abstract:

Imaging distributions of radioactive sources plays a substantial role in nuclear medicine as well as in monitoring nuclear waste and its deposit. Coded Aperture Imaging (CAI) has been proposed as an alternative to parallel or pinhole collimators, but requires image reconstruction as an extra step. Multiple reconstruction methods with varying run time and computational complexity have been proposed. Yet, no quantitative comparison between the different reconstruction methods has been carried out so far. This paper focuses on a comparison based on three sets of hot-rod phantom images captured with an experimental γ-camera consisting of a Tungsten-based MURA mask with a 2 mm thick 256 × 256 pixelated CdTe semiconductor detector coupled to a Timepix© readout circuit. Analytical reconstruction methods, MURA Decoding, Wiener Filter and a convolutional Maximum Likelihood Expectation Maximization (MLEM) algorithm were compared to data-driven Convolutional Encoder-Decoder (CED) approaches. The comparison is based on the contrast-to-noise ratio as it has been previously used to assess reconstruction quality. For the given set-up, MURA Decoding, the most commonly used CAI reconstruction method, provides robust reconstructions despite the assumption of a linear model. For single image reconstruction, however, MLEM performed best of all analytical reconstruction methods, but took on average 45 times longer than MURA Decoding. The fastest reconstruction method is the Wiener Filter with a run time 4.3 times faster compared to MURA Decoding and a mediocre quality. The CED with a specifically tailored training set was able to succeed the most commonly used MURA decoding on average by a factor between 1.37 and 2.60 and an equal run time.

Abstract:

Artificial intelligence technology is trending in nearly every medical area. It offers the possibility for improving analytics, therapy outcome, and user experience during therapy. In dialysis, the application of artificial intelligence as a therapy-individualization tool is led more by start-ups than consolidated players, and innovation in dialysis seems comparably stagnant. Factors such as technical requirements or regulatory processes are important and necessary but can slow down the implementation of artificial intelligence due to missing data infrastructure and undefined approval processes. Current research focuses mainly on analyzing health records or wearable technology to add to existing health data. It barely uses signal data from treatment devices to apply artificial intelligence models. This article, therefore, discusses requirements for signal processing through artificial intelligence in health care and compares these with the status quo in dialysis therapy. It offers solutions for given barriers to speed up innovation with sensor data, opening access to existing and untapped sources, and shows the unique advantage of signal processing in dialysis compared to other health care domains. This research shows that even though the combination of different data is vital for improving patients' therapy, adding signal-based treatment data from dialysis devices to the picture can benefit the understanding of treatment dynamics, improving and individualizing therapy.

Abstract:

Objective: Diagnosis of craniosynostosis using photogrammetric 3D surface scans is a promising radiation-free alternative to traditional computed tomography. We propose a 3D surface scan to 2D distance map conversion enabling the usage of the first convolutional neural networks (CNNs)-based classification of craniosynostosis. Benefits of using 2D images include preserving patient anonymity, enabling data augmentation during training, and a strong under-sampling of the 3D surface with good classification performance.Methods: The proposed distance maps sample 2D images from 3D surface scans using a coordinate transformation, ray casting, and distance extraction. We introduce a CNNbased classification pipeline and compare our classifier to alternative approaches on a dataset of 496 patients. We investigate into low-resolution sampling, data augmentation, and attribution mapping.Results: Resnet18 outperformed alternative classifiers on our dataset with an F1-score of 0.964 and an accuracy of 98.4 %. Data augmentation on 2D distance maps increased performance for all classifiers. Under-sampling allowed 256-fold computation reduction during ray casting while retaining an F1-score of 0.92. Attribution maps showed high amplitudes on the frontal head.Conclusion: We demonstrated a versatile mapping approach to extract a 2D distance map from the 3D head geometry increasing classification performance, enabling data augmentation during training on 2D distance maps, and the usage of CNNs. We found that low-resolution images were sufficient for a good classification performance.Significance: Photogrammetric surface scans are a suitable craniosynostosis diagnosis tool for clinical practice. Domain transfer to computed tomography seems likely and can further contribute to reducing ionizing radiation exposure for infants.

Abstract:

BACKGROUND: Electrical impedance measurements have become an accepted tool for monitoring intracardiac radio frequency ablation. Recently, the long-established generator impedance was joined by novel local impedance measurement capabilities with all electrical circuit terminals being accommodated within the catheter. OBJECTIVE: This work aims at in silico quantification of distinct influencing factors that have remained challenges due to the lack of ground truth knowledge and the superposition of effects in clinical settings. METHODS: We introduced a highly detailed in silico model of two local impedance enabled catheters, namely IntellaNav MiFi™ OI and IntellaNav Stablepoint™, embedded in a series of clinically relevant environments. Assigning material and frequency specific conductivities and subsequently calculating the spread of the electrical field with the finite element method yielded in silico local impedances. The in silico model was validated by comparison to in vitro measurements of standardized sodium chloride solutions. We then investigated the effect of the withdrawal of the catheter into the transseptal sheath, catheter-tissue interaction, insertion of the catheter into pulmonary veins, and catheter irrigation. RESULTS: All simulated setups were in line with in vitro experiments and in human measurements and gave detailed insight into determinants of local impedance changes as well as the relation between values measured with two different devices. CONCLUSION: The in silico environment proved to be capable of resembling clinical scenarios and quantifying local impedance changes. SIGNIFICANCE: The tool can assists the interpretation of measurements in humans and has the potential to support future catheter development.

Abstract:

Approximating the fast dynamics of depolarization waves in the human heart described by the monodomain model is numerically challenging. Splitting methods for the PDE-ODE coupling enable the computation with very fine space and time discretizations. Here, we compare different splitting approaches regarding convergence, accuracy, and efficiency. Simulations were performed for a benchmark problem with the Beeler-Reuter cell model on a truncated ellipsoid approximating the left ventricle including a localized stimulation. For this configuration, we provide a reference solution for the transmembrane potential. We found a semi-implicit approach with state variable interpolation to be the most efficient scheme. The results are transferred to a more physiological setup using a bi-ventricular domain with a complex external stimulation pattern to evaluate the accuracy of the activation time for different resolutions in space and time.

Abstract:

Sinus node (SN) pacemaking is based on a coupling between surface membrane ion-channels and intracellular Ca2+-handling. The fundamental role of the inward Na+/Ca2+ exchanger (NCX) is firmly established. However, little is known about the reverse mode exchange. A simulation study attributed important role to reverse NCX activity, however experimental evidence is still missing. Whole-cell and perforated patch-clamp experiments were performed on rabbit SN cells supplemented with fluorescent Ca2+-tracking. We established 2 and 8 mM pipette NaCl groups to suppress and enable reverse NCX. NCX was assessed by specific block with 1 μM ORM-10962. Mechanistic simulations were performed by Maltsev–Lakatta minimal computational SN model. Active reverse NCX resulted in larger Ca2+-transient amplitude with larger SR Ca2+-content. Spontaneous action potential (AP) frequency increased with 8 mM NaCl. When reverse NCX was facilitated by 1 μM strophantin the Ca2+i and spontaneous rate increased. ORM-10962 applied prior to strophantin prevented Ca2+i and AP cycle change. Computational simulations indicated gradually increasing reverse NCX current, Ca2+i and heart rate with increasing Na+i. Our results provide further evidence for the role of reverse NCX in SN pacemaking. The reverse NCX activity may provide additional Ca2+-influx that could increase SR Ca2+-content, which consequently leads to enhanced pacemaking activity.

Abstract:

The sinoatrial node (SAN) is a complex structure that spontaneously depolarizes rhythmically ("pacing") and excites the surrounding non-automatic cardiac cells ("drive") to initiate each heart beat. However, the mechanisms by which the SAN cells can activate the large and hyperpolarized surrounding cardiac tissue are incompletely understood. Experimental studies demonstrated the presence of an insulating border that separates the SAN from the hyperpolarizing influence of the surrounding myocardium, except at a discrete number of sinoatrial exit pathways (SEPs). We propose a highly detailed 3D model of the human SAN, including 3D SEPs to study the requirements for successful electrical activation of the primary pacemaking structure of the human heart. A total of 788 simulations investigate the ability of the SAN to pace and drive with different heterogeneous characteristics of the nodal tissue (gradient and mosaic models) and myocyte orientation. A sigmoidal distribution of the tissue conductivity combined with a mosaic model of SAN and atrial cells in the SEP was able to drive the right atrium (RA) at varying rates induced by gradual If block. Additionally, we investigated the influence of the SEPs by varying their number, length, and width. SEPs created a transition zone of transmembrane voltage and ionic currents to enable successful pace and drive. Unsuccessful simulations showed a hyperpolarized transmembrane voltage (-66 mV), which blocked the L-type channels and attenuated the sodium-calcium exchanger. The fiber direction influenced the SEPs that preferentially activated the crista terminalis (CT). The location of the leading pacemaker site (LPS) shifted toward the SEP-free areas. LPSs were located closer to the SEP-free areas (3.46 ± 1.42 mm), where the hyperpolarizing influence of the CT was reduced, compared with a larger distance from the LPS to the areas where SEPs were located (7.17± 0.98 mm). This study identified the geometrical and electrophysiological aspects of the 3D SAN-SEP-CT structure required for successful pace and drive in silico.

Abstract:

Interatrial conduction block refers to a disturbance in the propagation of electrical impulses in the conduction pathways between the right and the left atrium. It is a risk factor for atrial fibrillation, stroke, and premature death. Clin- ical diagnostic criteria comprise an increased P wave dura- tion and biphasic P waves in lead II, III and aVF due to ret- rograde activation of the left atrium. Machine learning algo- rithms could improve the diagnosis but require a large-scale, well-controlled and balanced dataset. In silico electrocardio- gram (ECG) signals, optimally obtained from a statistical shape model to cover anatomical variability, carry the poten- tial to produce an extensive database meeting the requirements for successful machine learning application. We generated the first in silico dataset including interatrial conduction block of 9,800simulated ECG signals based on a bi-atrial statistical shape model. Automated feature analysis was performed to evaluate P wave morphology, duration and P wave terminal force in lead V1. Increased P wave duration and P wave ter- minal force in lead V1 were found for models with interatrial conduction block compared to healthy models. A wide vari- ability of P wave morphology was detected for models with in- teratrial conduction block. Contrary to previous assumptions, our results suggest that a biphasic P wave morphology seems to be neither necessary nor sufficient for the diagnosis of in- teratrial conduction block. The presented dataset is ready for a classification with machine learning algorithms and can be easily extended.

Abstract:

Atrial fibrillation is responsible for a significant and steadily rising burden. Simultaneously, the treatment options for atrial fibrillation are far from optimal. Personalized simulations of cardiac electrophysiology could assist clinicians in the risk stratification and therapy planning for atrial fibrillation. However, the use of personalized simulations in clinics is currently not possible due to either too high computational costs or non-sufficient accuracy. Eikonal simulations come with low computational costs but cannot replicate the influence of cardiac tissue geometry on the conduction velocity of the wave propagation. Consequently, they currently lack the required accuracy to be applied in clinics. Biophysically detailed simulations on the other hand are accurate but associated with too high computational costs. To tackle this issue, a regression model is created based on biophysically detailed bidomain simulation data. This regression formula calculates the conduction velocity dependent on the thickness and curvature of the heart wall. Afterwards the formula was implemented into the eikonal model with the goal to increase the accuracy of the eikonal model without losing its advantage of computational efficiency. The results of the modified eikonal simulations demonstrate that (i) the local activation times become significantly closer to those of the biophysically detailed bidomain simulations, (ii) the advantage of the eikonal model of a low sensitivity to the resolution of the mesh was reduced further, and (iii) the unrealistic occurrence of endo-epicardial dissociation in simulations was remedied. The results suggest that the accuracy of the eikonal model was significantly increased. At the same time, the additional computational costs caused by the implementation of the regression formula are neglectable. In conclusion, a successful step towards a more accurate and fast computational model of cardiac electrophysiology was achieved.

Abstract:

Craniosynostosis is a congenital disease character-ized by the premature closure of one or multiple sutures of theinfant’s skull. For diagnosis, 3D photogrammetric scans are aradiation-free alternative to computed tomography. However,data is only sparsely available and the role of data augmentation for the classification of craniosynostosis has not yet beenanalyzed.In this work, we use a 2D distance map representation ofthe infants’ heads with a convolutional-neural-network-basedclassifier and employ a generative adversarial network (GAN)for data augmentation. We simulate two data scarcity scenar-ios with 15 % and 10 % training data and test the influence ofdifferent degrees of added synthetic data and balancing under-represented classes. We used total accuracy and F1-score as ametric to evaluate the final classifiers.For 15 % training data, the GAN-augmented dataset showedan increased F1-score up to 0.1 and classification accuracy upto 3 %. For 10 % training data, both metrics decreased. We present a deep convolutional GAN capable of creatingsynthetic data for the classification of craniosynostosis. Us-ing a moderate amount of synthetic data using a GAN showedslightly better performance, but had little effect overall. Thesimulated scarcity scenario of 10 % training data may havelimited the model’s ability to learn the underlying data distribution.

Abstract:

Conduction velocity (CV) slowing is associated with atrial fibrillation (AF) and reentrant ventricular tachycardia (VT). Clinical electroanatomical mapping systems used to localize AF or VT sources as ablation targets remain limited by the number of measuring electrodes and signal processing methods to generate high-density local activation time (LAT) and CV maps of heterogeneous atrial or trabeculated ventricular endocardium. The morphology and amplitude of bipolar electrograms depend on the direction of propagating electrical wavefront, making identification of low-amplitude signal sources commonly associated with fibrotic area difficulty. In comparison, unipolar electrograms are not sensitive to wavefront direction, but measurements are susceptible to distal activity. This study proposes a method for local CV calculation from optical mapping measurements, termed the circle method (CM). The local CV is obtained as a weighted sum of CV values calculated along different chords spanning a circle of predefined radius centered at a CV measurement location. As a distinct maximum in LAT differences is along the chord normal to the propagating wavefront, the method is adaptive to the propagating wavefront direction changes, suitable for electrical conductivity characterization of heterogeneous myocardium. In numerical simulations, CM was validated characterizing modeled ablated areas as zones of distinct CV slowing. Experimentally, CM was used to characterize lesions created by radiofrequency ablation (RFA) on isolated hearts of rats, guinea pig, and explanted human hearts. To infer the depth of RFA-created lesions, excitation light bands of different penetration depths were used, and a beat-to-beat CV difference analysis was performed to identify CV alternans. Despite being limited to laboratory research, studies based on CM with optical mapping may lead to new translational insights into better-guided ablation therapies.

Abstract:

Aims Atrial flutter (AFlut) is a common re-entrant atrial tachycardia driven by self-sustainable mechanisms that cause excitations to propagate along pathways different from sinus rhythm. Intra-cardiac electrophysiological mapping and catheter ablation are often performed without detailed prior knowledge of the mechanism perpetuating AFlut, likely prolonging the procedure time of these invasive interventions. We sought to discriminate the AFlut location [cavotricuspid isthmus-dependent (CTI), peri-mitral, and other left atrium (LA) AFlut classes] with a machine learning-based algorithm using only the non-invasive signals from the 12-lead electrocardiogram (ECG). Methods and results Hybrid 12-lead ECG dataset of 1769 signals was used (1424 in silico ECGs, and 345 clinical ECGs from 115 patients—three different ECG segments over time were extracted from each patient corresponding to single AFlut cycles). Seventy-seven features were extracted. A decision tree classifier with a hold-out classification approach was trained, validated, and tested on the dataset randomly split after selecting the most informative features. The clinical test set comprised 38 patients (114 clinical ECGs). The classifier yielded 76.3% accuracy on the clinical test set with a sensitivity of 89.7%, 75.0%, and 64.1% and a positive predictive value of 71.4%, 75.0%, and 86.2% for CTI, peri-mitral, and other LA class, respectively. Considering majority vote of the three segments taken from each patient, the CTI class was correctly classified at 92%. Conclusion Our results show that a machine learning classifier relying only on non-invasive signals can potentially identify the location of AFlut mechanisms. This method could aid in planning and tailoring patient-specific AFlut treatments.

Abstract:

In laparoscopic liver surgery (LLS) image-guidednavigation systems could support the surgeon by providingsubsurface information such as the positions of tumors andvessels. For this purpose, one option is to perform a registra-tion of preoperative 3D data and 3D surface patches recon-structed from laparoscopic images. Part of an automatic 3Dregistration pipeline is the feature description, which takes intoaccount various geometric and spatial information. Since thereis no leading feature descriptor in the field of LLS, two featuredescriptors are compared in this paper: The Fast Point FeatureHistogram (FPFH) and Triple Orthogonal Local Depth Images(TOLDI). To evaluate their performance, three perturbationswere induced: varying surface patch sizes, spatial displace-ment, and Gaussian deformation. Registration was performedusing the RANSAC algorithm. FPFH outperformed TOLDIfor small surface patches and in case of Gaussian deformationsin terms of registration accuracy. In contrast, TOLDI showedlower registration errors for patches with spatial displacement.While developing a 3D-3D registration pipeline, the choice ofthe feature descriptor is of importance, consequently a carefulchoice suitable for the application in LLS is necessary.

Abstract:

Background: Craniosynostosis is a condition caused by the premature fusion of skull sutures, leading to irregular growth patterns of the head. Three-dimensional photogrammetry is a radiation-free alternative to the diagnosis using computed tomography. While statistical shape models have been proposed to quantify head shape, no shape-model-based classification approach has been presented yet. Methods: We present a classification pipeline that enables an automated diagnosis of three types of craniosynostosis. The pipeline is based on a statistical shape model built from photogrammetric surface scans. We made the model and pathology-specific submodels publicly available, making it the first publicly available craniosynostosis-related head model, as well as the first focusing on infants younger than 1.5 years. To the best of our knowledge, we performed the largest classification study for craniosynostosis to date. Results: Our classification approach yields an accuracy of 97.8 %, comparable to other state-of-the-art methods using both computed tomography scans and stereophotogrammetry. Regarding the statistical shape model, we demonstrate that our model performs similar to other statistical shape models of the human head. Conclusion: We present a state-of-the-art shape-model-based classification approach for a radiation-free diagnosis of craniosynostosis. Our publicly available shape model enables the assessment of craniosynostosis on realistic and synthetic data.

Abstract:

Objective: To investigate cardiac activation maps estimated using electrocardiographic imaging and to find methods reducing line-of-block (LoB) artifacts, while preserving real LoBs. Methods: Body surface potentials were computed for 137 simulated ventricular excitations. Subsequently, the inverse problem was solved to obtain extracellular potentials (EP) and transmembrane voltages (TMV). From these, activation times (AT) were estimated using four methods and compared to the ground truth. This process was evaluated with two cardiac mesh resolutions. Factors contributing to LoB artifacts were identified by analyzing the impact of spatial and temporal smoothing on the morphology of source signals. Results: AT estimation using a spatiotemporal derivative performed better than using a temporal derivative. Compared to deflection-based AT estimation, correlation-based methods were less prone to LoB artifacts but performed worse in identifying real LoBs. Temporal smoothing could eliminate artifacts for TMVs but not for EPs, which could be linked to their temporal morphology. TMVs led to more accurate ATs on the septum than EPs. Mesh resolution had a negligible effect on inverse reconstructions, but small distances were important for cross-correlation-based estimation of AT delays. Conclusion: LoB artifacts are mainly caused by the inherent spatial smoothing effect of the inverse reconstruction. Among the configurations evaluated, only deflection-based AT estimation in combination with TMVs and strong temporal smoothing can prevent LoB artifacts, while preserving real LoBs. Significance: Regions of slow conduction are of considerable clinical interest and LoB artifacts observed in non-invasive ATs can lead to misinterpretations. We addressed this problem by identifying factors causing such artifacts and methods to reduce them.

Abstract:

Computational simulations of cardiac electrophysiology provide detailed information on the depolarization phenomena at different spatial and temporal scales. With the development of new hardware and software, in silico experiments have gained more importance in cardiac electrophysiology research. For plane waves in healthy tissue, in vivo and in silico electrograms at the surface of the tissue demonstrate symmetric morphology and high peak-to-peak amplitude. Simulations provided insight into the factors that alter the morphology and amplitude of the electrograms. The situation is more complex in remodeled tissue with fibrotic infiltrations. Clinically, different changes including fractionation of the signal, extended duration and reduced amplitude have been described. In silico, numerous approaches have been proposed to represent the pathological changes on different spatial and functional scales. Different modeling approaches can reproduce distinct subsets of the clinically observed electrogram phenomena. This review provides an overview of how different modeling approaches to incorporate fibrotic and structural remodeling affect the electrogram and highlights open challenges to be addressed in future research.

Abstract:

Cardiac resynchronization therapy is a valuable tool to restore left ventricular function in patients experiencing dyssynchronous ventricular activation. However, the non-responder rate is still as high as 40%. Recent studies suggest that left ventricular torsion or specifically the lack thereof might be a good predictor for the response of cardiac resynchronization therapy. Since left ventricular torsion is governed by the muscle fiber orientation and the heterogeneous electromechanical activation of the myocardium, understanding the relation between these components and the ability to measure them is vital. To analyze if locally altered electromechanical activation in heart failure patients affects left ventricular torsion, we conducted a simulation study on 27 personalized left ventricular models. Electroanatomical maps and late gadolinium enhanced magnetic resonance imaging data informed our in-silico model cohort. The angle of rotation was evaluated in every material point of the model and averaged values were used to classify the rotation as clockwise or counterclockwise in each segment and sector of the left ventricle. 88% of the patient models (n = 24) were classified as a wringing rotation and 12% (n = 3) as a rigid-body-type rotation. Comparison to classification based on in vivo rotational NOGA XP maps showed no correlation. Thus, isolated changes of the electromechanical activation sequence in the left ventricle are not sufficient to reproduce the rotation pattern changes observed in vivo and suggest that further patho-mechanisms are involved.

Abstract:

Left atrial enlargement (LAE) is one of the risk factors for atrial fibrillation (AF). A non-invasive and automated detection of LAE with the 12-lead electrocardiogram (ECG) could therefore contribute to an improved AF risk stratification and an early detection of new-onset AF incidents. However, one major challenge when applying machine learning techniques to identify and classify cardiac diseases usually lies in the lack of large, reliably labeled and balanced clinical datasets. We therefore examined if the extension of clinical training data by simulated ECGs derived from a novel bi-atrial shape model could improve the automated detection of LAE based on P waves of the 12-lead ECG. We derived 95 volumetric geometries from the bi-atrial statistical shape model with continuously increasing left atrial volumes in the range of 30 ml to 65 ml. Electrophysiological simulations with 10 different conduction velocity settings and 2 different torso models were conducted. Extracting the P waves of the 12-lead ECG thus yielded a synthetic dataset of 1,900 signals. Besides the simulated data, 7,168 healthy and 309 LAE ECGs from a public clinical ECG database were available for training and testing of an LSTM network to identify LAE. The class imbalance of the training data could be reduced from 1:23 to 1:6 when adding simulated data to the training set. The accuracy evaluated on the test dataset comprising a subset of the clinical ECG recordings improved from 0.91 to 0.95 if simulated ECGs were included as an additional input for the training of the classifier. Our results suggest that using a bi-atrial statistical shape model as a basis for ECG simulations can help to overcome the drawbacks of clinical ECG recordings and can thus lead to an improved performance of machine learning classifiers to detect LAE based on the 12-lead ECG.

Abstract:

Supervised training of neural networks requires large, diverse and well annotated data sets. In the medical field, this is often difficult to achieve due to constraints in time, expert knowledge and prevalence of an event. Artificial data augmentation can help to prevent overfitting and improve the detection of rare events as well as overall performance. However, most augmentation techniques use purely spatial transformations, which are not sufficient for video data with temporal correlations. In this paper, we present a novel methodology for workflow augmentation and demonstrate its benefit for event recognition in cataract surgery. The proposed approach increases the frequency of event alternation by creating artificial videos. The original video is split into event segments and a workflow graph is extracted from the original annotations. Finally, the segments are assembled into new videos based on the workflow graph. Compared to the original videos, the frequency of event alternation in the augmented cataract surgery videos increased by 26%. Further, a 3% higher classification accuracy and a 7.8% higher precision was achieved compared to a state-of-the-art approach. Our approach is particularly helpful to increase the occurrence of rare but important events and can be applied to a large variety of use cases.

Abstract:

BACKGROUND AND OBJECTIVE: Cardiac electrophysiology is a medical specialty with a long and rich tradition of computational modeling. Nevertheless, no community standard for cardiac electrophysiology simulation software has evolved yet. Here, we present the openCARP simulation environment as one solution that could foster the needs of large parts of this community. METHODS AND RESULTS: openCARP and the Python-based carputils framework allow developing and sharing simulation pipelines which automate in silico experiments including all modeling and simulation steps to increase reproducibility and productivity. The continuously expanding openCARP user community is supported by tailored infrastructure. Documentation and training material facilitate access to this complementary research tool for new users. After a brief historic review, this paper summarizes requirements for a high-usability electrophysiology simulator and describes how openCARP fulfills them. We introduce the openCARP modeling workflow in a multi-scale example of atrial fibrillation simulations on single cell, tissue, organ and body level and finally outline future development potential. CONCLUSION: As an open simulator, openCARP can advance the computational cardiac electrophysiology field by making state-of-the-art simulations accessible. In combination with the carputils framework, it offers a tailored software solution for the scientific community and contributes towards increasing use, transparency, standardization and reproducibility of in silico experiments.

Abstract:

The arrhythmogenesis of atrial fibrillation is associated with the presence of fibrotic atrial tissue. Not only fibrosis but also physiological anatomical variability of the atria and the thorax reflect in altered morphology of the P wave in the 12-lead electrocardiogram (ECG). Distinguishing between the effects on the P wave induced by local atrial substrate changes and those caused by healthy anatomical variations is important to gauge the potential of the 12-lead ECG as a non-invasive and cost-effective tool for the early detection of fibrotic atrial cardiomyopathy to stratify atrial fibrillation propensity. In this work, we realized 54,000 combinations of different atria and thorax geometries from statistical shape models capturing anatomical variability in the general population. For each atrial model, 10 different volume fractions (0-45%) were defined as fibrotic. Electrophysiological simulations in sinus rhythm were conducted for each model combination and the respective 12-lead ECGs were computed. P wave features (duration, amplitude, dispersion, terminal force in V1) were extracted and compared between the healthy and the diseased model cohorts. All investigated feature values systematically in- or decreased with the left atrial volume fraction covered by fibrotic tissue, however value ranges overlapped between the healthy and the diseased cohort. Using all extracted P wave features as input values, the amount of the fibrotic left atrial volume fraction was estimated by a neural network with an absolute root mean square error of 8.78%. Our simulation results suggest that although all investigated P wave features highly vary for different anatomical properties, the combination of these features can contribute to non-invasively estimate the volume fraction of atrial fibrosis using ECG-based machine learning approaches.

Abstract:

AIMS: The treatment of atrial fibrillation beyond pulmonary vein isolation has remained an unsolved challenge. Targeting regions identified by different substrate mapping approaches for ablation resulted in ambiguous outcomes. With the effective refractory period being a fundamental prerequisite for the maintenance of fibrillatory conduction, this study aims at estimating the effective refractory period with clinically available measurements. METHODS AND RESULTS: A set of 240 simulations in a spherical model of the left atrium with varying model initialization, combination of cellular refractory properties, and size of a region of lowered effective refractory period was implemented to analyse the capabilities and limitations of cycle length mapping. The minimum observed cycle length and the 25% quantile were compared to the underlying effective refractory period. The density of phase singularities was used as a measure for the complexity of the excitation pattern. Finally, we employed the method in a clinical test of concept including five patients. Areas of lowered effective refractory period could be distinguished from their surroundings in simulated scenarios with successfully induced multi-wavelet re-entry. Larger areas and higher gradients in effective refractory period as well as complex activation patterns favour the method. The 25% quantile of cycle lengths in patients with persistent atrial fibrillation was found to range from 85 to 190 ms. CONCLUSION: Cycle length mapping is capable of highlighting regions of pathologic refractory properties. In combination with complementary substrate mapping approaches, the method fosters confidence to enhance the treatment of atrial fibrillation beyond pulmonary vein isolation particularly in patients with complex activation patterns.

Abstract:

Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software must be available, discoverable, usable, and adaptable to new needs, both now and in the future. Research software therefore requires an environment that supports sustainability. Hence, a change is needed in the way research software development and maintenance are currently motivated, incentivized, funded, structurally and infrastructurally supported, and legally treated. Failing to do so will threaten the quality and validity of research. In this paper, we identify challenges for research software sustainability in Germany and beyond, in terms of motivation, selection, research software engineering personnel, funding, infrastructure, and legal aspects. Besides researchers, we specifically address political and academic decision-makers to increase awareness of the importance and needs of sustainable research software practices. In particular, we recommend strategies and measures to create an environment for sustainable research software, with the ultimate goal to ensure that software-driven research is valid, reproducible and sustainable, and that software is recognized as a first class citizen in research. This paper is the outcome of two workshops run in Germany in 2019, at deRSE19 - the first International Conference of Research Software Engineers in Germany - and a dedicated DFG-supported follow-up workshop in Berlin.

Abstract:

OBJECTIVE: Atrial flutter (AFl) is a common arrhythmia that can be categorized according to different self-sustained electrophysiological mechanisms. The non-invasive discrimination of such mechanisms would greatly benefit ablative methods for AFl therapy as the driving mechanisms would be described prior to the invasive procedure, helping to guide ablation. In the present work, we sought to implement recurrence quantification analysis (RQA) on 12-lead ECG signals from a computational framework to discriminate different electrophysiological mechanisms sustaining AFl. METHODS: 20 different AFl mechanisms were generated in 8 atrial models and were propagated into 8 torso models via forward solution, resulting in 1,256 sets of 12-lead ECG signals. Principal component analysis was applied on the 12-lead ECGs, and six RQA-based features were extracted from the most significant principal component scores in two different approaches: individual component RQA and spatial reduced RQA. RESULTS: In both approaches, RQA-based features were significantly sensitive to the dynamic structures underlying different AFl mechanisms. Hit rate as high as 67.7% was achieved when discriminating the 20 AFl mechanisms. RQA-based features estimated for a clinical sample suggested high agreement with the results found in the computational framework. CONCLUSION: RQA has been shown an effective method to distinguish different AFl electrophysiological mechanisms in a non-invasive computational framework. A clinical 12-lead ECG used as proof of concept showed the value of both the simulations and the methods. SIGNIFICANCE: The non-invasive discrimination of AFl mechanisms helps to delineate the ablation strategy, reducing time and resources required to conduct invasive cardiac mapping and ablation procedures.

Abstract:

Acute ischemic stroke is a major health problem with a high mortality rate and a high risk for permanent disabilities. Selective brain hypothermia has the neuroprotective potential to possibly lower cerebral harm. A recently developed catheter system enables to combine endovascular blood cooling and thrombectomy using the same endovascular access. By using the penumbral perfusion via leptomeningeal collaterals, the catheter aims at enabling a cold reperfusion, which mitigates the risk of a reperfusion injury. However, cerebral circulation is highly patient-specific and can vary greatly. Since direct measurement of remaining perfusion and temperature decrease induced by the catheter is not possible without additional harm to the patient, computational modeling provides an alternative to gain knowledge about resulting cerebral temperature decrease. In this work, we present a brain temperature model with a realistic division into gray and white matter and consideration of spatially resolved perfusion. Furthermore, it includes detailed anatomy of cerebral circulation with possibility of personalizing on base of real patient anatomy. For evaluation of catheter performance in terms of cold reperfusion and to analyze its general performance, we calculated the decrease in brain temperature in case of a large vessel occlusion in the middle cerebral artery (MCA) for different scenarios of cerebral arterial anatomy. Congenital arterial variations in the circle of Willis had a distinct influence on the cooling effect and the resulting spatial temperature distribution before vessel recanalization. Independent of the branching configurations, the model predicted a cold reperfusion due to a strong temperature decrease after recanalization (1.4-2.2  C after 25 min of cooling, recanalization after 20 min of cooling). Our model illustrates the effectiveness of endovascular cooling in combination with mechanical thrombectomy and its results serve as an adequate substitute for temperature measurement in a clinical setting in the absence of direct intraparenchymal temperature probes.

Abstract:

The contraction of the human heart is a complex process as a consequence of the interaction of internal and external forces. In current clinical routine, the resulting deformation can be imaged during an entire heart beat. However, the active tension development cannot be measured in vivo but may provide valuable diagnostic information. In this work, we present a novel numerical method for solving an inverse problem of cardiac biomechanics-estimating the dynamic active tension field, provided the motion of the myocardial wall is known. This ill-posed non-linear problem is solved using second order Tikhonov regularization in space and time. We conducted a sensitivity analysis by varying the fiber orientation in the range of measurement accuracy. To achieve RMSE <20% of the maximal tension, the fiber orientation needs to be provided with an accuracy of 10°. Also, variation was added to the deformation data in the range of segmentation accuracy. Here, imposing temporal regularization led to an eightfold decrease in the error down to 12%. Furthermore, non-contracting regions representing myocardial infarct scars were introduced in the left ventricle and could be identified accurately in the inverse solution (sensitivity >0.95). The results obtained with non-matching input data are promising and indicate directions for further improvement of the method. In future, this method will be extended to estimate the active tension field based on motion data from clinical images, which could provide important insights in terms of a new diagnostic tool for the identification and treatment of diseased heart tissue.

Abstract:

BACKGROUND Atrial !brillation (AF) is the most common supra- ventricular arrhythmia, characterized by disorganized atrial electri- cal activity, maintained by localized arrhythmogenic atrial drivers. Pulmonary vein isolation (PVI) allows to exclude PV-related drivers. However, PVI is less effective in patients with additional extra-PV arrhythmogenic drivers. OBJECTIVES To discriminate whether AF drivers are located near the PVs vs extra-PV regions using the noninvasive 12-lead electro- cardiogram (ECG) in a computational and clinical framework, and to computationally predict the acute success of PVI in these cohorts of data. METHODS AFdriverswereinducedin2computerizedatrialmodels and combined with 8 torso models, resulting in 1128 12-lead ECGs (80 ECGs with AF drivers located in the PVs and 1048 in extra-PV areas). A total of 103 features were extracted from the signals. Bi- nary decision tree classi!er was trained on the simulated data and evaluated using hold-out cross-validation. The PVs were subse- quently isolated in the models to assess PVI success Finally, the classi!er was tested on a clinical dataset (46 patients: 23 PV- dependent AF and 23 with additional extra-PV sources). RESULTS The classi!er yielded 82.6% speci!city and 73.9% sensi- tivity for detecting PV drivers on the clinical data. Consistency analysis on the 46 patients resulted in 93.5% results match. Applying PVI on the simulated AF cases terminated AF in 100% of the cases in the PV class. CONCLUSION Machine learning–based classi!cation of 12-lead- ECG allows discrimination between patients with PV drivers vs those with extra-PV drivers of AF. The novel algorithm may aid to identify patients with high acute success rates to PVI. KEYWORDS Atrial !brillation; Atrial ablation; Machine learning; Noninvasive; 12-lead electrocardiogram; Pulmonary vein isolation; Cardiac simulations (Cardiovascular Digital Health Journal 2021;2:126–136) © 2021 Heart Rhythm Society. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc- nd/4.0/).

Abstract:

Background: Hypertrophic cardiomyopathy (HCM) is typically caused by mutations in sarcomeric genes leading to cardiomyocyte disarray, replacement fibrosis, impaired contractility, and elevated filling pressures. These varying tissue properties are associ- ated with certain strain patterns that may allow to establish a diagnosis by means of non-invasive imaging without the necessity of harmful myocardial biopsies or con- trast agent application. With a numerical study, we aim to answer: how the variability in each of these mechanisms contributes to altered mechanics of the left ventricle (LV) and if the deformation obtained in in-silico experiments is comparable to values reported from clinical measurements. Methods: We conducted an in-silico sensitivity study on physiological and pathologi- cal mechanisms potentially underlying the clinical HCM phenotype. The deformation of the four-chamber heart models was simulated using a finite-element mechanical solver with a sliding boundary condition to mimic the tissue surrounding the heart. Furthermore, a closed-loop circulatory model delivered the pressure values acting on the endocardium. Deformation measures and mechanical behavior of the heart mod- els were evaluated globally and regionally. Results: Hypertrophy of the LV affected the course of strain, strain rate, and wall thickening—the root-mean-squared difference of the wall thickening between control (mean thickness 10 mm) and hypertrophic geometries (17 mm) was >10%. A reduc- tion of active force development by 40% led to less overall deformation: maximal radial strain reduced from 26 to 21%. A fivefold increase in tissue stiffness caused a more homogeneous distribution of the strain values among 17 heart segments. Fiber disarray led to minor changes in the circumferential and radial strain. A combination of pathological mechanisms led to reduced and slower deformation of the LV and halved the longitudinal shortening of the LA. Conclusions: This study uses a computer model to determine the changes in LV deformation caused by pathological mechanisms that are presumed to underlay HCM. This knowledge can complement imaging-derived information to obtain a more accu- rate diagnosis of HCM.

Abstract:

The term "In Silico Trial" indicates the use of computer modelling and simulation to evaluate the safety and efficacy of a medical product, whether a drug, a medical device, a diagnostic product or an advanced therapy medicinal product. Predictive models are positioned as new methodologies for the development and the regulatory evaluation of medical products. New methodologies are qualified by regulators such as FDA and EMA through formal processes, where a first step is the definition of the Context of Use (CoU), which is a concise description of how the new methodology is intended to be used in the development and regulatory assessment process. As In Silico Trials are a disruptively innovative class of new methodologies, it is important to have a list of possible CoUs highlighting potential applications for the development of the relative regulatory science. This review paper presents the result of a consensus process that took place in the InSilicoWorld Community of Practice, an online forum for experts in in silico medicine. The experts involved identified 46 descriptions of possible CoUs which were organised into a candidate taxonomy of nine CoU categories. Examples of 31 CoUs were identified in the available literature; the remaining 15 should, for now, be considered speculative.

Abstract:

In both clinical and computational studies, different pacing protocols are used to induce arrhythmia and non-inducibility is often considered as the endpoint of treatment. The need for a standardized methodology is urgent since the choice of the protocol used to induce arrhythmia could lead to contrasting results, e.g., in assessing atrial fibrillation (AF) vulnerabilty. Therefore, we propose a novel method-pacing at the end of the effective refractory period (PEERP)-and compare it to state-of-the-art protocols, such as phase singularity distribution (PSD) and rapid pacing (RP) in a computational study. All methods were tested by pacing from evenly distributed endocardial points at 1 cm inter-point distance in two bi-atrial geometries. Seven different atrial models were implemented: five cases without specific AF-induced remodeling but with decreasing global conduction velocity and two persistent AF cases with an increasing amount of fibrosis resembling different substrate remodeling stages. Compared with PSD and RP, PEERP induced a larger variety of arrhythmia complexity requiring, on average, only 2.7 extra-stimuli and 3 s of simulation time to initiate reentry. Moreover, PEERP and PSD were the protocols which unveiled a larger number of areas vulnerable to sustain stable long living reentries compared to RP. Finally, PEERP can foster standardization and reproducibility, since, in contrast to the other protocols, it is a parameter-free method. Furthermore, we discuss its clinical applicability. We conclude that the choice of the inducing protocol has an influence on both initiation and maintenance of AF and we propose and provide PEERP as a reproducible method to assess arrhythmia vulnerability.

Abstract:

Graphical visualization systems are a common clinical tool for displaying digital images and three-dimensional volumetric data. These systems provide a broad spectrum of information to support physicians in their clinical routine. For example, the field of radiology enjoys unrestricted options for interaction with the data, since information is pre-recorded and available entirely in digital form. However, some fields, such as microsurgery, do not benefit from this yet. Microscopes, endoscopes, and laparoscopes show the surgical site as it is. To allow free data manipulation and information fusion, 3D digitization of surgical sites is required. We aimed to find the number of cameras needed to add this functionality to surgical microscopes. For this, we performed in silico simulations of the 3D reconstruction of representative models of microsurgical sites with different numbers of cameras in narrow-baseline setups. Our results show that eight independent camera views are preferable, while at least four are necessary for a digital surgical site. In most cases, eight cameras allow the reconstruction of over 99% of the visible part. With four cameras, still over 95% can be achieved. This answers one of the key questions for the development of a prototype microscope. In future, such a system can provide functionality which is unattainable today

Abstract:

Background: Rate-varying S1S2 stimulation protocols can be used for restitution studies to characterize atrial substrate, ionic remodeling, and atrial fibrillation risk. Clinical restitution studies with numerous patients create large amounts of these data. Thus, an automated pipeline to evaluate clinically acquired S1S2 stimulation protocol data necessitates consistent, robust, reproducible, and precise evaluation of local activation times, electrogram amplitude, and conduction velocity. Here, we present the CVAR-Seg pipeline, developed focusing on three challenges: (i) No previous knowledge of the stimulation parameters is available, thus, arbitrary protocols are supported. (ii) The pipeline remains robust under different noise conditions. (iii) The pipeline supports segmentation of atrial activities in close temporal proximity to the stimulation artifact, which is challenging due to larger amplitude and slope of the stimulus compared to the atrial activity. Methods and Results: The S1 basic cycle length was estimated by time interval detection. Stimulation time windows were segmented by detecting synchronous peaks in different channels surpassing an amplitude threshold and identifying time intervals between detected stimuli. Elimination of the stimulation artifact by a matched filter allowed detection of local activation times in temporal proximity. A non-linear signal energy operator was used to segment periods of atrial activity. Geodesic and Euclidean inter electrode distances allowed approximation of conduction velocity. The automatic segmentation performance of the CVAR-Seg pipeline was evaluated on 37 synthetic datasets with decreasing signal-to-noise ratios. Noise was modeled by reconstructing the frequency spectrum of clinical noise. The pipeline retained a median local activation time error below a single sample (1 ms) for signal-to-noise ratios as low as 0 dB representing a high clinical noise level. As a proof of concept, the pipeline was tested on a CARTO case of a paroxysmal atrial fibrillation patient and yielded plausible restitution curves for conduction speed and amplitude. Conclusion: The proposed openly available CVAR-Seg pipeline promises fast, fully automated, robust, and accurate evaluations of atrial signals even with low signal-to-noise ratios. This is achieved by solving the proximity problem of stimulation and atrial activity to enable standardized evaluation without introducing human bias for large data sets.

Abstract:

The vascular function of a vessel can be qualitatively and intraoperatively checked by recording the blood dynamics inside the vessel via fluorescence angiography (FA). Although FA is the state of the art in proving the existence of blood flow during interventions such as bypass surgery, it still lacks a quantitative blood flow measurement that could decrease the recurrence rate and postsurgical mortality. Previous approaches show that the measured flow has a significant deviation compared to the gold standard reference (ultrasonic flow meter). In order to systematically address the possible sources of error, we investigated the error in transit time measurement of an indicator. Obtaining in vivo indicator dilution curves with a known ground truth is complex and often not possible. Further, the error in transit time measurement should be quantified and reduced. To tackle both issues, we first computed many diverse indicator dilution curves using an in silico simulation of the indicator’s flow. Second, we post-processed these curves to mimic measured signals. Finally, we fitted mathematical models (parabola, gamma variate, local density random walk, and mono-exponential model) to re-continualize the obtained discrete indicator dilution curves and calculate the time delay of two analytical functions. This re-continualization showed an increase in the temporal accuracy up to a sub-sample accuracy. Thereby, the Local Density Random Walk (LDRW) model performed best using the cross-correlation of the first derivative of both indicator curves with a cutting of the data at 40% of the peak intensity. The error in frames depends on the noise level and is for a signal-to-noise ratio (SNR) of 20dB and a sampling rate of fs = 60 Hz at f−1 · 0.25(±0.18), so this error is smaller than the distance between two consecutive s samples. The accurate determination of the transit time and the quantification of the error allow the calculation of the error propagation onto the flow measurement. Both can assist surgeons as an intraoperative quality check and thereby reduce the recurrence rate and post-surgical mortality.

Abstract:

Mathematical models of the human heart are evolving to become a cornerstone of precision medicine and support clinical decision making by providing a powerful tool to understand the mechanisms underlying pathophysiological conditions. In this study, we present a detailed mathematical description of a fully coupled multi-scale model of the human heart, including electrophysiology, mechanics, and a closed-loop model of circulation. State-of-the-art models based on human physiology are used to describe membrane kinetics, excitation-contraction coupling and active tension generation in the atria and the ventricles. Furthermore, we highlight ways to adapt this framework to patient specific measurements to build digital twins. The validity of the model is demonstrated through simulations on a personalized whole heart geometry based on magnetic resonance imaging data of a healthy volunteer. Additionally, the fully coupled model was employed to evaluate the effects of a typical atrial ablation scar on the cardiovascular system. With this work, we provide an adaptable multi-scale model that allows a comprehensive personalization from ion channels to the organ level enabling digital twin modeling

Abstract:

In patients with atrial fibrillation, intracardiac electrogram signal amplitude is known to decrease with increased structural tissue remodeling, referred to as fibrosis. In addition to the isolation of the pulmonary veins, fibrotic sites are considered a suitable target for catheter ablation. However, it remains an open challenge to find fibrotic areas and to differentiate their density and transmurality. This study aims to identify the volume fraction and transmurality of fibrosis in the atrial substrate. Simulated cardiac electrograms, combined with a generalized model of clinical noise, reproduce clinically measured signals. Our hybrid dataset approach combines and clinical electrograms to train a decision tree classifier to characterize the fibrotic atrial substrate. This approach captures different dynamics of the electrical propagation reflected on healthy electrogram morphology and synergistically combines it with synthetic fibrotic electrograms from experiments. The machine learning algorithm was tested on five patients and compared against clinical voltage maps as a proof of concept, distinguishing non-fibrotic from fibrotic tissue and characterizing the patient's fibrotic tissue in terms of density and transmurality. The proposed approach can be used to overcome a single voltage cut-off value to identify fibrotic tissue and guide ablation targeting fibrotic areas.

Abstract:

Aims Atrial cardiomyopathy (ACM) is associated with new-onset atrial fibrillation, arrhythmia recurrence after pulmonary vein isolation (PVI) and increased risk for stroke. At present, diagnosis of ACM is feasible by endocardial contact mapping of left atrial (LA) low-voltage substrate (LVS) or late gadolinium-enhanced magnetic resonance imaging, but their complexity limits a widespread use. The aim of this study was to assess non-invasive body surface electrocardiographic imaging (ECGI) as a novel clinical tool for diagnosis of ACM compared with endocardial mapping. Methods and results Thirty-nine consecutive patients (66 ± 9 years, 85% male) presenting for their first PVI for persistent atrial fibrillation underwent ECGI in sinus rhythm using a 252-electrode-array mapping system. Subsequently, high-density LA voltage and biatrial activation maps (mean 2090 ± 488 sites) were acquired in sinus rhythm prior to PVI. Freedom from arrhythmia recurrence was assessed within 12 months follow-up. Increased duration of total atrial conduction time (TACT) in ECGI was associated with both increased atrial activation time and extent of LA-LVS in endocardial contact mapping (r = 0.77 and r = 0.66, P < 0.0001 respectively). Atrial cardiomyopathy was found in 23 (59%) patients. A TACT value of 148 ms identified ACM with 91.3% sensitivity and 93.7% specificity. Arrhythmia recurrence occurred in 15 (38%) patients during a follow-up of 389 ± 55 days. Freedom from arrhythmia was significantly higher in patients with a TACT <148 ms compared with patients with a TACT ≥148 ms (82.4% vs. 45.5%, P = 0.019). Conclusion Analysis of TACT in non-invasive ECGI allows diagnosis of patients with ACM, which is associated with a significantly increased risk for arrhythmia recurrence following PVI.

Abstract:

Ventricular coordinates are widely used as a versatile tool for various applications that benefit from a description of local position within the heart. However, the practical usefulness of ventricular coordinates is determined by their ability to meet application-specific requirements. For regression-based estimation of biventricular position, for example, a symmetric definition of coordinate directions in both ventricles is important. For the transfer of data between different hearts as another use case, the consistency of coordinate values across different geometries is particularly relevant. To meet these requirements, we compare different approaches to compute coordinates and present Cobiveco, a symmetric, consistent and intuitive biventricular coordinate system that builds upon existing coordinate systems, but overcomes some of their limitations. A novel one-way transfer error is introduced to assess the consistency of the coordinates. Normalized distances along bijective trajectories between two boundaries were found to be superior to solutions of Laplace’s equation for defining coordinate values, as they show better linearity in space. Evaluation of transfer and linearity errors on 36 patient geometries revealed a more than 4-fold improvement compared to a state-of-the-art method. Finally, we show two application examples underlining the relevance for cardiac data processing. Cobiveco MATLAB code is available under a permissive open-source license.

Abstract:

The ECG is one of the most commonly used non-invasive tools to gain insights into the electrical functioning of the heart. It has been crucial as a foundation in the creation and validation of in silico models describing the underlying electrophysiological processes. However, so far, the contraction of the heart and its influences on the ECG have mainly been overlooked in in silico models. As the heart contracts and moves, so do the electrical sources within the heart responsible for the signal on the body surface, thus potentially altering the ECG. To illuminate these aspects, we developed a human 4-chamber electro-mechanically coupled whole heart in silico model and embedded it within a torso model. Our model faithfully reproduces measured 12-lead ECG traces, circulatory characteristics, as well as physiological ventricular rotation and atrioventricular valve plane displacement. We compare our dynamic model to three non-deforming ones in terms of standard clinically used ECG leads (Einthoven and Wilson) and body surface potential maps (BSPM). The non-deforming models consider the heart at its ventricular end-diastatic, end-diastolic and end-systolic states. The standard leads show negligible differences during P-Wave and QRS-Complex, yet during T-Wave the leads closest to the heart show prominent differences in amplitude. When looking at the BSPM, there are no notable differences during the P-Wave, but effects of cardiac motion can be observed already during the QRS-Complex, increasing further during the T-Wave. We conclude that for the modeling of activation (P-Wave/QRS-Complex), the associated effort of simulating a complete electro-mechanical approach is not worth the computational cost. But when looking at ventricular repolarization (T-Wave) in standard leads as well as BSPM, there are areas where the signal can be influenced by cardiac motion of the heart to an extent that should not be ignored.

Abstract:

We aim to provide a critical appraisal of basic concepts underlying signal recording and processing technologies applied for (i) atrial fibrillation (AF) mapping to unravel AF mechanisms and/or identifying target sites for AF therapy and (ii) AF detection, to optimize usage of technologies, stimulate research aimed at closing knowledge gaps, and developing ideal AF recording and processing technologies. Recording and processing techniques for assessment of electrical activity during AF essential for diagnosis and guiding ablative therapy including body surface electrocardiograms (ECG) and endo- or epicardial electrograms (EGM) are evaluated. Discussion of (i) differences in uni-, bi-, and multi-polar (omnipolar/Laplacian) recording modes, (ii) impact of recording technologies on EGM morphology, (iii) global or local mapping using various types of EGM involving signal processing techniques including isochronal-, voltage- fractionation-, dipole density-, and rotor mapping, enabling derivation of parameters like atrial rate, entropy, conduction velocity/direction, (iv) value of epicardial and optical mapping, (v) AF detection by cardiac implantable electronic devices containing various detection algorithms applicable to stored EGMs, (vi) contribution of machine learning (ML) to further improvement of signals processing technologies. Recording and processing of EGM (or ECG) are the cornerstones of (body surface) mapping of AF. Currently available AF recording and processing technologies are mainly restricted to specific applications or have technological limitations. Improvements in AF mapping by obtaining highest fidelity source signals (e.g. catheter–electrode combinations) for signal processing (e.g. filtering, digitization, and noise elimination) is of utmost importance. Novel acquisition instruments (multi-polar catheters combined with improved physical modelling and ML techniques) will enable enhanced and automated interpretation of EGM recordings in the near future.

Abstract:

Atrial flutter (AFL) is a common atrial arrhythmia typically characterized by electrical activity propagating around specific anatomical regions. It is usually treated with catheter ablation. However, the identification of rotational activities is not straightforward, and requires an intense effort during the first phase of the electrophysiological (EP) study, i.e., the mapping phase, in which an anatomical 3D model is built and electrograms (EGMs) are recorded. In this study, we modeled the electrical propagation pattern of AFL (measured during mapping) using network theory (NT), a well-known field of research from the computer science domain. The main advantage of NT is the large number of available algorithms that can efficiently analyze the network. Using directed network mapping, we employed a cycle-finding algorithm to detect all cycles in the network, resembling the main propagation pattern of AFL. The method was tested on two subjects in sinus rhythm, six in an experimental model of in-silico simulations, and 10 subjects diagnosed with AFL who underwent a catheter ablation. The algorithm correctly detected the electrical propagation of both sinus rhythm cases and in-silico simulations. Regarding the AFL cases, arrhythmia mechanisms were either totally or partially identified in most of the cases (8 out of 10), i.e., cycles around the mitral valve, tricuspid valve and figure-of-eight reentries. The other two cases presented a poor mapping quality or a major complexity related to previous ablations, large areas of fibrotic tissue, etc. Directed network mapping represents an innovative tool that showed promising results in identifying AFL mechanisms in an automatic fashion. Further investigations are needed to assess the reliability of the method in different clinical scenarios.

Abstract:

The human heart is a masterpiece of the highest complexity coordinating multi-physics aspects on a multi-scale range. Thus, modeling the cardiac function to reproduce physiological characteristics and diseases remains challenging. Especially the complex simulation of the blood's hemodynamics and its interaction with the myocardial tissue requires a high accuracy of the underlying computational models and solvers. These demanding aspects make whole-heart fully-coupled simulations computationally highly expensive and call for simpler but still accurate models. While the mechanical deformation during the heart cycle drives the blood flow, less is known about the feedback of the blood flow onto the myocardial tissue. To solve the fluid-structure interaction problem, we suggest a cycle-to-cycle coupling of the structural deformation and the fluid dynamics. In a first step, the displacement of the endocardial wall in the mechanical simulation serves as a unidirectional boundary condition for the fluid simulation. After a complete heart cycle of fluid simulation, a spatially resolved pressure factor (PF) is extracted and returned to the next iteration of the solid mechanical simulation, closing the loop of the iterative coupling procedure. All simulations were performed on an individualized whole heart geometry. The effect of the sequential coupling was assessed by global measures such as the change in deformation and-as an example of diagnostically relevant information-the particle residence time. The mechanical displacement was up to 2 mm after the first iteration. In the second iteration, the deviation was in the sub-millimeter range, implying that already one iteration of the proposed cycle-to-cycle coupling is sufficient to converge to a coupled limit cycle. Cycle-to-cycle coupling between cardiac mechanics and fluid dynamics can be a promising approach to account for fluid-structure interaction with low computational effort. In an individualized healthy whole-heart model, one iteration sufficed to obtain converged and physiologically plausible results.

Abstract:

Electrical impedance tomography is clinically used to trace ventilation related changes in electrical conductivity of lung tissue. Estimating regional pulmonary perfusion using electrical impedance tomography is still a matter of research. To support clinical decision making, reliable bedside information of pulmonary perfusion is needed. We introduce a method to robustly detect pulmonary perfusion based on indicator-enhanced electrical impedance tomography and validate it by dynamic multidetector computed tomography in two experimental models of acute respiratory distress syndrome. The acute injury was induced in a sublobar segment of the right lung by saline lavage or endotoxin instillation in eight anesthetized mechanically ventilated pigs. For electrical impedance tomography measurements, a conductive bolus (10% saline solution) was injected into the right ventricle during breath hold. Electrical impedance tomography perfusion images were reconstructed by linear and normalized Gauss-Newton reconstruction on a finite element mesh with subsequent element-wise signal and feature analysis. An iodinated contrast agent was used to compute pulmonary blood flow via dynamic multidetector computed tomography. Spatial perfusion was estimated based on first-pass indicator dilution for both electrical impedance and multidetector computed tomography and compared by Pearson correlation and Bland-Altman analysis. Strong correlation was found in dorsoventral (r = 0.92) and in right-to-left directions (r = 0.85) with good limits of agreement of 8.74% in eight lung segments. With a robust electrical impedance tomography perfusion estimation method, we found strong agreement between multidetector computed and electrical impedance tomography perfusion in healthy and regionally injured lungs and demonstrated feasibility of electrical impedance tomography perfusion imaging.

Abstract:

The electrocardiogram (ECG) is a standard cost-efficient and non-invasive tool for the early detection of various cardiac diseases. Quantifying different timing and amplitude features of and in between the single ECG waveforms can reveal important information about the underlying (dys-)function of the heart. Determining these features requires the detection of fiducial points that mark the on- and offset as well as the peak of each ECG waveform (P wave, QRS complex, T wave). Manually setting these points is time-consuming and requires a physician’s expert knowledge. Therefore, the highly modular ECGdeli toolbox for MATLAB was developed, which is capable of filtering clinically recorded 12-lead ECG signals and detecting the fiducial points, also called delineation. It is one of the few open toolboxes offering ECG delineation for P waves, T Waves and QRS complexes. The algorithms provided were evaluated with the QT database, an ECG database comprising 105 signals with fiducial points annotated by clinicians. The median difference between the fiducial points set by the boundary detection algorithm and the clinical annotations serving as a ground truth is less than 4 samples (16 ms) for the P wave and the QRS complex markers.

Abstract:

Computer modeling of the electrophysiology of the heart has undergone significant progress. A healthy heart can be modeled starting from the ion channels via the spread of a depolarization wave on a realistic geometry of the human heart up to the potentials on the body surface and the ECG. Research is advancing regarding modeling diseases of the heart. This article reviews progress in calculating and analyzing the corresponding electrocardiogram (ECG) from simulated depolarization and repolarization waves. First, we describe modeling of the P-wave, the QRS complex and the T-wave of a healthy heart. Then, both the modeling and the corresponding ECGs of several important diseases and arrhythmias are delineated: ischemia and infarction, ectopic beats and extrasystoles, ventricular tachycardia, bundle branch blocks, atrial tachycardia, flutter and fibrillation, genetic diseases and channelopathies, imbalance of electrolytes and drug-induced changes. Finally, we outline the potential impact of computer modeling on ECG interpretation. Computer modeling can contribute to a better comprehension of the relation between features in the ECG and the underlying cardiac condition and disease. It can pave the way for a quantitative analysis of the ECG and can support the cardiologist in identifying events or non-invasively localizing diseased areas. Finally, it can deliver very large databases of reliably labeled ECGs as training data for machine learning.

Abstract:

Large-scale electrophysiological simulations to obtain electrocardiograms (ECG) carry the potential to pro- duce extensive datasets for training of machine learning classifiers to, e.g., discriminate between different cardiac pathologies. The adoption of simulations for these purposes is limited due to a lack of ready-to- use models covering atrial anatomical variability. We built a bi-atrial statistical shape model (SSM) of the endocardial wall based on 47 segmented human CT and MRI datasets using Gaussian process morphable models. Generalization, specificity, and compact- ness metrics were evaluated. The SSM was applied to simulate atrial ECGs in 100 random volumetric instances. The first eigenmode of our SSM reflects a change of the total volume of both atria, the second the asym- metry between left vs. right atrial volume, the third a change in the prominence of the atrial appendages. The SSM is capable of generalizing well to unseen geometries and 95% of the total shape variance is cov- ered by its first 24 eigenvectors. The P waves in the 12-lead ECG of 100 random instances showed a duration of 109 . 7 ±12 . 2 ms in accordance with large cohort studies. The novel bi-atrial SSM itself as well as 100 exemplary instances with rule-based augmentation of atrial wall thickness, fiber orientation, inter-atrial bridges and tags for anatomical structures have been made publicly available. This novel, openly available bi-atrial SSM can in future be employed to generate large sets of realistic atrial geometries as a basis for in silico big data approaches.

Abstract:

Background In acute respiratory distress syndrome (ARDS), non-ventilated perfused regions coexist with non-perfused ventilated regions within lungs. The number of unmatched regions might reflect ARDS severity and affect the risk of ventilation-induced lung injury. Despite pathophysiological relevance, unmatched ventilation and perfusion are not routinely assessed at the bedside. The aims of this study were to quantify unmatched ventilation and perfusion at the bedside by electrical impedance tomography (EIT) investigating their association with mortality in patients with ARDS and to explore the effects of positive end-expiratory pressure (PEEP) on unmatched ventilation and perfusion in subgroups of patients with different ARDS severity based on PaO2/FiO(2) and compliance. Methods Prospective observational study in 50 patients with mild (36%), moderate (46%), and severe (18%) ARDS under clinical ventilation settings. EIT was applied to measure the regional distribution of ventilation and perfusion using central venous bolus of saline 5% during end-inspiratory pause. We defined unmatched units as the percentage of only ventilated units plus the percentage of only perfused units. Results Percentage of unmatched units was significantly higher in non-survivors compared to survivors (32[27-47]% vs. 21[17-27]%, p < 0.001). Percentage of unmatched units was an independent predictor of mortality (OR 1.22, 95% CI 1.07-1.39, p = 0.004) with an area under the ROC curve of 0.88 (95% CI 0.79-0.97, p < 0.001). The percentage of ventilation to the ventral region of the lung was higher than the percentage of ventilation to the dorsal region (32 [27-38]% vs. 18 [13-21]%, p < 0.001), while the opposite was true for perfusion (28 [22-38]% vs. 36 [32-44]%, p < 0.001). Higher percentage of only perfused units was correlated with lower dorsal ventilation (r = - 0.486, p < 0.001) and with lower PaO2/FiO(2) ratio (r = - 0.293, p = 0.039). Conclusions EIT allows bedside assessment of unmatched ventilation and perfusion in mechanically ventilated patients with ARDS. Measurement of unmatched units could identify patients at higher risk of death and could guide personalized treatment.

Abstract:

Cranio-maxillofacial surgery often alters the aesthetics of the face which can be a heavy burden for patients to decide whether or not to undergo surgery. Today, physicians can predict the post-operative face using surgery planning tools to support the patient’s decision-making. While these planning tools allow a simulation of the post-operative face, the facial texture must usually be captured by another 3D texture scan and subsequently mapped on the simulated face. This approach often results in face predictions that do not appear realistic or lively looking and are therefore ill-suited to guide the patient’s decision-making. Instead, we propose a method using a generative adversarial network to modify a facial image according to a 3D soft-tissue estimation of the post-operative face. To circumvent the lack of available data pairs between pre- and post-operative measurements we propose a semi-supervised training strategy using cycle losses that only requires paired open-source data of images and 3D surfaces of the face’s shape. After training on “in-the-wild” images we show that our model can realistically manipulate local regions of a face in a 2D image based on a modified 3D shape. We then test our model on four clinical examples where we predict the post-operative face according to a 3D soft-tissue prediction of surgery outcome, which was simulated by a surgery planning tool. As a result, we aim to demonstrate the potential of our approach to predict realistic post-operative images of faces without the need of paired clinical data, physical models, or 3D texture scans.

Abstract:

During atrial fibrillation, cardiac tissue undergoes different remodeling processes at different scales from the molecular level to the tissue level. One central player that contributes to both electrical and structural remodeling is the myofibroblast. Based on recent experimental evidence on myofibroblasts’ ability to contract, we extended a biophysical myofibroblast model with Ca2+ handling components and studied the effect on cellular and tissue electrophysiology. Using genetic algorithms, we fitted the myofibroblast model parameters to the existing in vitro data. In silico experiments showed that Ca2+ currents can explain the experimentally observed variability regarding the myofibroblast resting membrane potential. The presence of an L-type Ca2+ current can trigger automaticity in the myofibroblast with a cycle length of 799.9 ms. Myocyte action potentials were prolonged when coupled to myofibroblasts with Ca2+ handling machinery. Different spatial myofibroblast distribution patterns increased the vulnerable window to induce arrhythmia from 12 ms in non-fibrotic tissue to 22 ± 2.5 ms and altered the reentry dynamics. Our findings suggest that Ca2+ handling can considerably affect myofibroblast electrophysiology and alter the electrical propagation in atrial tissue composed of myocytes coupled with myofibroblasts. These findings can inform experimental validation experiments to further elucidate the role of myofibroblast Ca2+ handling in atrial arrhythmogenesis.

Abstract:

This contribution is part of a project concerning the creation of an artificial dataset comprising 3D head scans of craniosynostosis patients for a deep-learning-based classification. To conform to real data, both head and neck are required in the 3D scans. However, during patient recording, the neck is often covered by medical staff. Simply pasting an arbitrary neck leaves large gaps in the 3D mesh. We therefore use a publicly available statistical shape model (SSM) for neck reconstruction. However, most SSMs of the head are constructed using healthy subjects, so the full head reconstruction loses the craniosynostosis-specific head shape. We propose a method to recover the neck while keeping the pathological head shape intact. We propose a Laplace- Beltrami-based refinement step to deform the posterior mean shape of the full head model towards the pathological head. The artificial neck is created using the publicly available Liverpool-Y ork-Model. W e apply our method to construct artificial necks for head scans of 50 scaphocephaly patients. Our method reduces mean vertex correspondence error by approximately 1.3 mm compared to the ordinary posterior mean shape, preserves the pathological head shape, and creates a continuous transition between neck and head. The presented method showed good results for reconstructing a plausible neck to craniosynostosis patients. Easily generalized it might also be applicable to other pathological shapes.

Abstract:

Diseases caused by alterations of ionic concentrations are frequently observed challenges and play an important role in clinical practice. The clinically established method for the diagnosis of electrolyte concentration imbalance is blood tests. A rapid and non-invasive point-of-care method is yet needed. The electrocardiogram (ECG) could meet this need and becomes an established diagnostic tool allowing home monitoring of the electrolyte concentration also by wearable devices. In this review, we present the current state of potassium and calcium concentration monitoring using the ECG and summarize results from previous work. Selected clinical studies are presented, supporting or questioning the use of the ECG for the monitoring of electrolyte concentration imbalances. Differences in the findings from automatic monitoring studies are discussed, and current studies utilizing machine learning are presented demonstrating the potential of the deep learning approach. Furthermore, we demonstrate the potential of computational modeling approaches to gain insight into the mechanisms of relevant clinical findings and as a tool to obtain synthetic data for methodical improvements in monitoring approaches.

Abstract:

The solution of the inverse problem of electrocardiology allows the reconstruction of the spatial distribution of the electrical activity of the heart from the body surface electrocardiogram (electrocardiographic imaging, ECGI). ECGI using the equivalent dipole layer (EDL) model has shown to be accurate for cardiac activation times. However, validation of this method to determine repolarization times is lacking. In the present study, we determined the accuracy of the EDL model in reconstructing cardiac repolarization times, and assessed the robustness of the method under less ideal conditions (addition of noise and errors in tissue conductivity). A monodomain model was used to determine the transmembrane potentials in three different excitation-repolarization patterns (sinus beat and ventricular ectopic beats) as the gold standard. These were used to calculate the body surface ECGs using a finite element model. The resulting body surface electrograms (ECGs) were used as input for the EDL-based inverse reconstruction of repolarization times. The reconstructed repolarization times correlated well (COR > 0.85) with the gold standard, with almost no decrease in correlation after adding errors in tissue conductivity of the model or noise to the body surface ECG. Therefore, ECGI using the EDL model allows adequate reconstruction of cardiac repolarization times. Graphical abstract Validation of electrocardiographic imaging for repolarization using forward calculated body surface ECGs from simulated activation-repolarization sequences.

Abstract:

BACKGROUND: Using cardiovascular magnetic resonance imaging (CMR), it is possible to detect diffuse fibrosis of the left ventricle (LV) in patients with atrial fibrillation (AF), which may be independently associated with recurrence of AF after ablation. By conducting CMR, clinical, electrophysiology and biomarker assessment we planned to investigate LV myocardial fibrosis in patients undergoing AF ablation. METHODS: LV fibrosis was assessed by T1 mapping in 31 patients undergoing percutaneous ablation for AF. Galectin-3, coronary sinus type I collagen C terminal telopeptide (ICTP), and type III procollagen N terminal peptide were measured with ELISA. Comparison was made between groups above and below the median for LV extracellular volume fraction (ECV), followed by regression analysis. RESULTS: On linear regression analysis LV ECV had significant associations with invasive left atrial pressure (Beta 0.49, P = 0.008) and coronary sinus ICTP (Beta 0.75, P < 0.001), which remained significant on multivariable regression. CONCLUSION: LV fibrosis in patients with AF is associated with left atrial pressure and invasively measured levels of ICTP turnover biomarker.

Abstract:

Background Radiofrequency ablation (RFA) is a common approach to treat cardiac arrhythmias. During this intervention, numerous strategies are applied to indirectly estimate lesion formation. However, the assessment of the spatial extent of these acute injuries needs to be improved in order to create well-defined and durable ablation lesions. Methods We investigated the electrophysiological characteristics of rat atrial myocardium during an ex vivo RFA procedure with fluorescence-optical and electrical mapping. By analyzing optical data, the temporal growth of punctiform ablation lesions was reconstructed after stepwise RFA sequences. Unipolar electrograms (EGMs) were simultaneously recorded by a multielectrode array (MEA) before and after each RFA sequence. Based on the optical results, we searched for electrical features to delineate these lesions from healthy myocardium. Results Several unipolar EGM parameters were monotonically decreasing when distances between the electrode and lesion boundary were smaller than 2 mm. The negative component of the unipolar EGM [negative peak amplitude (Aneg)] vanished for distances lesser than 0.4 mm to the lesion boundary. Median peak-to-peak amplitude (Vpp) was decreased by 75% compared to baseline. Conclusion Aneg and Vpp are excellent parameters to discriminate the growing lesion area from healthy myocardium. The experimental setup opens new opportunities to investigate EGM characteristics of more complex ablation lesions.

Abstract:

The electrophysiological mechanism of the sinus node automaticity was previously considered exclusively regulated by the so-called "funny current". However, parallel investigations increasingly emphasized the importance of the Ca-homeostasis and Na/Ca exchanger (NCX). Recently, increasing experimental evidence, as well as insight through mechanistic modeling demonstrates the crucial role of the exchanger in sinus node pacemaking. NCX had a key role in the exciting story of discovery of sinus node pacemaking mechanisms, which recently settled with a consensus on the coupled-clock mechanism after decades of debate. This review focuses on the role of the Na/Ca exchanger from the early results and concepts to recent advances and attempts to give a balanced summary of the characteristics of the local, spontaneous, and rhythmic Ca releases, the molecular control of the NCX and its role in the fight-or-flight response. Transgenic animal models and pharmacological manipulation of intracellular Ca concentration and/or NCX demonstrate the pivotal function of the exchanger in sinus node automaticity. We also highlight where specific hypotheses regarding NCX function have been derived from computational modeling and require experimental validation. Nonselectivity of NCX inhibitors and the complex interplay of processes involved in Ca handling render the design and interpretation of these experiments challenging.

Abstract:

This work concerns the mathematical and numerical modeling of the heart. The aim is to enhance the understanding of the cardiac function in both physiological and pathological conditions. Along this road, a challenge arises from the multi-scale and multi-physics nature of the mathematical problem at hand. In this paper, we propose an electromechanical model that, in bi-ventricle geometries, combines the monodomain equation, the Bueno-Orovio minimal ionic model, and the Holzapfel-Ogden strain energy function for the passive myocardial tissue modelling together with the active strain approach combined with a model for the transmurally heterogeneous thickening of the myocardium. Since the distribution of the electric signal is dependent on the fibres orientation of the ventricles, we use a Laplace-Dirichlet Rule-Based algorithm to determine the myocardial fibres and sheets configuration in the whole bi-ventricle. In this paper, we study the influence of different fibre directions and incompressibility constraint and penalization on the compressibility of the material (bulk modulus) on the pressure-volume relation simulating a full heart beat. The coupled electromechanical problem is addressed by means of a fully segregated scheme. The numerical discretization is based on the Finite Element Method for the spatial discretization and on Backward Differentiation Formulas for the time discretization. The arising non-linear algebraic system coming from application of the implicit scheme is solved through the Newton method. Numerical simulations are carried out in a patient-specific biventricle geometry to highlight the most relevant results of both electrophysiology and mechanics and to compare them with physiological data and measurements. We show how various fibre configurations and bulk modulus modify relevant clinical quantities such as stroke volume, ejection fraction and ventricle contractility.

Abstract:

Identification of atrial sites that perpetuate atrial fibrillation (AF), and ablation thereof terminates AF, is challenging. We hypothesized that specific electrogram (EGM) characteristics identify AF-termination sites (AFTS). Twenty-one patients in whom low-voltage-guided ablation after pulmonary vein isolation terminated clinical persistent AF were included. Patients were included if short RF-delivery for <8sec at a given atrial site was associated with acute termination of clinical persistent AF. EGM-characteristics at 21 AFTS, 105 targeted sites without termination and 105 non-targeted control sites were analyzed. Alteration of EGM-characteristics by local fibrosis was evaluated in a three-dimensional high resolution (100 µm)-computational AF model. AFTS demonstrated lower EGM-voltage, higher EGM-cycle-length-coverage, shorter AF-cycle-length and higher pattern consistency than control sites (0.49 ± 0.39 mV vs. 0.83 ± 0.76 mV, p < 0.0001; 79 ± 16% vs. 59 ± 22%, p = 0.0022; 173 ± 49 ms vs. 198 ± 34 ms, p = 0.047; 80% vs. 30%, p < 0.01). Among targeted sites, AFTS had higher EGM-cycle-length coverage, shorter local AF-cycle-length and higher pattern consistency than targeted sites without AF-termination (79 ± 16% vs. 63 ± 23%, p = 0.02; 173 ± 49 ms vs. 210 ± 44 ms, p = 0.002; 80% vs. 40%, p = 0.01). Low voltage (0.52 ± 0.3 mV) fractionated EGMs (79 ± 24 ms) with delayed components in sinus rhythm ('atrial late potentials', respectively 'ALP') were observed at 71% of AFTS. EGMs recorded from fibrotic areas in computational models demonstrated comparable EGM-characteristics both in simulated AF and sinus rhythm. AFTS may therefore be identified by locally consistent, fractionated low-voltage EGMs with high cycle-length-coverage and rapid activity in AF, with low-voltage, fractionated EGMs with delayed components/ 'atrial late potentials' (ALP) persisting in sinus rhythm.

Abstract:

Afterinterventionssuchasbypasssurgeriesthevascularfunctionischeckedqualitatively and remotely by observing the blood dynamics inside the vessel via Fluorescence Angiography. This state-of-the-art method has to be improved by introducing a quantitatively measured blood flow. Previous approaches show that the measured blood flow cannot be easily calibrated against a gold standard reference. In order to systematically address the possible sources of error, we investigated the error in geodesic length measurement caused by spatial discretization on the camera chip. We used an in-silico vessel segmentation model based on mathematical functions as a ground truth for the length of vessel-like anatomical structures in the continuous space. Discretization errors for the chosen models were determined in a typical magnitude of 6%. Since this length error would propagate to an unacceptable error in blood flow measurement, counteractions need to be developed. Therefore, different methods for the centerline extraction and spatial interpolation have been tested and compared against their performance in reducing the discretization error in length measurement by re-continualization. In conclusion, the discretization error is reduced by the re-continualization of the centerline to an acceptable range. The discretization error is dependent on the complexity of the centerline and this dependency is also reduced. Thereby the centerline extraction by erosion in combination with the piecewise Bézier curve fitting performs best by reducing the error to 2.7% with an acceptable computational time.

Abstract:

Von wandernden Ionen über das Zellgewebe bis hin zur Aufzeichnung eines EKG: Die Softwaresimulation des menschlichen Herzens ermöglicht maßgeschneiderte Therapien. Am Karlsruher Institut für Technologie (KIT) haben Forscher ein Computermodell des menschlichen Herzens entwickelt. Die Wissenschaftler sind mittlerweile sogar schon so weit, dass sie das Modell auf die individuellen Eigen­schaften eines einzelnen Patienten maßschneidern können. Diese ­Simulation hat einen erheblichen Nutzen für die medizinische Praxis.

Abstract:

Therapeutic hypothermia (TH) is an approved neuroproctetive treatment to reduce neurological morbidity and mortality after hypoxic-ischemic damage related to cardiac arrest and neonatal asphyxia. Also in the treatment of acute ischemic stroke (AIS), which in Western countries still shows a very high mortality rate of about 25 %, selective mild TH by means of Targeted Temperature Management (TTM) could potentially decrease final infarct volume. In this respect, a novel intracarotid blood cooling catheter system has recently been developed, which allows for combined carotid blood cooling and mechanical thrombectomy (MT) and aims at selective mild TH in the affected ischemic brain (core and penumbra). Unfortunately, so far direct measurement and control of cooled cerebral temperature requires invasive or elaborate MRI-assisted measurements. Computational modeling provides unique opportunities to predict the resulting cerebral temperatures on the other hand. In this work, a simplified 3D brain model was generated and coupled with a 1D hemodynamics model to predict spatio-temporal cerebral temperature profiles using finite element modeling. Cerebral blood and tissue temperatures as well as the systemic temperature were analyzed for physiological conditions as well as for a middle cerebral artery (MCA) M1 occlusion. Furthermore, vessel recanalization and its effect on cerebral temperature was analyzed. The results show a significant influence of collateral flow on the cooling effect and are in accordance with experimental data in animals. Our model predicted a possible neuroprotective temperature decrease of 2.5 ℃ for the territory of MCA perfusion after 60 min of blood cooling, which underlines the potential of the new device and the use of TTM in case of AIS.

Abstract:

Background and Purpose: The exact mechanism of spontaneous pacemaking is not fully understood. Recent results suggest tight cooperation between intracellular Ca handling and sarcolemmal ion channels. An important player of this crosstalk is the Na/Ca exchanger (NCX), however, direct pharmacological evidence was unavailable so far because of the lack of a selective inhibitor. We investigated the role of the NCX current in pacemaking and analyzed the functional consequences of the I-NCX coupling by applying the novel selective NCX inhibitor ORM-10962 on the sinus node (SAN). Experimental Approach: Currents were measured by patch-clamp, Ca-transients were monitored by fluorescent optical method in rabbit SAN cells. Action potentials (AP) were recorded from rabbit SAN tissue preparations. Mechanistic computational data were obtained using the Yaniv . SAN model. Key Results: ORM-10962 (ORM) marginally reduced the SAN pacemaking cycle length with a marked increase in the diastolic Ca level as well as the transient amplitude. The bradycardic effect of NCX inhibition was augmented when the funny-current (I) was previously inhibited and , the effect of I was augmented when the Ca handling was suppressed. Conclusion and Implications: We confirmed the contribution of the NCX current to cardiac pacemaking using a novel NCX inhibitor. Our experimental and modeling data support a close cooperation between I and NCX providing an important functional consequence: these currents together establish a strong depolarization capacity providing important safety factor for stable pacemaking. Thus, after individual inhibition of I or NCX, excessive bradycardia or instability cannot be expected because each of these currents may compensate for the reduction of the other providing safe and rhythmic SAN pacemaking.

Abstract:

OBJECTIVE: Unipolar intracardiac electrograms (uEGMs) measured inside the atria during electro-anatomic mapping contain diagnostic information about cardiac excitation and tissue properties. The ventricular far field (VFF) caused by ventricular depolarization compromises these signals. Current signal processing techniques require several seconds of local uEGMs to remove the VFF component and thus prolong the clinical mapping procedure. We developed an approach to remove the VFF component using data obtained during initial anatomy acquisition. METHODS: We developed two models which can approximate the spatio-temporal distribution of the VFF component based on acquired EGM data: Polynomial fit, and dipole fit. Both were benchmarked based on simulated cardiac excitation in two models of the human heart and applied to clinical data. RESULTS: VFF data acquired in one atrium were used to estimate model parameters. Under realistic noise conditions, a dipole model approximated the VFF with a median deviation of 0.029mV, yielding a median VFF attenuation of 142. In a different setup, only VFF data acquired at distances of more than 5mm to the atrial endocardium were used to estimate the model parameters. The VFF component was then extrapolated for a layer of 5mm thickness lining the endocardial tissue. A median deviation of 0.082mV (median VFF attenuation of 49x) was achieved under realistic noise conditions. CONCLUSION: It is feasible to model the VFF component in a personalized way and effectively remove it from uEGMs. SIGNIFICANCE: Application of our novel, simple and computationally inexpensive methods allows immediate diagnostic assessment of uEGM data without prolonging data acquisition.

Abstract:

End-stage chronic kidney disease (CKD) patients are facing a 30% rise for the risk of lethal cardiac events (LCE) compared to non-CKD patients. At the same time, these patients undergoing dialysis experience shifts in the potassium concentrations. The increased risk of LCE paired with the concentration changes suggest a connection between LCE and concentration disbalances. To prove this link, a continuous monitoring device for the ionic concentrations, e.g. the ECG, is needed. In this work, we want to answer if an optimised signal processing chain can improve the result quantify the influence of a disbalanced training dataset on the final estimation result. The study was performed on a dataset consisting of 12-lead ECGs recorded during dialysis sessions of 32 patients. We selected three features to find a mapping from ECG features to [K+]o: T-wave ascending slope, T-wave descending slope and T-wave amplitude. A polynomial model of 3rd order was used to reconstruct the concentrations from these features. We solved a regularised weighted least squares problem with a weighting matrix dependent on the frequency of each concentration in the dataset (frequent concentration weighted less). By doing so, we tried to generate a model being suitable for the whole range of the concentrations.With weighting, errors are increasing for the whole dataset. For the data partition with [K+]o<5 mmol/l, errors are increasing, for [K+]o≥5 mmol/l, errors are decreasing. However, and apart from the exact reconstruction results, we can conclude that a model being valid for all patients and not only the majority, needs to be learned with a more homogeneous dataset. This can be achieved by leaving out data points or by weighting the errors during the model fitting. With increasing weighting, we increase the performance on the part of the [K+]o that are less frequent which was desired in our case.

Abstract:

The morphology of the electrocardiogram (ECG) varies among different healthy subjects due to anatomical and structural reasons, such as for example the shape of the heart geometry or the position and size of surrounding organs in the torso. Knowledge about these ECG morphology changes could be used to parameterize electrophysiological simula- tions of the human heart. In this work, we detected the boundaries of ECG waveforms, i.e. the P-wave, the QRS-complex and the T-wave, in 12- lead ECGs from 918 healthy subjects in the Physionet Com- puting in Cardiology Challenge 2020 Database with the IBT openECG toolbox. Subsequently, we obtained the onset, the peak and the offset of each P-wave, QRS-complex and T-wave in the signal. In this way, the duration of the P-wave, the QRS- complex and the T-wave, the PQ-, RR- and the QT-interval as well as the amplitudes of the P-wave, the Q-, R- and S- peak and the T-wave in each lead were extracted from the 918 healthy ECGs. Their statistical distributions and correlation between each other were assessed. The highest variabilities among the 918 healthy subject were found for the RR interval and the amplitudes of the QRS- complex. The highest correlation was observed for feature pairs that represent the same feature in different leads. Es- pecially the R-peak amplitudes showed a strong correlation across different leads. The calculated feature distributions can be used to optimize the parameters of populations of cardiac electrophysiological models. In this way, realistic in-silico generated surface ECGs can be simulated in large scale and could be used as input data for machine learning algorithms for a classification of cardio- vascular diseases.

Abstract:

This article analyzes the tools and methods used in the analysis of emotions from text for the purpose of managing society. It illustrates the influence of emotions on the management of people, society and businesses processes. Their importance and the changes that occurs over time in the processes of managing society. The role that social networks plays in managing society and the methods they uses. We researched different websites and software, observed their mechanisms for data collection, its analysis and use for the purpose of managing society. In general, we analyze the most common methods, the factors that affects the choice of a particular method, their influence and based on our analy-sis, give recommendations for improving the process of analyzing emotions for the purpose of managing society.

Abstract:

BACKGROUND: Electrical impedance tomography (EIT) with indicator dilution may be clinically useful to measure relative lung perfusion, but there is limited information on the performance of this technique. METHODS: Thirteen pigs (50-66 kg) were anaesthetised and mechanically ventilated. Sequential changes in ventilation were made: (i) right-lung ventilation with left-lung collapse, (ii) two-lung ventilation with optimised PEEP, (iii) two-lung ventilation with zero PEEP after saline lung lavage, (iv) two-lung ventilation with maximum PEEP (20/25 cm HO to achieve peak airway pressure 45 cm HO), and (v) two-lung ventilation under unilateral pulmonary artery occlusion. Relative lung perfusion was assessed with EIT and central venous injection of saline 3%, 5%, and 10% (10 ml) during breath holds. Relative perfusion was determined by positron emission tomography (PET) using Gallium-labelled microspheres. EIT and PET were compared in eight regions of equal ventro-dorsal height (right, left, ventral, mid-ventral, mid-dorsal, and dorsal), and directional changes in regional perfusion were determined. RESULTS: Differences between methods were relatively small (95% of values differed by less than 8.7%, 8.9%, and 9.5% for saline 10%, 5%, and 3%, respectively). Compared with PET, EIT underestimated relative perfusion in dependent, and overestimated it in non-dependent, regions. EIT and PET detected the same direction of change in relative lung perfusion in 68.9-95.9% of measurements. CONCLUSIONS: The agreement between EIT and PET for measuring and tracking changes of relative lung perfusion was satisfactory for clinical purposes. Indicator-based EIT may prove useful for measuring pulmonary perfusion at bedside.

Abstract:

Local brain hypothermia is an attractive method for providing cerebral neuroprotection for ischemic stroke patients and at the same time reducing systemic side effects of cooling. In acute ischemic stroke patients with large vessel occlusion, combination with endovascular mechanical recanalization treatment could potentially allow for an alleviation of inflammatory and apoptotic pathways in the critical phase of reperfusion. The direct cooling of arterial blood by means of an intra-carotid heat exchange catheter compatible with recanalization systems is a novel promising approach. Focusing on the concept of "cold reperfusion", we developed an energetic model to calculate the rate of temperature decrease during intra-carotid cooling in case of physiological as well as decreased perfusion. Additionally, we discussed and considered the effect and biological significance of temperature decrease on resulting brain perfusion. Our model predicted a 2 °C brain temperature decrease in 8.3, 11.8 and 26.2 min at perfusion rates of 50, 30 and 10ml100g⋅min, respectively. The systemic temperature decrease - caused by the venous blood return to the main circulation - was limited to 0.5 °C in 60 min. Our results underline the potential of catheter-assisted, intracarotid blood cooling to provide a fast and selective brain temperature decrease in the phase of vessel recanalization. This method can potentially allow for a tissue hypothermia during the restoration of the physiological flow and thus a "cold reperfusion" in the setting of mechanical recanalization.

Abstract:

Atypical atrial flutter (AFlut) is a reentrant arrhythmia which patients frequently develop after ablation for atrial fibrillation (AF). Indeed, substrate modifications during AF ablation can increase the likelihood to develop AFlut and it is clinically not feasible to reliably and sensitively test if a patient is vulnerable to AFlut. Here, we present a novel method based on personalized computational models to identify pathways along which AFlut can be sustained in an individual patient. We build a personalized model of atrial excitation propagation considering the anatomy as well as the spatial distribution of anisotropic conduction velocity and repolarization characteristics based on a combination of a priori knowledge on the population level and information derived from measurements performed in the individual patient. The fast marching scheme is employed to compute activation times for stimuli from all parts of the atria. Potential flutter pathways are then identified by tracing loops from wave front collision sites and constricting them using a geometric snake approach under consideration of the heterogeneous wavelength condition. In this way, all pathways along which AFlut can be sustained are identified. Flutter pathways can be instantiated by using an eikonal-diffusion phase extrapolation approach and a dynamic multifront fast marching simulation. In these dynamic simulations, the initial pattern eventually turns into the one driven by the dominant pathway, which is the only pathway that can be observed clinically. We assessed the sensitivity of the flutter pathway maps with respect to conduction velocity and its anisotropy. Moreover, we demonstrate the application of tailored models considering disease-specific repolarization properties (healthy, AF-remodeled, potassium channel mutations) as well as applicabiltiy on a clinical dataset. Finally, we tested how AFlut vulnerability of these substrates is modulated by exemplary antiarrhythmic drugs (amiodarone, dronedarone). Our novel method allows to assess the vulnerability of an individual patient to develop AFlut based on the personal anatomical, electrophysiological, and pharmacological characteristics. In contrast to clinical electrophysiological studies, our computational approach provides the means to identify all possible AFlut pathways and not just the currently dominant one. This allows to consider all relevant AFlut pathways when tailoring clinical ablation therapy in order to reduce the development and recurrence of AFlut.

Abstract:

Each heartbeat is initiated by cyclic spontaneous depolarization of cardiomyocytes in the sinus node forming the primary natural pacemaker. In patients with end-stage renal disease undergoing hemodialysis, it was recently shown that the heart rate drops to very low values before they suffer from sudden cardiac death with an unexplained high incidence. We hypothesize that the electrolyte changes commonly occurring in these patients affect sinus node beating rate and could be responsible for severe bradycardia. To test this hypothesis, we extended the Fabbri et al. computational model of human sinus node cells to account for the dynamic intracellular balance of ion concentrations. Using this model, we systematically tested the effect of altered extracellular potassium, calcium, and sodium concentrations. Although sodium changes had negligible (0.15 bpm/mM) and potassium changes mild effects (8 bpm/mM), calcium changes markedly affected the beating rate (46 bpm/mM ionized calcium without autonomic control). This pronounced bradycardic effect of hypocalcemia was mediated primarily by I attenuation due to reduced driving force, particularly during late depolarization. This, in turn, caused secondary reduction of calcium concentration in the intracellular compartments and subsequent attenuation of inward I and reduction of intracellular sodium. Our in silico findings are complemented and substantiated by an empirical database study comprising 22,501 pairs of blood samples and in vivo heart rate measurements in hemodialysis patients and healthy individuals. A reduction of extracellular calcium was correlated with a decrease of heartrate by 9.9 bpm/mM total serum calcium (p < 0.001) with intact autonomic control in the cross-sectional population. In conclusion, we present mechanistic in silico and empirical in vivo data supporting the so far neglected but experimentally testable and potentially important mechanism of hypocalcemia-induced bradycardia and asystole, potentially responsible for the highly increased and so far unexplained risk of sudden cardiac death in the hemodialysis patient population.

Abstract:

Chronic kidney disease (CKD) affects 13% of the worldwide population and end stage patients often receive haemodialysis treatment to control the electrolyte concentrations. The cardiovascular death rate increases by 10% - 30% in dialysis patients than in general population. To analyse possible links between electrolyte concentration variation and cardiovascular diseases, a continuous non-invasive monitoring tool enabling the estimation of potassium and calcium concentration from features of the ECG is desired. Although the ECG was shown capable of being used for this purpose, the method still needs improvement. In this study, we examine the influence of lead reduction techniques on the estimation results of serum calcium and potassium concentrations.We used simulated 12 lead ECG signals obtained using an adapted Himeno et al. model. Aiming at a precise estimation of the electrolyte concentrations, we compared the estimation based on standard ECG leads with the estimation using linearly transformed fusion signals. The transformed signals were extracted from two lead reduction techniques: principle component analysis (PCA) and maximum amplitude transformation (Max- Amp). Five features describing the electrolyte changes were calculated from the signals. To reconstruct the ionic concentrations, we applied a first and a third order polynomial regression connecting the calculated features and concentration values. Furthermore, we added 30 dB white Gaussian noise to the ECGs to imitate clinically measured signals. For the noisefree case, the smallest estimation error was achieved with a specific single lead from the standard 12 lead ECG. For example, for a first order polynomial regression, the error was 0.0003±0.0767 mmol/l (mean±standard deviation) for potassium and -0.0036±0.1710 mmol/l for calcium (Wilson lead V1). For the noisy case, the PCA signal showed the best estimation performance with an error of -0.003±0.2005 mmol/l for potassium and -0.0002±0.2040 mmol/l for calcium (both first order fit). Our results show that PCA as ECG lead reduction technique is more robust against noise than MaxAmp and standard ECG leads for ionic concentration reconstruction.

Abstract:

Changes of serum and extracellular ion concentrations occur regularly in patients with chronic kidney disease (CKD). Recently, hypocalcemia, i.e. a decrease of the extra-cellular calcium concentration [Ca2+]o, has been suggested as potential pathomechanism contributing to the unexplained high rate of sudden cardiac death (SCD) in CKD patients. In particular, there is a hypothesis that hypocalcaemia could slow down natural pacemaking in the human sinus node to fatal degrees. Here, we address the question whether there are inter-species differences in the response of cellular sinus node pacemaking to changes of [Ca2+]o. Towards this end, we employ computational models of mouse, rabbit and human sinus node cells. The Fabbri et al. human model was updated to consider changes of intracellular ion concentrations. We identified crucial inter-species differences in the response of cellular pacemaking in the sinus node to changes of [Ca2+]o with little changes of cycle length in mouse and rabbit models (<83 ms) in contrast to a pronounced bradycardic effect in the human model (up to > 1000 ms). Our results suggest that experiments with human sinus node cells are required to investigate the potential mechanism of hypocalcaemia-induced bradycardic SCD in CKD patients and small animal models are not well suited.

Abstract:

Atrial fibrillation (AF) is the most prevalent form of cardiac arrhythmia. The atrial wall thickness (AWT) can potentially improve our understanding of the mechanism underlying atrial structure that drives AF and provides important clinical information. However, most existing studies for estimating AWT rely on ruler-based measurements performed on only a few selected locations in 2D or 3D using digital calipers. Only a few studies have developed automatic approaches to estimate the AWT in the left atrium, and there are currently no methods to robustly estimate the AWT of both atrial chambers. Therefore, we have developed a computational pipeline to automatically calculate the 3D AWT across bi-atrial chambers and extensively validated our pipeline on both ex vivo and in vivo human atria data. The atrial geometry was first obtained by segmenting the atrial wall from the MRIs using a novel machine learning approach. The epicardial and endocardial surfaces were then separated using a multi-planar convex hull approach to define boundary conditions, from which, a Laplace equation was solved numerically to automatically separate bi-atrial chambers. To robustly estimate the AWT in each atrial chamber, coupled partial differential equations by coupling the Laplace solution with two surface trajectory functions were formulated and solved. Our pipeline enabled the reconstruction and visualization of the 3D AWT for bi-atrial chambers with a relative error of 8% and outperformed existing algorithms by >7%. Our approach can potentially lead to improved clinical diagnosis, patient stratification, and clinical guidance during ablation treatment for patients with AF.

Abstract:

Under persistent atrial fibrillation (peAF), cardiac tissue experiences electrophysiological and structural remodeling. Fibrosis in the atrial tissue has an important impact on the myocyte action potential and its propagation. The objective of this work is to explore the effect of heterogeneities present in the fibrotic tissue and their impact on the intracardiac electrogram (EGM). Human atrial myocyte and fibroblast electrophysiology was simulated using mathematical models proposed by Koivumäki et al. to represent electrical remodeling under peAF and the paracrine effect of the transforming grow factor 1 (TGF-1). 2D tissue simulations were computed varying the density of fibrosis (10%, 20% and 40%), myofibroblasts and collagen were randomly distributed with different ratios (0%-100%, 50%-50% and 100%- 0%). Results show that increasing the fibrosis density changes the re-entry dynamics from functional to anatomical due to a block in conduction in regions with high fibrosis density (40%). EGM morphology was affected by different ratios of myofibroblasts-collagen. For low myofibroblast densities (below 50%) the duration of active segments was shorter compared to higher myofibroblasts densities (above 50%). Our results show that fibrosis heterogeneities can alter the dynamics of the re-entry and the morphology of the EGM.

Abstract:

Aims Chronic left atrial enlargement (LAE) increases the risk of atrial fibrillation. Electrocardiogram (ECG) criteria might provide a means to diagnose LAE and identify patients at risk; however, current criteria perform poorly. We seek to characterize the potentially differential effects of atrial dilation vs. hypertrophy on the ECG P-wave. Methods and results We predict effects on the P-wave of (i) left atrial dilation (LAD), i.e. an increase of LA cavity volume without an increase in myocardial volume, (ii) left atrial concentric hypertrophy (LACH), i.e. a thickened myocardial wall, and (iii) a combination of the two. We performed a computational study in a cohort of 72 anatomical variants, derived from four human atrial anatomies. To model LAD, pressure was applied to the LA endocardium increasing cavity volume by up to 100%. For LACH, the LA wall was thickened by up to 3.3 mm. P-waves were derived by simulating atrial excitation propagation and computing the body surface ECG. The sensitivity regarding changes beyond purely anatomical effects was analysed by altering conduction velocity by 25% in 96 additional model variants. Left atrial dilation prolonged P-wave duration (PWd) in two of four subjects; in one subject a shortening, and in the other a variable change were seen. Left atrial concentric hypertrophy, in contrast, consistently increased P-wave terminal force in lead V1 (PTF-V1) in all subjects through an enlarged amplitude while PWd was unaffected. Combined hypertrophy and dilation generally enhanced the effect of hypertrophy on PTF-V1. Conclusion Isolated LAD has moderate effects on the currently used P-wave criteria, explaining the limited utility of PWd and PTF-V1 in detecting LAE in clinical practice. In contrast, PTF-V1 may be a more sensitive indicator of LA myocardial hypertrophy.

Abstract:

The cardiac muscarinic receptor (M2R) regulates heart rate, in part, by modulating the acetylcholine (ACh) activated K+ current IK,ACh through dissociation of G-proteins, that in turn activate KACh channels. Recently, M2Rs were noted to exhibit intrinsic voltage sensitivity, i.e. their affinity for ligands varies in a voltage dependent manner. The voltage sensitivity of M2R implies that the affinity for ACh (and thus the ACh effect) varies throughout the time course of a cardiac electrical cycle. The aim of this study was to investigate the contribution of M2R voltage sensitivity to the rate and shape of the human sinus node action potentials in physiological and pathophysiological conditions. We developed a Markovian model of the IK,ACh modulation by voltage and integrated it into a computational model of human sinus node. We performed simulations with the integrated model varying ACh concentration and voltage sensitivity. Low ACh exerted a larger effect on IK,ACh at hyperpolarized versus depolarized membrane voltages. This led to a slowing of the pacemaker rate due to an attenuated slope of phase 4 depolarization with only marginal effect on action potential duration and amplitude. We also simulated the theoretical effects of genetic variants that alter the voltage sensitivity of M2R. Modest negative shifts in voltage sensitivity, predicted to increase the affinity of the receptor for ACh, slowed the rate of phase 4 depolarization and slowed heart rate, while modest positive shifts increased heart rate. These simulations support our hypothesis that altered M2R voltage sensitivity contributes to disease and provide a novel mechanistic foundation to study clinical disorders such as atrial fibrillation and inappropriate sinus tachycardia.

Abstract:

Electrocardiographic imaging (ECGI) reconstructs the electrical activity of the heart from a dense array of body-surface electrocardiograms and a patient-specific heart-torso geometry. Depending on how it is formulated, ECGI allows the reconstruction of the activation and recovery sequence of the heart, the origin of premature beats or tachycardia, the anchors/hotspots of re-entrant arrhythmias and other electrophysiological quantities of interest. Importantly, these quantities are directly and noninvasively reconstructed in a digitized model of the patient’s three-dimensional heart, which has led to clinical interest in ECGI’s ability to personalize diagnosis and guide therapy. Despite considerable development over the last decades, validation of ECGI is challenging. Firstly, results depend considerably on implementation choices, which are necessary to deal with ECGI’s ill-posed character. Secondly, it is challenging to obtain (invasive) ground truth data of high quality. In this review, we discuss the current status of ECGI validation as well as the major challenges remaining for complete adoption of ECGI in clinical practice. Specifically, showing clinical benefit is essential for the adoption of ECGI. Such benefit may lie in patient outcome improvement, workflow improvement, or cost reduction. Future studies should focus on these aspects to achieve broad adoption of ECGI, but only after the technical challenges have been solved for that specific application/pathology. We propose ‘best’ practices for technical validation and highlight collaborative efforts recently organized in this field. Continued interaction between engineers, basic scientists and physicians remains essential to find a hybrid between technical achievements, pathological mechanisms insights, and clinical benefit, to evolve this powerful technique towards a useful role in clinical practice.

Abstract:

Electrocardiographic imaging (ECGI) strongly relies on a priori assumptions and additional information to overcome ill-posedness. The major challenge of obtaining good reconstructions consists in finding ways to add information that effectively restricts the solution space without violating properties of the sought solution. In this work, we attempt to address this problem by constructing a spatio-temporal basis of body surface potentials (BSP) from simulations of many focal excitations. Measured BSPs are projected onto this basis and reconstructions are expressed as linear combinations of corresponding transmembrane voltage (TMV) basis vectors. The novel method was applied to simulations of 100 atrial ectopic foci with three different conduction velocities. Three signal-to-noise ratios (SNR) and bases of six different temporal lengths were considered. Reconstruction quality was evaluated using the spatial correlation coefficient of TMVs as well as estimated local activation times (LAT). The focus localization error was assessed by computing the geodesic distance between true and reconstructed foci. Compared with an optimally parameterized Tikhonov-Greensite method, the BSP basis reconstruction increased the mean TMV correlation by up to 22, 24, and 32% for an SNR of 40, 20, and 0 dB, respectively. Mean LAT correlation could be improved by up to 5, 7, and 19% for the three SNRs. For 0 dB, the average localization error could be halved from 15.8 to 7.9 mm. For the largest basis length, the localization error was always below 34 mm. In conclusion, the new method improved reconstructions of atrial ectopic activity especially for low SNRs. Localization of ectopic foci turned out to be more robust and more accurate. Preliminary experiments indicate that the basis generalizes to some extent from the training data and may even be applied for reconstruction of non-ectopic activity.

Abstract:

Optical mapping is widely used as a tool to investigate cardiac electrophysiology in ex vivo preparations. Digital filtering of fluorescence-optical data is an important requirement for robust subsequent data analysis and still a challenge when processing data acquired from thin mammalian myocardium. Therefore, we propose and investigate the use of an adaptive spatio-temporal Gaussian filter for processing optical mapping signals from these kinds of tissue usually having low signal-to-noise ratio (SNR). We demonstrate how filtering parameters can be chosen automatically without additional user input. For systematic comparison of this filter with standard filtering methods from the literature, we generated synthetic signals representing optical recordings from atrial myocardium of a rat heart with varying SNR. Furthermore, all filter methods were applied to experimental data from an ex vivo setup. Our developed filter outperformed the other filter methods regarding local activation time detection at SNRs smaller than 3 dB which are typical noise ratios expected in these signals. At higher SNRs, the proposed filter performed slightly worse than the methods from literature. In conclusion, the proposed adaptive spatio-temporal Gaussian filter is an appropriate tool for investigating fluorescence-optical data with low SNR. The spatio-temporal filter parameters were automatically adapted in contrast to the other investigated filters.

Abstract:

Promising results have been reported in noninvasive estimation of cardiac activation times (AT) using the equivalent dipole layer (EDL) source model in combination with the boundary element method (BEM). However, the assumption of equal anisotropy ratios in the heart that underlies the EDL model does not reflect reality. In the present study, we quantify the errors of the nonlinear AT imaging based on the EDL approximation. Nine different excitation patterns (sinus rhythm and eight ectopic beats) were simulated with the monodomain model. Based on the bidomain theory, the body surface potential maps (BSPMs) were calculated for a realistic finite element volume conductor with an anisotropic heart model. For the forward calculations, three cases of bidomain conductivity tensors in the heart were considered: isotropic, equal, and unequal anisotropy ratios in the intra- and extracellular spaces. In all inverse reconstructions, the EDL model with BEM was employed: AT were estimated by solving the nonlinear optimization problem with the initial guess provided by the fastest route algorithm. Expectedly, the case of unequal anisotropy ratios resulted in larger localization errors for almost all considered activation patterns. For the sinus rhythm, all sites of early activation were correctly estimated with an optimal regularization parameter being used. For the ectopic beats, all but one foci were correctly classified to have either endo- or epicardial origin with an average localization error of 20.4 mm for unequal anisotropy ratio. The obtained results confirm validation studies and suggest that cardiac anisotropy might be neglected in clinical applications of the considered EDL-based inverse procedure.

Abstract:

BACKGROUND: Complementary to clinical and experimental studies, computational cardiac modeling serves to obtain a comprehensive understanding of the cardiovascular system in order to analyze dysfunction, evaluate existing, and develop novel treatment strategies. OBJECTIVES: We describe the basics of multiscale computational modeling of cardiac electrophysiology from the molecular ion channel to the whole body scale. By modeling cardiac ischemia, we illustrate how in silico experiments can contribute to our understanding of how the pathophysiological mechanisms translate into changes observed in diagnostic tools such as the electrocardiogram (ECG). MATERIALS AND METHODS: Quantitative in silico modeling spans a wide range of scales from ion channel biophysics to ECG signals. For each of the scales, a set of mathematical equations describes electrophysiology in relation to the other scales. Integration of ischemia-induced changes is performed on the ion channel, single-cell, and tissue level. This approach allows us to study how effects simulated at molecular scales translate to changes in the ECG. RESULTS: Ischemia induces action potential shortening and conduction slowing. Hence, ischemic myocardium has distinct and significant effects on propagation and repolarization of excitation, depending on the intramural extent of the ischemic region. For transmural and subendocardial ischemic regions, ST segment elevation and depression, respectively, were observed, whereas intermediate ischemic regions were found to be electrically silent (NSTEMI). CONCLUSIONS: In silico modeling contributes quantitative and mechanistic insight into fundamental ischemia-related arrhythmogenic mechanisms. In addition, computational modeling can help to translate experimental findings at the (sub-)cellular level to the organ and body context (e. g., ECG), thereby providing a thorough understanding of this routinely used diagnostic tool that may translate into optimized applications.

Abstract:

OBJECTIVE: Atrial tachycardia (AT) still pose a major challenge in catheter ablation. Although state-of-the-art electroanatomical mapping systems allow to acquire several thousand intracardiac electrograms (EGMs), algorithms for diagnostic analysis are mainly limited to the amplitude of the signal (voltage map) and the local activation time~(LAT map). We applied spatio-temporal analysis of EGM activity to generate maps indicating reentries and diastolic potentials, thus identifying and localizing the driving mechanism of AT. METHODS: First, the time course of active surface area (ASA) is determined during one basic cycle length (BCL). The global cycle length coverage (gCLC) reflects the relative duration within one BCL for which activity was present in each individual atrium. A local cycle length coverage (lCLC) is computed for circular sub-areas with 20mm diameter. The simultaneous active surface area sASA is determined to indicate the spatial extent of depolarizing tissue. RESULTS: Combined analysis of these spatial scales allowed to correctly identify and localize the driving mechanism: gCLC values of 100% were indicative for atria harbouring a reentrant driver. lCLC could detect micro reentries within an area of 1.651.28cm in simulated data and differentiate them against focal sources. Mid-diastolic potentials, being potential targets for catheter ablation, were identified as the areas showing confined activity based on sASA values. CONCLUSION: The concept of spatio-temporal activity analysis proved successful and correctly indicated the tachycardia mechanism in 20 simulated AT scenarios and three clinical data sets. SIGNIFICANCE: Automatic interpretation of intracardiac mapping data could help to improve the treatment strategy in complex cases of AT.

Abstract:

Background: During atrial fibrillation, heterogeneities and anisotropies result in a chaotic propagation of the depolarization wavefront. The electrophysiological parameter called conduction velocity (CV) influences the propagation pattern over the atrium. We present a method that determines the regional CV for deformed catheter shapes, which result due to the catheter movement and changing wall contact.Methods: The algorithm selects stable catheter positions, finds the local activation times (LAT), considers the wall contact and calculates all CV estimates within the area covered by the catheter. The method is evaluated with simulated data and then applied to four clinical data sets. Both sinus rhythm activity as well as depolarization wavefronts initiated by stimulation are analyzed. The regional CV is compared with the fractionation duration (FD) and peak-to-peak (P2P) voltages. A speed of 0.5 m/s was defined to create the simulated LAT.Results: After analyzing the simulated LAT with clinical catheter spatial coordinates, the median CV of 0.5 m/s with an interquartile range of 0.22 and exact CV direction vectors were obtained. For clinical cases, the CV magnitude range of 0.08 m/s to 1.0 m/s was obtained. The P2P amplitude of 0.7 mV to 3.7 mV and the mean FD from 40.79ms to 48.66ms was obtained. The correlation of 0.86 was observed between CV and P2P amplitude, and 0.62 between CV and FD.Conclusion: In this paper, a method is presented and validated which calculates the CV for the deformed catheter and changing wall contact. In an exemplary clinical data set correlation between regional CV with FD and the P2P voltage was observed.

Abstract:

AIMS: To test the ability of four circulating biomarkers of fibrosis, and of low left atrial voltage, to predict recurrence of atrial fibrillation after catheter ablation. BACKGROUND: Circulating biomarkers potentially may be used to improve patient selection for atrial fibrillation ablation. Low voltage areas in the left atrium predict arrhythmia recurrence when mapped in sinus rhythm. This study tested type III procollagen N terminal peptide (PIIINP), galectin-3 (gal-3), fibroblast growth factor 23 (FGF-23), and type I collagen C terminal telopeptide (ICTP), and whether low voltage areas in the left atrium predicted atrial fibrillation recurrence, irrespective of the rhythm during mapping. METHODS: 92 atrial fibrillation ablation patients were studied. Biomarker levels in peripheral and intra-cardiac blood were measured with enzyme-linked immunosorbent assay. Low voltage (<0.5mV) was expressed as a proportion of the mapped left atrial surface area. Follow-up was one year. The primary endpoint was recurrence of arrhythmia. The secondary endpoint was a composite of recurrence despite two procedures, or after one procedure if no second procedure was undertaken. RESULTS: The biomarkers were not predictive of either endpoint. After multivariate Cox regression analysis, high proportion of low voltage area in the left atrium was found to predict the primary endpoint in sinus rhythm mapping (hazard ratio 4.323, 95% confidence interval 1.337-13.982, p = 0.014) and atrial fibrillation mapping (hazard ratio 5.195, 95% confidence interval 1.032-26.141, p = 0.046). This effect was also apparent for the secondary endpoint. CONCLUSION: The studied biomarkers do not predict arrhythmia recurrence after catheter ablation. Left atrial voltage is an independent predictor of recurrence, whether the left atrium is mapped in atrial fibrillation or sinus rhythm.

Abstract:

Computational modeling is an important tool to advance our knowledge on cardiac diseases and their underlying mechanisms. Computational models of conduction in cardiac tissues require identification of parameters. Our knowledge on these parameters is limited, especially for diseased tissues. Here, we assessed and quantified parameters for computational modeling of conduction in cardiac tissues. We used a rabbit model of myocardial infarction (MI) and an imaging-based approach to derive the parameters. Left ventricular tissue samples were obtained from fixed control hearts (animals: 5) and infarcted hearts (animals: 6) within 200 μm (region 1), 250-750 μm (region 2) and 1,000-1,250 μm (region 3) of the MI border. We assessed extracellular space, fibroblasts, smooth muscle cells, nuclei and gap junctions by a multi-label staining protocol. With confocal microscopy we acquired three-dimensional (3D) image stacks with a voxel size of 200 × 200 × 200 nm. Image segmentation yielded 3D reconstructions of tissue microstructure, which were used to numerically derive extracellular conductivity tensors. Volume fractions of myocyte, extracellular, interlaminar cleft, vessel and fibroblast domains in control were (in %) 65.03 ± 3.60, 24.68 ± 3.05, 3.95 ± 4.84, 7.71 ± 2.15, and 2.48 ± 1.11, respectively. Volume fractions in regions 1 and 2 were different for myocyte, myofibroblast, vessel, and extracellular domains. Fibrosis, defined as increase in fibrotic tissue constituents, was (in %) 21.21 ± 1.73, 16.90 ± 9.86, and 3.58 ± 8.64 in MI regions 1, 2, and 3, respectively. For control tissues, image-based computation of longitudinal, transverse and normal extracellular conductivity yielded (in S/m) 0.36 ± 0.11, 0.17 ± 0.07, and 0.1 ± 0.06, respectively. Conductivities were markedly increased in regions 1 (+75, +171, and +100%), 2 (+53, +165, and +80%), and 3 (+42, +141, and +60%). Volume fractions of the extracellular space including interlaminar clefts strongly correlated with conductivities in control and MI hearts. Our study provides novel quantitative data for computational modeling of conduction in normal and MI hearts. Notably, our study introduces comprehensive statistical information on tissue composition and extracellular conductivities on a microscopic scale in the MI border zone. We suggest that the presented data fill a significant gap in modeling parameters and extend our foundation for computational modeling of cardiac conduction.

Abstract:

Objectives: This study hypothesized that P-wave morphology and timing under left atrial appendage (LAA) pacing change characteristically immediately upon anterior mitral line (AML) block. Background: Perimitral flutter commonly occurs following ablation of atrial fibrillation and can be cured by an AML. However, confirmation of bidirectional block can be challenging, especially in severely fibrotic atria. Methods: The study analyzed 129 consecutive patients (66 ± 8 years, 64% men) who developed perimitral flutter after atrial fibrillation ablation. We designed electrocardiography criteria in a retrospective cohort (n = 76) and analyzed them in a validation cohort (n = 53). Results: Bidirectional AML block was achieved in 110 (85%) patients. For ablation performed during LAA pacing without flutter (n = 52), we found a characteristic immediate V1 jump (increase in LAA stimulus to P-wave peak interval in lead V1) as a real-time marker of AML block (V1 jump ≥30 ms: sensitivity 95%, specificity 100%, positive predictive value 100%, negative predictive value 88%). As V1 jump is not applicable when block coincides with termination of flutter, absolute V1 delay was used as a criterion applicable in all cases (n = 129) with a delay of 203 ms indicating successful block (sensitivity 92%, specificity 84%, positive predictive value 90%, negative predictive value 87%). Furthermore, an initial negative P-wave portion in the inferior leads was observed, which was attenuated in case of additional cavotricuspid isthmus ablation. Computational P-wave simulations provide mechanistic confirmation of these findings for diverse ablation scenarios (pulmonary vein isolation ± AML ± roof line ± cavotricuspid isthmus ablation). Conclusions: V1 jump and V1 delay are novel real-time electrocardiography criteria allowing fast and straightforward assessment of AML block during ablation for perimitral flutter.

Abstract:

Catheter ablation is a curative therapeutic approach for atrial fibrillation (AF). Ablation of rotational sources based on basket catheter measurements has been proposed as a promising approach in patients with persistent AF to complement pulmonary vein isolation. However, clinically reported success rates are equivocal calling for a mechanistic investigation under controlled conditions. We present a computational framework to benchmark ablation strategies considering the whole cycle from excitation propagation to electrogram acquisition and processing to virtual therapy. Fibrillation was induced in a patient-specific 3D volumetric model of the left atrium, which was homogeneously remodelled to sustain reentry. The resulting extracellular potential field was sampled using models of grid catheters as well as realistically deformed basket catheters considering the specific atrial anatomy. Virtual electrograms were processed to compute phase singularity density maps to target rotor tips with up to three circular ablations. Stable rotors were successfully induced in different regions of the homogeneously remodelled atrium showing that rotors are not constrained to unique anatomical structures or locations. Phase singularity density maps correctly identified and located the rotors (deviation < 10 mm) based on catheter recordings only for sufficient resolution (inter-electrode distance = 3 mm) and proximity to the wall (< 10 mm). Targeting rotor sites with ablation did not stop reentries in the homogeneously remodelled atria independent from lesion size (1-7 mm radius), from linearly connecting lesions with anatomical obstacles, and from the number of rotors targeted sequentially (up to 3). Our results show that phase maps derived from intracardiac electrograms can be a powerful tool to map atrial activation patterns, yet they can also be misleading due to inaccurate localization of rotor tips depending on electrode resolution and distance to the wall. This should be considered to avoid ablating regions that are in fact free of rotor sources of AF. In our experience, ablation of rotor sites was not successful to stop fibrillation. Our comprehensive simulation framework provides the means to holistically benchmark ablation strategies in silico under consideration of all steps invol

Abstract:

Patients suffering from end stage of chronic kid- ney disease (CKD) often undergo haemodialysis to normalize the electrolyte concentrations. Moreover, cardiovascular disease (CVD) is the main cause of death in CKD patients. To study the connection between CKD and CVD, we investi- gated the effects of an electrolyte variation on cardiac signals (action potential and ECG) using a computational model. In a first step, simulations with the Himeno et al. ventricular cell model were performed on cellular level with different extra- cellular sodium ([Na+]o), calcium ([Ca2+]o) and potassium ([K+]o) concentrations as occurs in CKD patients. [Ca2+]o and [K+]o changes caused variations in different features describ- ing the morphology of the AP. Changes due to a [Na+]o varia- tion were not as prominent. Simulations with [Ca2+]o varia- tions were also carried out on ventricular ECG level and a 12-lead ECG was computed. Thus, a multiscale simulator from ion channel to ECG reproducing the calcium-dependent inactivation of ICaL was achieved. The results on cellular and ventricular level agree with results from literature. Moreover, we suggest novel features representing electrolyte changes that have not been described in literature. These results could be helpful for further studies aiming at the estimation of ionic concentrations based on ECG recordings.

Abstract:

Multi-scale computational modeling of cardiac electrophysiology has fostered our understanding of the genesis of the ECG. While current models capture the relevant processes under physiological and many disease conditions with high fidelity, proper representation of the conditions in the extracellular milieu remains challenging. The recent human ventricular myocyte model by Himeno et al. is one of the first biophysical models which faithfully represents the dependence of the action potential (AP) duration on the extracellular calcium concentration ([Ca2+]o). Here, we present a heterogeneous formulation of the Himeno et al. cellular model and integrate it into a multi-scale framework to compute body surface ECGs. We propose three variants of the Himeno et al. model to account for transmural heterogeneity. The ionic current level parameter sets representing subendocardial, M, and subepicardial cell types were informed by the experimental data presented with the O’Hara-Rudy model and tuned to match AP level features such as repolarization stability. As shown in a previous work by Keller et al., an apico-basal gradient of IKs conductance is a likely mechanism causing concordant T-waves. Therefore, we increased the IKs conductance in the Himeno et al. model at the apex by a factor of 3.5 compared to the base to obtain an APD shortening of 12.5%. The model setup comprising transmural and apico-basal heterogeneity yielded a physiological ventricular ECG comparable to previous setups building on the ten Tusscher et al. cellular model. Our novel setup allows to study, for the first time, how realistic changes of the AP under hypo- and hypercalcaemic conditions translate to changes in the ECG. Resulting QT prolongation under hypocalcaemic conditions quantitatively matched human experimental data. In conclusion, the setup presented here provides a tool to study the effect of altered calcium levels in the extracellular milieu of the heart, as e. g. occurring during renal failure, across multiple spatial scales mechanistically.

Abstract:

The Purkinje system is part of the fast-conducting ventricular excitation system. The anatomy of the Purkinje system varies from person to person and imposes a unique excitation pattern on the ventricular myocardium, which defines the morphology of the QRS complex of the ECG to a large degree. While it cannot be imaged in-vivo, it plays an important role for personalizing computer simulations of cardiac electrophysiology. Here, we present a new method to automatically model and customize the Purkinje system based on the measured electrocardiogram (ECG) of a patient. A graphbased algorithm was developed to generate Purkinje systems based on the parameters fibre density, minimal distance from the atrium, conduction velocity, and position and timing of excitation sources mimicking the bundle branches. Based on the resulting stimulation profile, the activation times of the ventricles were calculated using the fast marching approach. Predescribed action potentials and a finite element lead field matrix were employed to obtain surface ECG signals. The root mean square error (RMSE) between the simulated and measured QRS complexes of the ECGs was used as cost function to perform optimization of the Purkinje parameters. One complete evaluation from Purkinje tree generation to the simulated ECG could be computed in about 10 seconds on a standard desktop computer. The measured ECG of the patient used to build the anatomical model was matched via parallel simplex optimization with a remaining RMSE of 4.05 mV in about 16 hours. The approach presented here allows to tailor the structure of the Purkinje system through the measured ECG in a patient-specific way. The computationally efficient implementation facilitates global optimization.

Abstract:

This study examines the effect of mental workload on the electrocardiogram (ECG) of participants driving the Lane Change Task (LCT). Different levels of mental workload were induced by a secondary task (n-back task) with three levels of difficulty. Subjective data showed a significant increase of the experienced workload over all three levels. An exploratory approach was chosen to extract a large number of rhythmical and morphological features from the ECG signal thereby identifying those which differentiated best between the levels of mental workload. No single rhythmical or morphological feature was able to differentiate between all three levels. A group of parameters were extracted which were at least able to discriminate between two levels. For future research, a combination of features is recommended to achieve best diagnosticity for different levels of mental workload.

Abstract:

Heart rate variability (HRV) plays an important role in medicine and psychology because it is used to quantify imbalances of the autonomic nervous system (ANS). An important manifestations of the ANS on HRV is also directly related to respiration and it is called respiratory sinus arrhythmia (RSA). This is a controlled phenomenon that leads to a synchronized coupling between respiration and instantaneous heart rate. Thus, the portion of HRV that is not related to respiration, and could potentially contain undiscovered diagnostic value, is overlapped and remains hidden in a standard HRV analysis. In such cases, a decoupling procedure would deliver a discriminated HRV analysis and possible new insights about the regulation of the cardiovascular system. In this work, we propose an algorithm based on Granger's causality to measure coupling between respiration and HRV. In the case of significant coupling, we estimate and cancel the respiration driven HRV component using a linear filtering approach. We tested the method using synthetic signals and prove it to deliver a reliable coupling measurement in 96.3% of the cases and reconstruct respiration free signals with a median correlation coefficient of 0.992. Afterwards, we applied our method to signals recorded during paced respiration and during natural breathing. We demonstrated that coupling is dependent on respiratory frequency and that it maximizes at 0.3 Hz. Furthermore, the HRV parameters measured during paced respiration tend to level among subjects after decoupling. The intersubject variability of HRV parameter is also decreased after the separation process. During natural breathing, coupling is notoriously lower to non-existing and decoupling has little impact on HRV. We conclude that the method proposed here can be used to investigate the diagnostic value of respiration independent HRV parameters.

Abstract:

The most important ECG marker for the diagnosis of ischemia or infarction is a change in the ST segment. Baseline wander is a typical artifact that corrupts the recorded ECG and can hinder the correct diagnosis of such diseases. For the purpose of finding the best suited filter for the removal of baseline wander, the ground truth about the ST change prior to the corrupting artifact and the subsequent filtering process is needed. In order to create the desired reference, we used a large simulation study that allowed us to represent the ischemic heart at a multiscale level from the cardiac myocyte to the surface ECG. We also created a realistic model of baseline wander to evaluate five filtering techniques commonly used in literature. In the simulation study, we included a total of 5.5 million signals coming from 765 electrophysiological setups. We found that the best performing method was the wavelet-based baseline cancellation. However, for medical applications, the Butterworth high-pass filter is the better choice because it is computationally cheap and almost as accurate. Even though all methods modify the ST segment up to some extent, they were all proved to be better than leaving baseline wander unfiltered.

Abstract:

Radiofrequency ablation has become a first-line approach for curative therapy of many cardiac arrhythmias. Various existing catheter designs provide high spatial resolution to identify the best spot for performing ablation and to assess lesion formation. However, creation of transmural and nonconducting ablation lesions requires usage of catheters with larger electrodes and improved thermal conductivity, leading to reduced spatial sensitivity. As trade-off, an ablation catheter with integrated mini electrodes was introduced. The additional diagnostic benefit of this catheter is still not clear. In order to solve this issue, we implemented a computational setup with different ablation scenarios. Our in silico results show that peak-to-peak amplitudes of unipolar electrograms from mini electrodes are more suitable to differentiate ablated and nonablated tissue compared to electrograms from the distal ablation electrode. However, in orthogonal mapping position, no significant difference was observed between distal electrode and mini electrodes electrograms in the ablation scenarios. In conclusion, catheters with mini electrodes bring about additional benefit to distinguish ablated tissue from nonablated tissue in parallel position with high spatial resolution. It is feasible to detect conduction gaps in linear lesions with this catheter by evaluating electrogram data from mini electrodes.

Abstract:

In den Lebenswissenschaften ist die Individualisierte Medizin aktuell ein zentrales Thema, vielleicht ein Hype. Das bestätigen auch synonyme, erweiternde und klärende Begriffe wie Personalisierte Medizin, Customized Medicine, Stratifizierende Medizin oder Präzisionsmedizin. In einer State of the Union Address an die Bevölkerung der Vereinigten Staaten von Amerika hat Präsident Barack Obama 2015 die Bedeutung der Präzisionsmedizin hervorgehoben [1]. Diese Initiative wurde inhaltlich wesentlich vom Direktor des National Institute of Health, dem Genetiker Francis Collins, vorangetrieben [2]. Individualisierte Medizin, das ist eine gute Botschaft, betont sie doch die Wertigkeit des einzelnen Patienten. Für klinisch tätige Ärzte ist das bereits eine Selbstverständlichkeit. Die Bedeutung eines Wortes, und das sei mit einem Lächeln hinzugefügt, zeigt sich nach Wittgenstein im Gebrauch der Sprache [3].Die Nationale Akademie der Wissenschaften Leopoldina, die acatech Deutsche Akademie der Technikwissenschaften und die Union der Deutschen Akademien der Wissenschaften haben im Dezember 2014 eine Stellungnahme über Voraussetzungen und Konsequenzen der Individualisierten Medizin publiziert. Darin wird der Fokus, wie im Vorwort ausgeführt, auf molekulare, genetische und pharmakologische Aspekte der Onkologie gelegt, einen Bereich, in dem die Individualisierung am weitesten fortgeschritten ist. Diese Beschränkung bedeutet, dass andere eng assoziierte Themen, wie die Patienten- und Versorgungsperspektiven, der Bereich der Medizintechnik oder neue Erkrankungen, beispielsweise in der Psychiatrie, in dieser Studie nicht beleuchtet werden. Die Behandlung dieser Gebiete bedarf einer separaten nachfolgenden Betrachtung. [4].Vor einer Betrachtung wesentlicher Beiträge allein der Bildgebung in der Individualisierten Medizin seien wenige vorausschickende Bemerkungen zu zwei Grenz-Fragen der Wissenschaft gemacht. Was steht für und gegen Stellungnahmen der genannten Akademien? Erfüllt die Beschäftigung mit der Bildgebung Kriterien der Wissenschaft?Eine der Aufgaben der Akademien ist es, Ordnung in die vorhandenen Aussagen und auch damit vorhandene Daten zu bringen, die in unterschiedlichen Disziplinen hervorgebracht werden, um daraus ein Gesamtbild zu formen. Weiterhin sollen Empfehlungen gegeben werden, wie die Entwicklungen günstig zu beeinflussen sind [5]. Wichtige Grenzen der wissenschaftlichen Politik- bzw. Gesellschaftsberatung bilden etwa Katastrophenwarnungen und Heilsverheißungen, andererseits nicht-altruistische, sondern dem Eigeninteresse dienende, wie auch politisierende Verlautbarungen. Das setzt eine Selbstbegrenzung voraus.Wünschenswert ist bei wissenschaftlichem Handeln der Respekt von und vor Grenzen, ist die Distanz zur Macht. Diese Macht kann der Politik, der Ökonomie und auch den Medien zugeschrieben werden; fatal sind Nähe oder gar Einfluss von Ideologien. Dabei wird nicht nur ein behutsamer Umgang mit Empfehlungen angesprochen; im wissenschaftlichen Handeln sind gerade beim Gegenstand der Bildgebung Berührungen mit der und sogar Überlappungen mit Interessen der Industrie möglich, teilweise gewünscht und fruchtbar. Letztlich ist es ja immer die Industrialisierung, die medizinischen Fortschritt, sei er pharmakologisch oder technologisch abbildbar, breiten Bevölkerungsgruppen und entlegenen Standorten zugänglich macht. Das bedarf immer einer gegenseitigen kritischen Begleitung.Die Wissenschaft dient dem Erkenntnisgewinn. Dazu gehört eine methodische Suche nach Wahrheit, die alle Befähigten überprüfen und nachvollziehen können. Wenn dieses angenommen, akzeptiert werden kann, dann sind die Technikwissenschaften Wissenschaften, dann betreiben Radiologie und Nuklearmedizin Wissenschaft (science). Dann bedarf es nicht der Aufzählung von Nobelpreisen oder ähnlichen Anerkennungen in der Scientific Community. Dann bedarf es nicht der Aufzählung fachlicher Beispiele; die Methoden und die Technologien fallen nicht vom Himmel. Wissenschaft wird von Menschen betrieben und getragen. An Pioniere der Bildgebung, an Personen, wie Wilhelm Conrad Röntgen, Marie Curie, Godfrey Hounsfield, Peter Mansfield, Paul Lauterbur oder Stephan Hell sei erinnert.* Dieses Editorial wird zeitgleich in Nuklearmedizin publiziert. Schober O, Dössel O, Ermert H et al. Bildgebung in Klinik und Forschung: Beitrag zur Individualisierten Medizin? Nuklearmedizin 2017; 56: 157-161; https://doi.org/10.3413/2017-05-0002.

Abstract:

Electrocardiographic imaging (ECGI) has recently gained attention as a viable diagnostic tool for reconstructing cardiac electrical activity in normal hearts as well as in cardiac arrhythmias. However, progress has been limited by the lack of both standards and unbiased comparisons of approaches and techniques across the community, as well as the consequent difficulty of effective collaboration across research groups.. To address these limitations, we created the Consortium for Electrocardiographic Imaging (CEI), with the objective of facilitating collaboration across the research community in ECGI and creating standards for comparisons and reproducibility. Here we introduce CEI and describe its two main efforts, the creation of EDGAR, a public data repository, and the organization of three collaborative workgroups that address key components and applications in ECGI. Both EDGAR and the workgroups will facilitate the sharing of ideas, data and methods across the ECGI community and thus address the current lack of reproducibility, broad collaboration, and unbiased comparisons.

Abstract:

Cardiologists measure electric signals inside the human heart aiming at a better diagnosis and optimized therapy of atrial arrhythmias like atrial flutter and atrial fibrillation. The catheters that are used for this purpose are improving: now they are able to pick up the electric signals at up to 64 positions inside the heart simultaneously. The patterns of electric depolarization are sometimes very simple, comparable to plane waves. But in case of patients with severe atrial arrhythmias they can be quite complex: U-turns around a line of block, ectopic centres, break throughs, reentry circuits, rotors, fractionated signals and chaotic patterns are often observed. Methods of biosignal analysis can support the cardiologists in classifying the signals and extract information of high diagnostic relevance. Computer models of the electrophysiology of the human heart can serve to design better algorithms for data analysis and to test algorithms, because the ground truth is known.

Abstract:

Robust and exact automatic P wave detection and delineation in the electrocardiogram (ECG) is still an interesting but challenging research topic. The early prognosis of cardiac afflictions such as atrial fibrillation and the response of a patient to a given treatment is believed to improve if the P wave is carefully analyzed during sinus rhythm. Manual annotation of the signals is a tedious and subjective task. Its correctness depends on the experience of the annotator, quality of the signal, and ECG lead. In this work, we present a wavelet-based algorithm to detect and delineate P waves in individual ECG leads. We evaluated a large group of commonly used wavelets and frequency bands (wavelet levels) and introduced a special phase free wavelet transformation. The local extrema of the transformed signals are directly related to the delineating points of the P wave. First, the algorithm was studied using synthetic signals. Then, the optimal parameter configuration was found using intracardiac electrograms and surface ECGs measured simultaneously. The reverse biorthogonal wavelet 3.3 was found to be optimal for this application. In the end, the method was validated using the QT database from PhysioNet. We showed that the algorithm works more accurately and more robustly than other methods presented in literature. The validation study delivered an average delineation error of the P wave onset of -0.32+/-12.41 ms when compared to manual annotations. In conclusion, the algorithm is suitable for handling varying P wave shapes and low signal-to-noise ratios.

Abstract:

AIMS: P-wave morphology correlates with the risk for atrial fibrillation (AF). Left atrial (LA) enlargement could explain both the higher risk for AF and higher P-wave terminal force (PTF) in lead V1. However, PTF-V1 has been shown to correlate poorly with LA size. We hypothesize that PTF-V1 is also affected by the earliest activated site (EAS) in the right atrium and its proximity to inter-atrial connections (IAC), which both show tremendous variability. METHODS AND RESULTS: Atrial excitation was triggered from seven different EAS in a cohort of eight anatomically personalized computational models. The posterior IACs were non-conductive in a second set of simulations. Body surface ECGs were computed and separated by left and right atrial contributions. Mid-septal EAS yielded the highest PTF-V1. More anterior/superior and more inferior EAS yielded lower absolute PTF-V1 values deviating by a factor of up to 2.0 for adjacent EAS. Earliest right-to-left activation was conducted via Bachmann's Bundle (BB) for anterior/superior EAS and shifted towards posterior IACs for more inferior EAS. Non-conducting posterior IACs increased PTF-V1 by up to 150% compared to intact posterior IACs for inferior EAS. LA contribution to the P-wave integral was 24% on average. CONCLUSION: The electrical contributor's site of earliest activation and intactness of posterior IACs affect PTF-V1 significantly by changing LA breakthrough sites independent from LA size. This should be considered for interpretation of electrocardiographical signs of LA abnormality and LA enlargement.

Abstract:

Computational models of cardiac electrophysiology provided insights into arrhythmogenesis and paved the way toward tailored therapies in the last years. To fully leverage in silico models in future research, these models need to be adapted to reflect pathologies, genetic alterations, or pharmacological effects, however. A common approach is to leave the structure of established models unaltered and estimate the values of a set of parameters. Today's high-throughput patch clamp data acquisition methods require robust, unsupervised algorithms that estimate parameters both accurately and reliably. In this work, two classes of optimization approaches are evaluated: gradient-based trust-region-reflective and derivative-free particle swarm algorithms. Using synthetic input data and different ion current formulations from the Courtemanche et al. electrophysiological model of human atrial myocytes, we show that neither of the two schemes alone succeeds to meet all requirements. Sequential combination of the two algorithms did improve the performance to some extent but not satisfactorily. Thus, we propose a novel hybrid approach coupling the two algorithms in each iteration. This hybrid approach yielded very accurate estimates with minimal dependency on the initial guess using synthetic input data for which a ground truth parameter set exists. When applied to measured data, the hybrid approach yielded the best fit, again with minimal variation. Using the proposed algorithm, a single run is sufficient to estimate the parameters. The degree of superiority over the other investigated algorithms in terms of accuracy and robustness depended on the type of current. In contrast to the non-hybrid approaches, the proposed method proved to be optimal for data of arbitrary signal to noise ratio. The hybrid algorithm proposed in this work provides an important tool to integrate experimental data into computational models both accurately and robustly allowing to assess the often non-intuitive consequences of ion channel-level changes on higher levels of integration.

Abstract:

BACKGROUND AND OBJECTIVE: Progress in biomedical engineering has improved the hardware available for diagnosis and treatment of cardiac arrhythmias. But although huge amounts of intracardiac electrograms (EGMs) can be acquired during electrophysiological examinations, there is still a lack of software aiding diagnosis. The development of novel algorithms for the automated analysis of EGMs has proven difficult, due to the highly interdisciplinary nature of this task and hampered data access in clinical systems. Thus we developed a software platform, which allows rapid implementation of new algorithms, verification of their functionality and suitable visualization for discussion in the clinical environment. METHODS: A software for visualization was developed in Qt5 and C++ utilizing the class library of VTK. The algorithms for signal analysis were implemented in MATLAB. Clinical data for analysis was exported from electroanatomical mapping systems. RESULTS: The visualization software KaPAVIE (Karlsruhe Platform for Analysis and Visualization of Intracardiac Electrograms) was implemented and tested on several clinical datasets. Both common and novel algorithms were implemented which address important clinical questions in diagnosis of different arrhythmias. It proved useful in discussions with clinicians due to its interactive and user-friendly design. Time after export from the clinical mapping system to visualization is below 5min. CONCLUSION: KaPAVIE(2) is a powerful platform for the development of novel algorithms in the clinical environment. Simultaneous and interactive visualization of measured EGM data and the results of analysis will aid diagnosis and help understanding the underlying mechanisms of complex arrhythmias like atrial fibrillation.

Abstract:

Whole-chamber mapping using a 64-pole basket catheter (BC) has become a featured approach for the analysis of excitation patterns during atrial fibrillation. A flexible catheter design avoids perforation but may lead to spline bunching and influence coverage. We aim to quantify the catheter deformation and endocardial coverage in clinical situations and study the effect of catheter size and electrode arrangement using an in silico basket model. Atrial coverage and spline separation were evaluated quantitatively in an ensemble of clinical measurements. A computational model of the BC was implemented including an algorithm to adapt its shape to the atrial anatomy. Two clinically relevant mapping positions in each atrium were assessed in both clinical and simulated data. The simulation environment allowed varying both BC size and electrode arrangement. Results showed that interspline distances of more than 20&#8201;mm are common, leading to a coverage of less than 50% of the left atrial (LA) surface. In an ideal in silico scenario with variable catheter designs, a maximum coverage of 65% could be reached. As spline bunching and insufficient coverage can hardly be avoided, this has to be taken into account for interpretation of excitation patterns and development of new panoramic mapping techniques.

Abstract:

Noninvasive reconstruction of cardiac electrical activity has a great potential to support clinical decision making, planning and treatment. Recently, significant progress has been made in the estimation of the cardiac activation from body surface potential maps (BSPMs) using boundary element method (BEM) with the equivalent double layer (EDL) as source model. In this formulation, noninvasive assessment of activation times results in a nonlinear optimization problem with an initial estimate calculated with the fastest route algorithm (FRA). Each FRAsimulated activation sequence is converted into the ECG. The best initialization is determined by the sequence providing the highest correlation between predicted and measured potentials.We quantitatively assess the effects of the forward modeling errors on the FRA-based initialization. We present three simulation setups to investigate the effects of volume conductor model simplifications, neglecting the cardiac anisotropy and geometrical errors on the localization of ectopic beats starting on the ventricular surface. For the analysis, 12-lead ECG and 99 electrodes BSPM system were used. The areas in the heart exposing the largest localization errors were volume conductor model and electrode configuration specific with an average error <10 mm. The results show the robustness of the FRA-based initialization with respect to the considered modeling errors.

Abstract:

ECG imaging is an emerging technology for the reconstruction of cardiac electric activity from non-invasively measured body surface potential maps. In this case report, we present the first evaluation of transmurally imaged activation times against endocardially reconstructed isochrones for a case of sustained monomorphic ventricular tachycardia (VT). Computer models of the thorax and whole heart were produced from MR images. A recently published approach was applied to facilitate electrode localization in the catheter laboratory, which allows for the acquisition of body surface potential maps while performing non-contact mapping for the reconstruction of local activation times. ECG imaging was then realized using Tikhonov regularization with spatio-temporal smoothing as proposed by Huiskamp and Greensite and further with the spline-based approach by Erem et al. Activation times were computed from transmurally reconstructed transmembrane voltages. The results showed good qualitative agreement between the non-invasively and invasively reconstructed activation times. Also, low amplitudes in the imaged transmembrane voltages were found to correlate with volumes of scar and grey zone in delayed gadolinium enhancement cardiac MR. The study underlines the ability of ECG imaging to produce activation times of ventricular electric activity-and to represent effects of scar tissue in the imaged transmembrane voltages.

Abstract:

Microstructural characterization of cardiac tissue and its remodeling in disease is a crucial step in many basic research projects. We present a comprehensive approach for three-dimensional characterization of cardiac tissue at the submicrometer scale. We developed a compression-free mounting method as well as labeling and imaging protocols that facilitate acquisition of three-dimensional image stacks with scanning confocal microscopy. We evaluated the approach with normal and infarcted ventricular tissue. We used the acquired image stacks for segmentation, quantitative analysis and visualization of important tissue components. In contrast to conventional mounting, compression-free mounting preserved cell shapes, capillary lumens and extracellular laminas. Furthermore, the new approach and imaging protocols resulted in high signal-to-noise ratios at depths up to 60 microm. This allowed extensive analyzes revealing major differences in volume fractions and distribution of cardiomyocytes, blood vessels, fibroblasts, myofibroblasts and extracellular space in control vs. infarct border zone. Our results show that the developed approach yields comprehensive data on microstructure of cardiac tissue and its remodeling in disease. In contrast to other approaches, it allows quantitative assessment of all major tissue components. Furthermore, we suggest that the approach will provide important data for physiological models of cardiac tissue at the submicrometer scale.

Abstract:

One promising application of electrocardiographic (ECG) imaging is noninvasive reconstruction of atrial activities. However, despite numerous clinical studies, which are mostly concerned with complex irregular excitation patterns, there are relatively few in silico investigations on the imaging of ectopic activation. In the present work, we explore the localization accuracy of ECG imaging regarding atrial focal sites. For the forward calculations, we used four realistic geometrical models with complex anatomical structure and a rule-based fiber orientation embedded into the atrial model. Excitation propagation was simulated with the monodomain model. For each geometrical model, 20 activation sequences originating from the posterior wall of the left atrium were simulated. Based on the bidomain theory, the body surface potential maps resulting from these focal events were computed. For the inverse reconstructions, we employed a full-search procedure based on the fastest route algorithm assuming uniform excitation propagation. Localization errors were revealed to be dependent on the model-specific atrial geometry. We also performed similarity analysis for the first halves of the P wave duration, which improved the results in three models.

Abstract:

INTRODUCTION: The "Experimental Data and Geometric Analysis Repository", or EDGAR is an Internet-based archive of curated data that are freely distributed to the international research community for the application and validation of electrocardiographic imaging (ECGI) techniques. The EDGAR project is a collaborative effort by the Consortium for ECG Imaging (CEI, ecg-imaging.org), and focused on two specific aims. One aim is to host an online repository that provides access to a wide spectrum of data, and the second aim is to provide a standard information format for the exchange of these diverse datasets. METHODS: The EDGAR system is composed of two interrelated components: 1) a metadata model, which includes a set of descriptive parameters and information, time signals from both the cardiac source and body-surface, and extensive geometric information, including images, geometric models, and measure locations used during the data acquisition/generation; and 2) a web interface. This web interface provides efficient, search, browsing, and retrieval of data from the repository. RESULTS: An aggregation of experimental, clinical and simulation data from various centers is being made available through the EDGAR project including experimental data from animal studies provided by the University of Utah (USA), clinical data from multiple human subjects provided by the Charles University Hospital (Czech Republic), and computer simulation data provided by the Karlsruhe Institute of Technology (Germany). CONCLUSIONS: It is our hope that EDGAR will serve as a communal forum for sharing and distribution of cardiac electrophysiology data and geometric models for use in ECGI research.

Abstract:

The interaction of spiral waves of excitation with atrial anatomy remains unclear. This simulation study isolates the role of atrial anatomical structures on spiral wave spontaneous drift in the human atrium. We implemented realistic and idealised 3D human atria models to investigate the functional impact of anatomical structures on the long-term ( approximately 40 s) behaviour of spiral waves. The drift of a spiral wave was quantified by tracing its tip trajectory, which was correlated to atrial anatomical features. The interaction of spiral waves with the following idealised geometries was investigated: (a) a wedge-like structure with a continuously varying atrial wall thickness; (b) a ridge-like structure with a sudden change in atrial wall thickness; (c) multiple bridge-like structures consisting of a bridge connected to the atrial wall. Spiral waves drifted from thicker to thinner regions and along ridge-like structures. Breakthrough patterns caused by pectinate muscles (PM) bridges were also observed, albeit infrequently. Apparent anchoring close to PM-atrial wall junctions was observed. These observations were similar in both the realistic and the idealised models. We conclude that spatially altering atrial wall thickness is a significant cause of drift of spiral waves. PM bridges cause breakthrough patterns and induce transient anchoring of spiral waves.

Abstract:

Models of cardiac mechanics are increasingly used to investigate cardiac physiology. These models are characterized by a high level of complexity, including the particular anisotropic material properties of biological tissue and the actively contracting material. A large number of independent simulation codes have been developed, but a consistent way of verifying the accuracy and replicability of simulations is lacking. To aid in the verification of current and future cardiac mechanics solvers, this study provides three benchmark problems for cardiac mechanics. These benchmark problems test the ability to accurately simulate pressure-type forces that depend on the deformed objects geometry, anisotropic and spatially varying material properties similar to those seen in the left ventricle and active contractile forces. The benchmark was solved by 11 different groups to generate consensus solutions, with typical differences in higher-resolution solutions at approximately 0.5%, and consistent results between linear, quadratic and cubic finite elements as well as different approaches to simulating incompressible materials. Online tools and solutions are made available to allow these tests to be effectively used in verification of future cardiac mechanics software.

Abstract:

Atrial fibrillation (AF) is the most common arrhythmia of the heart in industrialized countries. Its generation and the transitory behavior of paroxysmal AF are still not well understood. In this work we examine the interaction of two activation sources via an isthmus as possible cause for the initiation of fibrillation episodes. For this study, the electrophysiological model of Bueno-Orovio, Cherry and Fenton is adapted to atrial electrophysiology, both for physiological and electrophysiologically remodeled conditions due to AF. We show that the interaction of the pacemakers, combined with the geometrical constraints of the isthmus, can produce fibrillatory-type irregularities, which we quantify by the loss of spatial phase coherence in the transmembrane voltage. Transitions to irregular behavior occur when the frequencies of the pacemakers exceed certain thresholds, suggesting that AF episodes are initiated by frequency changes of the activating sources (sinus node, ectopic focus).

Abstract:

Background: Intracardiac electrograms are an indispensable part during diagnosis of supraventriculararrhythmias, but atrial activity (AA) can be obscured by ventricular far-fields (VFF). Concepts based onstatistical independence like principal component analysis (PCA) cannot be applied for VFF removalduring atrial tachycardia with stable conduction.Methods: A database of realistic electrograms containing AAand VFF was generated. Both PCA and thenew technique periodic component analysis (&#960;CA) were implemented, benchmarked, and applied toclinical data.Results: The concept of &#960;CA was successfully verified to retain compromised AA morphology,showing high correlation (cc = 0.98 ± 0.01) for stable atrial cycle length (ACL). Performance ofPCA failed during temporal coupling (cc = 0.03 ± 0.08) but improved for increasing conductionvariability (cc = 0.77 ± 0.14). Stability of ACL was identified as a critical parameter for &#960;CAapplication. Analysis of clinical data confirmed these findings.Conclusion: &#960;CA is introduced as a powerful new technique for artifact removal in periodic signals.Its concept and performance were benchmarked against PCA using simulated data and demonstratedon measured electrograms.

Abstract:

PURPOSE: To evaluate two commonly used respiratory motion correction techniques for coronary magnetic resonance angiography (MRA) regarding their dependency on motion estimation accuracy and final image quality and to compare both methods to the respiratory gating approach used in clinical practice. MATERIALS AND METHODS: Ten healthy volunteers were scanned using a non-Cartesian radial phase encoding acquisition. Respiratory motion was corrected for coronary MRA according to two motion correction techniques, image-based (IMC) and reconstruction-based (RMC) respiratory motion correction. Both motion correction approaches were compared quantitatively and qualitatively against a reference standard navigator-based respiratory gating (RG) approach. Quantitative comparisons were performed regarding visible vessel length, vessel sharpness, and total acquisition time. Two experts carried out a visual scoring of image quality. Additionally, numerical simulations were performed to evaluate the effect of motion estimation inaccuracy on RMC and IMC. RESULTS: RMC led to significantly better image quality than IMC (P's paired Student's t-test were smaller than 0.001 for vessel sharpness and visual scoring). RMC did not show a statistically significant difference compared to reference standard RG (vessel length [99% confidence interval]: 86.913 [83.097-95.015], P = 0.107; vessel sharpness: 0.640 [0.605-0.802], P = 0.012; visual scoring: 2.583 [2.410-3.424], P = 0.018) in terms of vessel visualization and image quality while reducing scan times by 56%. Simulations showed higher dependencies for RMC than for IMC on motion estimation inaccuracies. CONCLUSION: RMC provides a similar image quality as the clinically used RG approach but almost halves the scan time and is independent of subjects' breathing patterns. Clinical validation of RMC is now desirable. J. Magn. Reson. Imaging 2015.

Abstract:

Over the last decades, the information content derived from cardiac electric and magnetic field measurements has been debated. Our co-workers Wilhelms et al. inves- tigated electrically silent acute ischemia in human ven- tricles caused by occlusion of a coronary artery. In the present work, we extend the previous study by calculating associated magnetic fields produced by early stage acute ischemia with varying transmural extent. Multiscale com- putational simulations were performed for calculations of body surface potential maps (BSPM) and magnetocardio- grams (MCG) on a magnetometer sensor matrix situated above the anterior chest wall. Depending on the ischemia size, the ST-segments of the simulated electrocardiograms (ECG) experienced depression for subendocardial cases and elevation for transmural ischemia. One intermedi- ate extent resulted in a zero ST-segment which makes it diagnostically indistinguishable from the healthy case. Magnetic field calculations for this electrically silent is- chemia also revealed no difference compared to the control case. Otherwise, both ECG and MCG signals during ST- segments showed either depression or elevation from zero line. In this simulation study, MCG did not deliver addi- tional information to uncover electrically silent ischemia. For a general conclusion, further in-silico investigations with different ischemia shapes, sizes and positions should be performed and clinical studies with recordings of both ECG and MCG signals have to be conducted.

Abstract:

BACKGROUND: Considering the rates of sudden cardiac death (SCD) and pump failure death (PFD) in chronic heart failure (CHF) patients and the cost-effectiveness of their preventing treatments, identification of CHF patients at risk is an important challenge. In this work, we studied the prognostic performance of the combination of an index potentially related to dispersion of repolarization restitution (Deltaalpha), an index quantifying T-wave alternans (IAA) and the slope of heart rate turbulence (TS) for classification of SCD and PFD. METHODS: Holter ECG recordings of 597 CHF patients with sinus rhythm enrolled in the MUSIC study were analyzed and Deltaalpha, IAA and TS were obtained. A strategy was implemented using support vector machines (SVM) to classify patients in three groups: SCD victims, PFD victims and other patients (the latter including survivors and victims of non-cardiac causes). Cross-validation was used to evaluate the performance of the implemented classifier. RESULTS: Deltaalpha and IAA, dichotomized at 0.035 (dimensionless) and 3.73 muV, respectively, were the ECG markers most strongly associated with SCD, while TS, dichotomized at 2.5 ms/RR, was the index most strongly related to PFD. When separating SCD victims from the rest of patients, the individual marker with best performance was Deltaalpha>/=0.035, which, for a fixed specificity (Sp) of 90%, showed a sensitivity (Se) value of 10%, while the combination of Deltaalpha and IAA increased Se to 18%. For separation of PFD victims from the rest of patients, the best individual marker was TS </= 2.5 ms/RR, which, for Sp=90%, showed a Se of 26%, this value being lower than Se=34%, produced by the combination of Deltaalpha and TS. Furthermore, when performing SVM classification into the three reported groups, the optimal combination of risk markers led to a maximum Sp of 79% (Se=18%) for SCD and Sp of 81% (Se=14%) for PFD. CONCLUSIONS: The results shown in this work suggest that it is possible to efficiently discriminate SCD and PFD in a population of CHF patients using ECG-derived risk markers like Deltaalpha, TS and IAA.

Abstract:

Catheter ablation has emerged as an effective treatment strategy for atrial fibrillation (AF) in recent years. During AF, complex fractionated atrial electrograms (CFAE) can be recorded and are known to be a potential target for ablation. Automatic algorithms have been developed to simplify CFAE detection, but they are often based on a single descriptor or a set of descriptors in combination with sharp decision classifiers. However, these methods do not reflect the progressive transition between CFAE classes. The aim of this study was to develop an automatic classification algorithm, which combines the information of a complete set of descriptors and allows for progressive and transparent decisions. We designed a method to automatically analyze CFAE based on a set of descriptors representing various aspects, such as shape, amplitude and temporal characteristics. A fuzzy decision tree (FDT) was trained and evaluated on 429 predefined electrograms. CFAE were classified into four subgroups with a correct rate of 81+/-3%. Electrograms with continuous activity were detected with a correct rate of 100%. In addition, a percentage of certainty is given for each electrogram to enable a comprehensive and transparent decision. The proposed FDT is able to classify CFAE with respect to their progressive transition and may allow objective and reproducible CFAE interpretation for clinical use.

Abstract:

The fiber orientation in the atria has a significant contribution to the electrophysiologic behavior of the heart and to the genesis of arrhythmia. Atrial fiber orientation has a direct effect on excitation propagation, activation patterns and the P-wave. We present a rule-based algorithm that works robustly on different volumetric meshes composed of either isotropic hexahedra or arbitrary tetrahedra as well as on 3-dimensional triangular surface meshes in patient-specific geometric models. This method fosters the understanding of general pro-arrhythmic mechanisms and enhances patient-specific modeling approaches.

Abstract:

Electroencephalography (EEG) is a method to measure the electrical activity of brain signals by electrodes attached to the scalp at multiple locations. In this study we used the EEG signals of Alcoholic and Control subjects were obtained from Machine Learning repository according to the 10-20 International System. There were 29 subjects from control group and 29 from alcoholic comprising of electrodes from different brain lobes such as Central Lobe (C3, C4), Frontal (F3, F4, F7, F8), Occipital Lobe (O1, O2), Parietal Lobe (P3, P4), Temporal Lobe (T7) and Front Polar (Fp1, Fp2). In the first phase, the nonlinear complexity based features are computed such as Approximate Entropy, Sample Entropy and Wavelet Entropy. These features for each electrode are passed as input to the Machine Learning classifiers such as Multilayer Perceptron (MPL), K-nearest Neighbor (KNN) and LIB Support Vector Machine (SVM) to classify for alcoholic and control group. The highest accuracy was obtained using MLP of 98.22 % at electrode C3. Moreover, above 90% accuracy was obtained using MPL at electrode C3, C4, F7; KNN at electrodes C3, C4, F7 and LIB SVM at electrodes C3, C4, F7 where KNN gives highest accuracy of 97.67% at electrode C4 and LIB SVM an accuracy of 94.67 % at electrode F7. Secondly, the ensemble methods are employed such as Minimum, Maximum, Sum, Average, Product, Majority Vote, Bayes, Decision Template and Dempster Shefer Fusion. Using ensemble methods most electrodes depicted higher accuracy than individual classifier such as Electrode F4, Fp2, O1, O2 and T7. While electrode C3 the ensemble methods Moving Average, DT, DFT gives highest accuracy of 98.22% and at electrodes C4 Moving Average, Sum, Average, DT, DFT provided an accuracy of 97.11%.

Abstract:

AIMS: The clinical efficacy in preventing the recurrence of atrial fibrillation (AF) is higher for amiodarone than for dronedarone. Moreover, pharmacotherapy with these drugs is less successful in patients with remodelled substrate induced by chronic AF (cAF) and patients suffering from familial AF. To date, the reasons for these phenomena are only incompletely understood. We analyse the effects of the drugs in a computational model of atrial electrophysiology. METHODS AND RESULTS: The Courtemanche-Ramirez-Nattel model was adapted to represent cAF remodelled tissue and hERG mutations N588K and L532P. The pharmacodynamics of amiodarone and dronedarone were investigated with respect to their dose and heart rate dependence by evaluating 10 descriptors of action potential morphology and conduction properties. An arrhythmia score was computed based on a subset of these biomarkers and analysed regarding circadian variation of drug concentration and heart rate. Action potential alternans at high frequencies was observed over the whole dronedarone concentration range at high frequencies, while amiodarone caused alternans only in a narrow range. The total score of dronedarone reached critical values in most of the investigated dynamic scenarios, while amiodarone caused only minor score oscillations. Compared with the other substrates, cAF showed significantly different characteristics resulting in a lower amiodarone but higher dronedarone concentration yielding the lowest score. CONCLUSION: Significant differences exist in the frequency and concentration-dependent effects between amiodarone and dronedarone and between different atrial substrates. Our results provide possible explanations for the superior efficacy of amiodarone and may aid in the design of substrate-specific pharmacotherapy for AF.

Abstract:

Signals obtained from biological systems exhibit pronounced complexity. The patterns of change contain valu- able information about the dynamics of underlying control mechanism of the complex biological systems. Human gait is a complex process with multiple inputs and numerous outputs. Various complexity analysis tools have been proposed to extract information from human gait time series. In this study, we used recently developed threshold based symbolic entropy to compare the spontaneous output of the human locomotors system during constrained and metronomically paced walking protocols. For that purpose, stride interval time series of healthy subjects who walked for 1 h at normal, slow and fast rates under different conditions was transformed into symbol sequences. Normalized corrected Shannon entropy (NCSE) was computed from the symbol sequences of the stride inter- val time series. The findings indicated that the unprompted output of human locomotors system is more complex during unconstrained normal walking as compared with slow, fast or metronomically paced walking

Abstract:

During the contraction of the ventricles, the ventricles interact with the atria as well as with the pericardium and the surrounding tissue in which the heart is embedded. The atria are stretched, and the atrioventricular plane moves toward the apex. The atrioventricular plane displacement (AVPD) is considered to be a major contributor to the ventricular function, and a reduced AVPD is strongly related to heart failure. At the same time, the epicardium slides almost frictionlessly on the pericardium with permanent contact. Although the interaction between the ventricles, the atria and the pericardium plays an important role for the deformation of the heart, this aspect is usually not considered in computational models. In this work, we present an electromechanical model of the heart, which takes into account the interaction between ventricles, pericardium and atria and allows to reproduce the AVPD. To solve the contact problem of epicardium and pericardium, a contact handling algorithm based on penalty formulation was developed, which ensures frictionless and permanent contact. Two simulations of the ventricular contraction were conducted, one with contact handling of pericardium and heart and one without. In the simulation with contact handling, the atria were stretched during the contraction of the ventricles, while, due to the permanent contact with the pericardium, their volume increased. In contrast to that, in the simulations without pericardium, the atria were also stretched, but the change in the atrial volume was much smaller. Furthermore, the pericardium reduced the radial contraction of the ventricles and at the same time increased the AVPD.

Abstract:

Tracking the location of medical devices in interventional X-ray data solves different problems. For example the motion information of the devices is used to determine cardiac or respiratory motion during X-ray guided procedures or device features are used as landmarks to register images. In this publication an approach using a 3D deformable catheter model is presented and used to track a coronary sinus (CS) catheter in 3D plus time through a complete rotational angiography sequence. The benefits of using voxel based models with attenuation information for 2D/3D registration are investigated in comparison to binary catheter models. The 2D/3D registration of the model allows to extract a 3D catheter shape from every individual 2D projection. The tracking accuracy is evaluated on simulated and clinical rotational angiography data of the contrast enhanced left atrium. The quantitative evaluation of the experiments delivers an average registration accuracy for all catheter electrodes of 0.23 mm in 2D and 0.95 mm in 3D when using an attenuation model of the catheter. The overall tracking accuracy is lower when using binary catheter models.

Abstract:

Cardiac ablation procedures during electrophysiology interventions are performed under x-ray guidance with a C-arm imaging system. Some procedures require catheter navigation in complex anatomies like the left atrium. Navigation aids like 3D road maps and external tracking systems may be used to facilitate catheter navigation. As an alternative to external tracking a fully automatic method is presented here that enables the calculation of the 3D location of the ablation catheter from individual 2D x-ray projections. The method registers a high resolution, deformable 3D attenuation model of the catheter to a 2D x-ray projection. The 3D localization is based on the divergent beam projection of the catheter. On an individual projection, the catheter tip is detected in 2D by image filtering and a template matching method. The deformable 3D catheter model is adapted using the projection geometry provided by the C-arm system and 2D similarity measures for an accurate 2D/3D registration. Prior to the tracking and registration procedure, the deformable 3D attenuation model is automatically extracted from a separate 3D cone beam CT reconstruction of the device. The method can hence be applied to various cardiac ablation catheters. In a simulation study of a virtual ablation procedure with realistic background, noise, scatter and motion blur an average 3D registration accuracy of 3.8 mm is reached for the catheter tip. In this study four different types of ablation catheters were used. Experiments using measured C-arm fluoroscopy projections of a catheter in a RSD phantom deliver an average 3D accuracy of 4.5 mm.

Abstract:

Cardiac C-arm CT imaging delivers a tomographic region-of-interest reconstruction of the patient's heart during image guided catheter interventions. Due to the limited size of the flat detector a volume image is reconstructed, which is truncated in the cone-beam (along the patient axis) and the fan-beam (in the transaxial plane) direction. To practically address this local tomography problem correction methods, like projection extension, are available for first pass image reconstruction. For second pass correction methods, like metal artefact reduction, alternative correction schemes are required when the field of view is limited to a region-of-interest of the patient. In classical CT imaging metal artefacts are corrected by metal identification in a first volume reconstruction and generation of a corrected projection data set followed by a second reconstruction. This approach fails when the metal structures are located outside the reconstruction field of view. When a C-arm CT is performed during a cardiac intervention pacing leads and other cables are frequently positioned on the patients skin, which results in propagating streak artefacts in the reconstruction volume. A first pass approach to reduce this type of artefact is introduced and evaluated here. It makes use of the fact that the projected position of objects outside the reconstruction volume changes with the projection perspective. It is shown that projection based identification, tracking and removal of high contrast structures like cables, only detected in a subset of the projections, delivers a more consistent reconstruction volume with reduced artefact level. The method is quantitatively evaluated based on 50 simulations using cardiac CT data sets with variable cable positioning. These data sets are forward projected using a C-arm CT system geometry and generate artefacts comparable to those observed in clinical cardiac C-arm CT acquisitions. A C-arm CT simulation of every cardiac CT data set without cables served as a ground truth. The 3D root mean square deviation between the simulated data set with and without cables could be reduced for 96% of the simulated cases by an average of 37% (min -9%, max 73%) when using the first pass correction method. In addition, image quality improvement is demonstrated for clinical whole heart C-arm CT data sets when the cable removal algorithm was applied.

Abstract:

Radiofrequency ablation (RFA) therapy is the gold standard in interventional treatment of many cardiac arrhythmias. A major obstacle are non transmural lesions, leading to recurrence of arrhythmias. Recent clinical studies have suggested intracardiac electrogram (EGM) criteria as a promising marker to evaluate lesion development. Seeking for a deeper understanding of underlying mechanisms, we established a simulation approach for acute RFA lesions. Ablation lesions were modeled by a passive necrotic core surrounded by a borderzone with properties of heated myocardium. Herein, conduction velocity and electrophysiological properties were altered. We simulated EGMs during RFA to study the relation between lesion formation and EGM changes using the bidomain model. Simulations were performed on a three dimensional setup including a geometrically detailed representation of the catheter with highly conductive electrodes. For validation, EGMs recorded during RFA procedures in five patients were analyzed and compared to simulation results. Clinical data showed major changes in the distal unipolar EGM. During RFA, the negative peak amplitude decreased up to 104% and maximum negative deflection was up to 88% smaller at the end of the ablation sequence. These changes mainly occurred in the first 10 s after ablation onset. Simulated unipolar EGM reproduced the clinical changes, reaching up to 83% negative peak amplitude reduction and 80% decrease in maximum negative deflection for transmural lesions. In future work, the established model may enable the development of further EGM criteria for transmural lesions even for complex geometries in order to support clinical therapy.

Abstract:

Chronic atrial fibrillation (AF) is a complex disease with underlying changes in electrophysiology, calcium signaling and the structure of atrial myocytes. How these individual remodeling targets and their emergent interactions contribute to cell physiology in chronic AF is not well understood. To approach this problem, we performed in silico experiments in a computational model of the human atrial myocyte. The remodeled function of cellular components was based on a broad literature review of in vitro findings in chronic AF, and these were integrated into the model to define a cohort of virtual cells. Simulation results indicate that while the altered function of calcium and potassium ion channels alone causes a pronounced decrease in action potential duration, remodeling of intracellular calcium handling also has a substantial impact on the chronic AF phenotype. We additionally found that the reduction in amplitude of the calcium transient in chronic AF as compared to normal sinus rhythm is primarily due to the remodeling of calcium channel function, calcium handling and cellular geometry. Finally, we found that decreased electrical resistance of the membrane together with remodeled calcium handling synergistically decreased cellular excitability and the subsequent inducibility of repolarization abnormalities in the human atrial myocyte in chronic AF. We conclude that the presented results highlight the complexity of both intrinsic cellular interactions and emergent properties of human atrial myocytes in chronic AF. Therefore, reversing remodeling for a single remodeled component does little to restore the normal sinus rhythm phenotype. These findings may have important implications for developing novel therapeutic approaches for chronic AF.

Abstract:

Left atrial fibrosis is thought to contribute to the manifestation of atrial fibrillation (AF). Late Gadolinium enhancement (LGE) MRI has the potential to image regions of low perfusion, which can be related to fibrosis. We show that a simulation with a patient-specific model including left atrial regional fibrosis derived from LGE-MRI reproduces local activation in the left atrium more precisely than the regular simulation without fibrosis. AF simulations showed a spontaneous termination of the arrhythmia in the absence of fibrosis and a stable rotor center in the presence of fibrosis. The methodology may provide a tool for a deeper understanding of the mechanisms maintaining AF and eventually also for the planning of substrate-guided ablation procedures in the future.

Abstract:

In case of chest pain, immediate diagnosis of myocardial ischemia is required to respond with an appropriate treatment. The diagnostic capability of the electrocardiogram (ECG), however, is strongly limited for ischemic events that do not lead to ST elevation. This computational study investigates the potential of different electrode setups in detecting early ischemia at 10 minutes after onset: standard 3-channel and 12-lead ECG as well as body surface potential maps (BSPMs). Further, it was assessed if an additional ECG electrode with optimized position or the right-sided Wilson leads can improve sensitivity of the standard 12-lead ECG. To this end, a simulation study was performed for 765 different locations and sizes of ischemia in the left ventricle. Improvements by adding a single, subject specifically optimized electrode were similar to those of the BSPM: 211% increased detection rate depending on the desired specificity. Adding right-sided Wilson leads had negligible effect. Absence of ST deviation could not be related to specific locations of the ischemic region or its transmurality. As alternative to the ST time integral as a feature of ST deviation, the K point deviation was introduced: the baseline deviation at the minimum of the ST-segment envelope signal, which increased 12-lead detection rate by 7% for a reasonable threshold.

Abstract:

AIMS: Human ether-a-go-go-related gene (hERG) missense mutations N588K and L532P are both associated with atrial fibrillation (AF). However, the underlying gain-of-function mechanism is different. The aim of this computational study is to assess and understand the arrhythmogenic mechanisms of these genetic disorders on the cellular and tissue level as a basis for the improvement of therapeutic strategies. METHODS AND RESULTS: The IKr formulation of an established model of human atrial myocytes was adapted by using the measurement data of wild-type and mutant hERG channels. Restitution curves of the action potential duration and its slope, effective refractory period (ERP), conduction velocity, reentry wavelength (WL), and the vulnerable window (VW) were determined in a one-dimensional (1D) tissue strand. Moreover, spiral wave inducibility and rotor lifetime in a 2D tissue patch were evaluated. The two mutations caused an increase in IKr regarding both peak amplitude and current integral, whereas the duration during which IKr is active was decreased. The WL was reduced due to a shorter ERP. Spiral waves could be initiated by using mutation models as opposed to the control case. The frequency dependency of the VW was reversed. CONCLUSION: Both mutations showed an increased arrhythmogenicity due to decreased refractory time in combination with a more linear repolarization phase. The effects were more pronounced for mutation L532P than for N588K. Furthermore, spiral waves presented higher stability and a more regular pattern for L532P. These in silico investigations unveiling differences of mutations affecting the same ion channel may help to advance genotype-guided AF prevention and therapy strategies.

Abstract:

BACKGROUND: Investigations on adverse biological effects of nanoparticles (NPs) in the lung by in vitro studies are usually performed under submerged conditions where NPs are suspended in cell culture media. However, the behaviour of nanoparticles such as agglomeration and sedimentation in such complex suspensions is difficult to control and hence the deposited cellular dose often remains unknown. Moreover, the cellular responses to NPs under submerged culture conditions might differ from those observed at physiological settings at the air-liquid interface. RESULTS: In order to avoid problems because of an altered behaviour of the nanoparticles in cell culture medium and to mimic a more realistic situation relevant for inhalation, human A549 lung epithelial cells were exposed to aerosols at the air-liquid interphase (ALI) by using the ALI deposition apparatus (ALIDA). The application of an electrostatic field allowed for particle deposition efficiencies that were higher by a factor of more than 20 compared to the unmodified VITROCELL deposition system. We studied two different amorphous silica nanoparticles (particles produced by flame synthesis and particles produced in suspension by the Stober method). Aerosols with well-defined particle sizes and concentrations were generated by using a commercial electrospray generator or an atomizer. Only the electrospray method allowed for the generation of an aerosol containing monodisperse NPs. However, the deposited mass and surface dose of the particles was too low to induce cellular responses. Therefore, we generated the aerosol with an atomizer which supplied agglomerates and thus allowed a particle deposition with a three orders of magnitude higher mass and of surface doses on lung cells that induced significant biological effects. The deposited dose was estimated and independently validated by measurements using either transmission electron microscopy or, in case of labelled NPs, by fluorescence analyses. Surprisingly, cells exposed at the ALI were less sensitive to silica NPs as evidenced by reduced cytotoxicity and inflammatory responses. CONCLUSION: Amorphous silica NPs induced qualitatively similar cellular responses under submerged conditions and at the ALI. However, submerged exposure to NPs triggers stronger effects at much lower cellular doses. Hence, more studies are warranted to decipher whether cells at the ALI are in general less vulnerable to NPs or specific NPs show different activities dependent on the exposure method.

Abstract:

The goal of ECG-imaging (ECGI) is to reconstruct heart electrical activity from body surface potential maps. The problem is ill-posed, which means that it is extremely sensitive to measurement and modeling errors. The most commonly used method to tackle this obstacle is Tikhonov regularization, which consists in converting the original problem into a well-posed one by adding a penalty term. The method, despite all its practical advantages, has however a serious drawback: The obtained solution is often over-smoothed, which can hinder precise clinical diagnosis and treatment planning. In this paper, we apply a binary optimization approach to the transmembrane voltage (TMV)-based problem. For this, we assume the TMV to take two possible values according to a heart abnormality under consideration. In this work, we investigate the localization of simulated ischemic areas and ectopic foci and one clinical infarction case. This affects only the choice of the binary values, while the core of the algorithms remains the same, making the approximation easily adjustable to the application needs. Two methods, a hybrid metaheuristic approach and the difference of convex functions (DC), algorithm were tested. For this purpose, we performed realistic heart simulations for a complex thorax model and applied the proposed techniques to the obtained ECG signals. Both methods enabled localization of the areas of interest, hence showing their potential for application in ECGI. For the metaheuristic algorithm, it was necessary to subdivide the heart into regions in order to obtain a stable solution unsusceptible to the errors, while the analytical DC scheme can be efficiently applied for higher dimensional problems. With the DC method, we also successfully reconstructed the activation pattern and origin of a simulated extrasystole. In addition, the DC algorithm enables iterative adjustment of binary values ensuring robust performance.

Abstract:

Electrocardiographic imaging (ECG imaging) is a method to depict electrophysiological processes in the heart. It is an emerging technology with the potential of making the therapy of cardiac arrhythmia less invasive, less expensive, and more precise. A major challenge for integrating the method into clinical workflow is the seamless and correct identification and localization of electrodes on the thorax and their assignment to recorded channels. This work proposes a camera-based system, which can localize all electrode positions at once and to an accuracy of approximately 1+/-1 mm. A system for automatic identification of individual electrodes is implemented that overcomes the need of manual annotation. For this purpose, a system of markers is suggested, which facilitates a precise localization to subpixel accuracy and robust identification using an error-correcting code. The accuracy of the presented system in identifying and localizing electrodes is validated in a phantom study. Its overall capability is demonstrated in a clinical scenario.

Abstract:

There is evidence that rotors could be drivers that maintain atrial fibrillation. Complex fractionated atrial electrograms have been located in rotor tip areas. However, the concept of electrogram fractionation, defined using time intervals, is still controversial as a tool for locating target sites for ablation. We hypothesize that the fractionation phenomenon is better described using non-linear dynamic measures, such as approximate entropy, and that this tool could be used for locating the rotor tip. The aim of this work has been to determine the relationship between approximate entropy and fractionated electrograms, and to develop a new tool for rotor mapping based on fractionation levels. Two episodes of chronic atrial fibrillation were simulated in a 3D human atrial model, in which rotors were observed. Dynamic approximate entropy maps were calculated using unipolar electrogram signals generated over the whole surface of the 3D atrial model. In addition, we optimized the approximate entropy calculation using two real multi-center databases of fractionated electrogram signals, labeled in 4 levels of fractionation. We found that the values of approximate entropy and the levels of fractionation are positively correlated. This allows the dynamic approximate entropy maps to localize the tips from stable and meandering rotors. Furthermore, we assessed the optimized approximate entropy using bipolar electrograms generated over a vicinity enclosing a rotor, achieving rotor detection. Our results suggest that high approximate entropy values are able to detect a high level of fractionation and to locate rotor tips in simulated atrial fibrillation episodes. We suggest that dynamic approximate entropy maps could become a tool for atrial fibrillation rotor mapping.

Abstract:

Congenital Long-QT Syndrome (LQTS) is a genetic dis- order affecting the repolarization of the heart. The most prevalent subtypes of LQTS are LQT1-3. In this work, we aim to evaluate the differences in the T-waves of simu- lated LQT1-3 in order to identify markers in the ECG that might help to classify patients solely based on ECG mea- surements. For LQT1, mutation S277L was used to char- acterize IKs and mutation S818L in IKr for LQT2. Volt- age clamp data were used to parametrize the ion channel equations of the ten Tusscher and Panfilov model of hu- man ventricular electrophysiology. LQT3 was integrated using an existing mutant INa model. The monodomain model was used in a transmural and apico-basal heteroge- neous model of the ventricles to calculate ventricular exci- tation propagation. The forward calculation on a torso model was performed to determine body surface ECGs. Compared to the physiological case with a QT-time of 375 ms, this interval was prolonged in all LQTS (LQT1 423 ms; LQT2 394 ms; LQT3 405 ms). The T-wave ampli- tude was changed (Einthoven lead II: LQT1 108%; LQT2 91%; LQT3 103%). Also, the width of the T-wave was en- larged (full width at half maximum: LQT1 111%; LQT2 125%; LQT3 109%). At the current state of modeling and data analysis, the three LQTS have not been distinguish- able solely by ECG data.

Abstract:

Abstract Magnetic particle imaging (MPI) is a new imaging modality using oscillating magnetic fields in the frequency range of 10 kHz to 100 kHz. The duration of data acquisition becomes smaller, and signal-to-noise ratio improves if the amplitude of these fields is increased - technically amplitudes of up to 100 mT might be feasible for human-sized systems. On the other hand, with increasing field strength, adverse health effects must be expected: oscillating magnetic fields can stimulate nerves and muscle and heat up tissue. Thresholds for stimulation with magnetic fields in this frequency range are not precisely known, neither is the local temperature rise following exposure. The ICNIRP guidelines define reference levels for magnetic field exposure for the general public that contain large safety factors - for medical diagnostics, they might be exceeded for a short time. In this article, research and guidelines in this field are briefly reviewed, and new results are presented in order to contribute to a future definition of safety limits for oscillating magnetic fields in MPI.

Abstract:

Numerical and patient-specific models of the human atrial anatomy and electrophysiology have a high potential to enhance our knowledge regarding pathological conditions and to increase the outcome of diagnosis and therapy. This chapter briefly describes the current state of the art in modeling of generalized human atria. Furthermore, the chapter demonstrates ways to personalize human atrial anatomy and electrophysiology based on a variety of measurement data from, e.g. late enhancement magnetic resonance imaging (MRI), patch clamp technique, intracardiac electrograms and body surface potential maps. Wherever patient data cannot be collected, patient-group specific behavior can be integrated. Some examples of the personalization process are described and the validation process is discussed together with future options for personalization, validation and application.

Abstract:

Atrial fibrillation (AF) is the most common cardiac arrhythmia, and the total number of AF patients is constantly increasing. The mechanisms leading to and sustaining AF are not completely understood yet. Heterogeneities in atrial electrophysiology seem to play an important role in this context. Although some heterogeneities have been used in in-silico human atrial modeling studies, they have not been thoroughly investigated. In this study, the original electrophysiological (EP) models of Courtemanche et al., Nygren et al. and Maleckar et al. were adjusted to reproduce action potentials in 13 atrial regions. The parameter sets were validated against experimental action potential duration data and ECG data from patients with AV block. The use of the heterogeneous EP model led to a more synchronized repolarization sequence in a variety of 3D atrial anatomical models. Combination of the heterogeneous EP model with a model of persistent AF-remodeled electrophysiology led to a drastic change in cell electrophysiology. Simulated Ta-waves were significantly shorter under the remodeling. The heterogeneities in cell electrophysiology explain the previously observed Ta-wave effects. The results mark an important step toward the reliable simulation of the atrial repolarization sequence, give a deeper understanding of the mechanism of atrial repolarization and enable further clinical investigations.

Abstract:

Computational atrial models aid the understanding of pathological mechanisms and therapeutic measures in basic research. The use of biophysical models in a clinical environment requires methods to personalize the anatomy and electrophysiology (EP). Strategies for the automation of model generation and for evaluation are needed. In this manuscript, the current efforts of clinical atrial modeling in the euHeart project are summarized within the context of recent publications in this field. Model-based segmentation methods allow for the automatic generation of ready-to-simulate patient-specific anatomical models. EP models can be adapted to patient groups based on a-priori knowledge, and to the individual without significant further data acquisition. ECG and intracardiac data build the basis for excitation personalization. Information from late enhancement (LE) MRI can be used to evaluate the success of radio-frequency ablation (RFA) procedures and interactive virtual atria pave the way for RFA planning. Atrial modeling is currently in a transition from the sole use in basic research to future clinical applications. The proposed methods build the framework for model-based diagnosis and therapy evaluation and planning. Complex models allow to understand biophysical mechanisms and enable the development of simplified models for clinical applications.

Abstract:

Multiscale cardiac modeling has made great advances over the last decade. Highly detailed atrial models were created and used for the investigation of initiation and perpetuation of atrial fibrillation. The next challenge is the use of personalized atrial models in clinical practice. In this study, a framework of simple and robust tools is presented, which enables the generation and validation of patient-specific anatomical and electrophysiological atrial models. Introduction of rule-based atrial fiber orientation produced a realistic excitation sequence and a better correlation to the measured electrocardiograms. Personalization of the global conduction velocity lead to a precise match of the measured P-wave duration. The use of a virtual cohort of nine patient and volunteer models averaged out possible model-specific errors. Intra-atrial excitation conduction was personalized manually from left atrial local activation time maps. Inclusion of LE-MRI data into the simulations revealed possible gaps in ablation lesions. A fast marching level set approach to compute atrial depolarization was extended to incorporate anisotropy and conduction velocity heterogeneities and reproduced the monodomain solution. The presented chain of tools is an important step towards the use of atrial models for the patient-specific AF diagnosis and ablation therapy planing.

Abstract:

Ventricular ectopic beats (VEBs) trigger a characteristic response of the heart called heart rate turbulence (HRT). The HRT can be used to predict sudden cardiac death in patients with a history of myocardial infarction. In this work, we present a reliable algorithm to detect and classify ectopic beats. Every electrocardiogram (ECG) is processed with innovative filtering techniques, artifact detection methods, and a robust multichannel analysis to produce accurate annotation results. For the classification task, a support vec- tor machine was used. Furthermore, a new approach to the analysis of HRT is proposed. The HRT is interpreted as the response of a second-order system to an external perturbation. The system theoretical parameters were estimated. The influence of VEB on the morphology of subsequent T waves was also analyzed. A strong influence was detected in the study with 14 patients experiencing frequent VEB. The evolution of the morphology of the T wave with every new beat was studied, and it could be concluded that an exponential shape underlies this dynamic process and was called morphological heart rate turbulence (MHRT). Parameters were defined to quantify the MHRT. The analysis of the MHRT could help to understand the influence of an ectopic beat on the repolarization processes of the heart and more accurately stratify the risk of sudden cardiac death.

Abstract:

Inhibition of the atrial ultra-rapid delayed rectifier potassium current (I Kur) represents a promising therapeutic strategy in the therapy of atrial fibrillation. However, experimental and clinical data on the antiarrhythmic efficacy remain controversial. We tested the hypothesis that antiarrhythmic effects of I Kur inhibitors are dependent on kinetic properties of channel blockade. A mathematical description of I Kur blockade was introduced into Courtemanche-Ramirez-Nattel models of normal and remodeled atrial electrophysiology. Effects of five model compounds with different kinetic properties were analyzed. Although a reduction of dominant frequencies could be observed in two dimensional tissue simulations for all compounds, a reduction of spiral wave activity could be only be detected in two cases. We found that an increase of the percent area of refractory tissue due to a prolongation of the wavelength seems to be particularly important. By automatic tracking of spiral tip movement we find that increased refractoriness resulted in rotor extinction caused by an increased spiral-tip meandering. We show that antiarrhythmic effects of I Kur inhibitors are dependent on kinetic properties of blockade. We find that an increase of the percent area of refractory tissue is the underlying mechanism for an increased spiral-tip meandering, resulting in the extinction of re-entrant circuits.

Abstract:

Electrophysiological modeling of cardiac tissue is commonly based on functional and structural properties measured in experiments. Our knowledge of these properties is incomplete, in particular their remodeling in disease. Here, we introduce a methodology for quantitative tissue characterization based on fluorescent labeling, three-dimensional scanning confocal microscopy, image processing and reconstruction of tissue micro-structure at sub-micrometer resolution. We applied this methodology to normal rabbit ventricular tissue and tissue from hearts with myocardial infarction. Our analysis revealed that the volume fraction of fibroblasts increased from 4.830.42% (meanstandard deviation) in normal tissue up to 6.510.38% in myocardium from infarcted hearts. The myocyte volume fraction decreased from 76.209.89% in normal to 73.488.02% adjacent to the infarct. Numerical field calculations on three-dimensional reconstructions of the extracellular space yielded an extracellular longitudinal conductivity of 0.2640.082 S/m with an anisotropy ratio of 2.0951.11 in normal tissue. Adjacent to the infarct, the longitudinal conductivity increased up to 0.4000.051 S/m, but the anisotropy ratio decreased to 1.2950.09. Our study indicates an increased density of gap junctions proximal to both fibroblasts and myocytes in infarcted versus normal tissue, supporting previous hypotheses of electrical coupling of fibroblasts and myocytes in infarcted hearts. We suggest that the presented methodology provides an important contribution to modeling normal and diseased tissue. Applications of the methodology include the clinical characterization of disease-associated remodeling. 1.

Abstract:

Mathematical modeling of cardiac electrophysiology is an insightful method to investigate the underlying mechanisms responsible for arrhythmias such as atrial fibrillation. In past years, five models of human atrial electrophysiology with different formulations of ionic currents, and consequently diverging properties, have been published. The aim of this work is to give an overview of strengths and weaknesses of these models depending on the purpose and the general requirements of simulations. Therefore, these models were systematically benchmarked with respect to general mathematical properties and their ability to reproduce certain electrophysiological phenomena, such as action potential alternans. To assess the models ability to replicate modified properties of human myocytes and tissue in cardiac disease, electrical remodeling in chronic atrial fibrillation was chosen as test case. The healthy and remodeled model variants were compared with experimental results in single-cell, 1D and 2D tissue simulations to investigate action potential and restitution properties, as well as the initiation of reentrant circuits.

Abstract:

Despite the commonly accepted notion that action potential duration (APD) is distributed heterogeneously throughout the ventricles and that the associated dispersion of repolarization is mainly responsible for the shape of the T-wave, its concordance and exact morphology are still not completely understood. This paper evaluated the T-waves for different previously measured heterogeneous ion channel distributions. To this end, cardiac activation and repolarization was simulated on a high resolution and anisotropic biventricular model of a volunteer. From the same volunteer, multichannel ECG data were obtained. Resulting transmembrane voltage distributions for the previously measured heterogeneous ion channel expressions were used to calculate the ECG and the simulated T-wave was compared to the measured ECG for quantitative evaluation. Both exclusively transmural (TM) and exclusively apico-basal (AB) setups produced concordant T-waves, whereas interventricular (IV) heterogeneities led to notched T-wave morphologies. The best match with the measured T-wave was achieved for a purely AB setup with shorter apical APD and a mix of AB and TM heterogeneity with M-cells in midmyocardial position and shorter apical APD. Finally, we probed two configurations in which the APD was negatively correlated with the activation time. In one case, this meant that the repolarization directly followed the sequence of activation. Still, the associated T-waves were concordant albeit of low amplitude.

Abstract:

Atrial arrhythmias are frequently treated using catheter ablation during electrophysiological (EP) studies. However, success rates are only moderate and could be improved with the help of personalized simulation models of the atria. In this work, we present a workflow to generate and validate personalized EP simulation models based on routine clinical computed tomography (CT) scans and intracardiac electrograms. From four patient data sets, we created anatomical models from angiographic CT data with an automatic segmentation algorithm. From clinical intracardiac catheter recordings, individual conduction velocities were calculated. In these subject-specific EP models, we simulated different pacing maneuvers and measurements with circular mapping catheters that were applied in the respective patients. This way, normal sinus rhythm and pacing from a coronary sinus catheter were simulated. Wave directions and conduction velocities were quantitatively analyzed in both clinical measurements and simulated data and were compared. On average, the overall difference of wave directions was 15° (8%), and the difference of conduction velocities was 16 cm/s (17%). The method is based on routine clinical measurements and is thus easy to integrate into clinical practice. In the long run, such personalized simulations could therefore assist treatment planning and increase success rates for atrial arrhythmias.

Abstract:

Thin-walled cardiac tissue samples superfused with oxygenated solutions are widely used in experimental studies. However, due to decreased oxygen supply and insufficient wash out of waste products in the inner layers of such preparations, electrophysiological functions could be compromised. Although the cascade of events triggered by cutting off perfusion is well known, it remains unclear as to which degree electrophysiological function in viable surface layers is affected by pathological processes occurring in adjacent tissue. Using a 3D numerical bidomain model, we aim to quantify the impact of superfusion-induced heterogeneities occurring in the depth of the tissue on impulse propagation in superficial layers. Simulations demonstrated that both the pattern of activation as well as the distribution of extracellular potentials close to the surface remain essentially unchanged. This was true also for the electrophysiological properties of cells in the surface layer, where most relevant depolarization parameters varied by less than 5.5 %. The main observed effect on the surface was related to action potential duration that shortened noticeably by 53 % as hypoxia deteriorated. Despite the known limitations of such experimental methods, we conclude that superfusion is adequate for studying impulse propagation and depolarization whereas repolarization studies should consider the influence of pathological processes taking place at the core of tissue sample.

Abstract:

This review article gives a comprehensive survey of the progress made in computa- tional modeling of the human atria during the last 10 years. Modeling the anatomy has emerged from simple peanut-like structures to very detailed models including atrial wall and fiber di- rection. Electrophysiological models started with just two cellular models in 1998. Today, five models exist considering e.g. details of intracellular compartments and atrial heterogeneity. On the pathological side, modeling atrial remodeling and fibrotic tissue are other important aspects. The bridge to data that are measured in the catheter laboratory and on the body surface (ECG) is under construction. Every measurement can be used either for model personalization or for validation. Potential clinical applications are briefly outlined and future research perspectives are suggested.

Abstract:

Tissue heating during magnetic resonance measurements is a potential hazard at high-field MRI, and particularly, in the framework of parallel radiofrequency transmission. The heating is directly related to the radiofrequency energy absorbed during an magnetic resonance examination, that is, the specific absorption rate (SAR). SAR is a pivotal parameter in MRI safety regulations, requiring reliable estimation methods. Currently used methods are usually based on models which are neither patient-specific nor taken into account patient position and posture, which typically leads to the need for large safety margins. In this work, a novel approach is presented, which measures local SAR in a patient-specific manner. Using a specific formulation of Maxwell's equations, the local SAR is estimated via postprocessing of the complex transmit sensitivity of the radiofrequency antenna involved. The approximations involved in the proposed method are investigated. The presented approach yields a sufficiently accurate and patient-specific local SAR measurement of the brain within a scan time of less than 5 min.

Abstract:

Introduction: Atrial fibrillation (AF) is the most common cardiac arrhythmia affecting around 1% of the population. Several anti-arrhythmic drugs such as e.g. amiodarone or dronedarone influence cardiac electrophysiology reducing arrhythmias. However, the electrophysiological mechanisms underlying the initiation and persistence of AF are not completely understood yet.Methods: A mathematical model of atrial electrophysiology was modified to simulate the effects of chronic AF (cAF). Furthermore, ion channel conductivities were reduced according to the inhibition caused by two different concentrations of amiodarone and dronedarone. The resulting drug effects were investigated in healthy and cAF single-cells as well as in tissue. In a 1D tissue strand, restitution curves of the effective refractory period (ERP), the conduction velocity (CV) and the wavelength (WL) were computed. Furthermore, persistence of rotors in a 2D tissue patch was analyzed. For this purpose, four rotors were initiated in the cAF patch and then the drug effects were incorporated.Results: Dronedarone and amiodarone prolonged the atrial action potential duration of cAF cells, whereas high concentration of amiodarone slightly shortened it in healthy cells. Furthermore, both drugs increased the ERP and slowed the CV. Dronedarone shows the longer ERP and also a higher CV. As a result, the WL was prolonged by dronedarone and shortened by high concentration of amiodarone. Low concentration of amiodarone did not change the WL. In the 2D tissue patch, dronedarone altered significantly the trajectory of rotors, but did not terminate them.Conclusion: Computer simulations of the effects of antiarrhythmic drugs on cardiac electrophysiology are a helpful tool to better understand the mechanisms responsible for persistence and termination of AF. However, ion current measurement data available in literature show great variability of values depending on the species or temperature. Therefore, integration of drug effects into models of cardiac electrophysiology still needs to be improved.

Abstract:

Aims Amiodarone and cisapride are both known to prolong the QT interval, yet the two drugs have different effects on arrhythmia. Cisapride can cause torsades de pointes while amiodarone is found to be anti-arrhythmic. A computational model was used to investigate the action of these two drugs.Methods and results In a biophysically detailed model, the ion current conductivities affected by both drugs were reduced in order to simulate the pharmacological effects in healthy and ischaemic cells. Furthermore, restitution curves of the action potential duration (APD), effective refractory period, conduction velocity, wavelength, and the vulnerable window were determined in a one-dimensional (1D) tissue strand. Moreover, cardiac excitation propagation was computed in a 3D model of healthy ventricles. The corresponding body surface potentials were calculated and standard 12-lead electrocardiograms were derived. Both cisapride and amiodarone caused a prolongation of the QT interval and the refractory period. However, cisapride did not significantly alter the conduction-related properties, such as e.g. the wavelength or vulnerable window, whereas amiodarone had a larger impact on them. It slightly flattened the APD restitution slope and furthermore reduced the conduction velocity and wavelength.Conclusion Both drugs show similar prolongation of the QT interval, although they present different electrophysiological properties in the single-cell as well as in tissue simulations of cardiac excitation propagation. These computer simulations help to better understand the underlying mechanisms responsible for the initiation or termination of arrhythmias caused by amiodarone and cisapride.

Abstract:

Models of cardiac tissue electrophysiology are an important component of the Cardiac Physiome Project, which is an international effort to build biophysically based multi-scale mathematical models of the heart. Models of tissue electrophysiology can provide a bridge between electrophysiological cell models at smaller scales, and tissue mechanics, metabolism and blood flow at larger scales. This paper is a critical review of cardiac tissue electrophysiology models, focussing on the micro-structure of cardiac tissue, generic behaviours of action potential propagation, different models of cardiac tissue electrophysiology, the choice of parameter values and tissue geometry, emergent properties in tissue models, numerical techniques and computational issues. We propose a tentative list of information that could be included in published descriptions of tissue electrophysiology models, and used to support interpretation and evaluation of simulation results. We conclude with a discussion of challenges and open questions.

Abstract:

In this manuscript we review the state of cardiac cell modelling in the context of international initiatives such as the IUPS Physiome and Virtual Physiological Human Projects, which aim to integrate computational models across scales and physics. In particular we focus on the relationship between experimental data and model parameterisation across a range of model types and cellular physiological systems. Finally, in the context of parameter identification and model reuse within the Cardiac Physiome, we suggest some future priority areas for this field.

Abstract:

The specific absorption rate (SAR) is a limiting constraint in sequence design for high-field MRI. SAR estimation is typically performed by numerical simulations using generic human body models. This entails an intrinsic uncertainty in present SAR prediction. This study first investigates the required detail of human body models in terms of spatial resolution and the number of soft tissue classes required, based on finite-differences time-domain simulations of a 3 T body coil. The numerical results indicate that a resolution of 5 mm is sufficient for local SAR estimation. Moreover, a differentiation between fatty tissues, water-rich tissues, and the lungs was found to be essential to represent eddy current paths inside the human body. This study then proposes a novel approach for generating individualized body models from whole-body water-fat-separated MR data and applies it to volunteers. The SAR hotspots consistently occurred in the arms due to proximity to the body coil as well as in narrow regions of the muscles. An initial in vivo validation of the simulated fields in comparison with measured B(1) -field maps showed good qualitative and quantitative agreement. Magn Reson Med, 2011. (c) 2011 Wiley-Liss, Inc.

Abstract:

OBJECT: Parallel transmission facilitates a relatively direct control of the RF transmit field. This is usually applied to improve the RF field homogeneity but might also allow a reduction of the specific absorption rate (SAR) to increase freedom in sequence design for high-field MRI. However, predicting the local SAR is challenging as it depends not only on the multi-channel drive but also on the individual patient. MATERIALS AND METHODS: The potential of RF shimming for SAR management is investigated for a 3 T body coil with eight independent transmit elements, based on Finite-Difference Time-Domain (FDTD) simulations. To address the patient-dependency of the SAR, nine human body models were generated from volunteer MR data and used in the simulations. A novel approach to RF shimming that enforces local SAR constraints is proposed. RESULTS: RF shimming substantially reduced the local SAR, consistently for all volunteers. Using SAR constraints, a further SAR reduction could be achieved with only minor compromises in RF performance. CONCLUSION: Parallel transmission can become an important tool to control and manage the local SAR in the human body. The practical use of local SAR constraints is feasible with consistent results for a variety of body models.

Abstract:

The specific absorption rate (SAR) is an important safety criterion, limiting many MR protocols with respect to the achievable contrast and scan duration. Parallel transmission enables control of the radiofrequency field in space and time and hence allows for SAR management. However, a trade-off exists between radiofrequency pulse performance and SAR reduction. To overcome this problem, in this work, parallel transmit radiofrequency pulses are adapted to the position in sampling k-space. In the central k-space, highly homogeneous but SAR-intensive radiofrequency shim settings are used to achieve optimal performance and contrast. In the outer k-space, the homogeneity requirement is relaxed to reduce the average SAR of the scan. The approach was experimentally verified on phantoms and volunteers using field echo and spin echo sequences. A reduction of the SAR by 25-50% was achieved without compromising image quality.

Abstract:

Ventricular wall deformation is widely assumed to have an impact on the morphology of the T-wave that can be measured on the body surface. This study aims at quantifying these effects based on an in silico approach. To this end, we used a hybrid, static-dynamic approach: action potential propagation and repolarization were simulated on an electrophysiologically detailed but static 3-D heart model while the forward calculation accounted for ventricular deformation and the associated movement of the electrical sources (thus, it was dynamic). The displacement vectors that describe the ventricular motion were extracted from cinematographic and tagged MRI data using an elastic registration procedure. To probe to what extent the T-wave changes depend on the synchrony/asynchrony of mechanical relaxation and electrical repolarization, we created three electrophysiological configurations, each with a unique QT time: a setup with physiological QT time, a setup with pathologically short QT time (SQT), and pathologically long QT time (LQT), respectively. For all three electrophysiological configurations, a reduction of the T-wave amplitude was observed when the dynamic model was used for the forward calculations. The largest amplitude changes and the lowest correlation coefficients between the static and dynamic model were observed for the SQT setup, followed by the physiological QT and LQT setups.

Abstract:

BACKGROUND: The prevalence of atrial fibrillation is increased in patients with end-stage renal disease. Previous studies suggested that extracellular electrolyte alterations caused by hemodialysis (HD) therapy could be proarrhythmic. METHODS: Multiscale models were used for a consequent analysis of the effects of extracellular ion concentration changes on atrial electrophysiology. Simulations were based on measured electrolyte concentrations from patients with end-stage renal disease. RESULTS: Simulated conduction velocity and effective refractory period are decreased at the end of an HD session, with potassium having the strongest influence. P-wave is prolonged in patients undergoing HD therapy in the simulation as in measurements. CONCLUSIONS: Electrolyte concentration alterations impact atrial electrophysiology from the action potential level to the P-wave and can be proarrhythmic, especially because of induced hypokalemia. Analysis of blood electrolytes enables patient-specific electrophysiology modeling. We are providing a tool to investigate atrial arrhythmias associated with HD therapy, which, in the future, can be used to prevent such complications.

Abstract:

Ongoing developments in cardiac modelling have resulted, in particular, in the development of advanced and increasingly complex computational frameworks for simulating cardiac tissue electrophysiology. The goal of these simulations is often to represent the detailed physiology and pathologies of the heart using codes that exploit the computational potential of high-performance computing architectures. These developments have rapidly progressed the simulation capacity of cardiac virtual physiological human style models; however, they have also made it increasingly challenging to verify that a given code provides a faithful representation of the purported governing equations and corresponding solution techniques. This study provides the first cardiac tissue electrophysiology simulation benchmark to allow these codes to be verified. The benchmark was successfully evaluated on 11 simulation platforms to generate a consensus gold-standard converged solution. The benchmark definition in combination with the gold-standard solution can now be used to verify new simulation codes and numerical methods in the future.

Abstract:

The loss of cardiac pump function accounts for a significant increase in both mortality and morbidity in Western society, where there is currently a one in four lifetime risk, and costs associated with acute and long-term hospital treatments are accelerating. The significance of cardiac disease has motivated the application of state-of-the-art clinical imaging techniques and functional signal analysis to aid diagnosis and clinical planning. Measurements of cardiac function currently provide high-resolution datasets for characterizing cardiac patients. However, the clinical practice of using population-based metrics derived from separate image or signal-based datasets often indicates contradictory treatments plans owing to inter-individual variability in pathophysiology. To address this issue, the goal of our work, demonstrated in this study through four specific clinical applications, is to integrate multiple types of functional data into a consistent framework using multi-scale computational modelling.

Abstract:

The electric properties of human tissue can potentially be used as an additional diagnostic parameter, e.g., in tumor diagnosis. In the framework of radiofrequency safety, the electric conductivity of tissue is needed to correctly estimate the local specific absorption rate distribution during MR measurements. In this study, a recently developed approach, called electric properties tomography (EPT) is adapted for and applied to in vivo imaging. It derives the patient's electric conductivity and permittivity from the spatial sensitivity distributions of the applied radiofrequency coils. In contrast to other methods to measure the patient's electric properties, EPT does not apply externally mounted electrodes, currents, or radiofrequency probes, which enhances the practicability of the approach. This work shows that conductivity distributions can be reconstructed from phase images and permittivity distributions can be reconstructed from magnitude images of the radiofrequency transmit field. Corresponding numerical simulations using finite-difference time-domain methods support the feasibility of this phase-based conductivity imaging and magnitude-based permittivity imaging. Using this approximation, three-dimensional in vivo conductivity and permittivity maps of the human brain are obtained in 5 and 13 min, respectively, which can be considered a step toward clinical feasibility for EPT. Magn Reson Med, 2011. (c) 2011 Wiley-Liss, Inc.

Abstract:

In this paper, we present an efficient method to estimate changes in forward-calculated body surface potential maps (BSPMs) caused by variations in tissue conductivities. For blood, skeletal muscle, lungs, and fat, the influence of conductivity variations was analyzed using the principal component analysis (PCA). For each single tissue, we obtained the first PCA eigenvector from seven sample simulations with conductivities between ±75% of the default value. We showed that this eigenvector was sufficient to estimate the signal over the whole conductivity range of ±75%. By aligning the origins of the different PCA coordinate systems and superimposing the single tissue effects, it was possible to estimate the BSPM for combined conductivity variations in all four tissues. Furthermore, the method can be used to easily calculate confidence intervals for the signal, i.e., the minimal and maximal possible amplitudes for given conductivity uncertainties. In addition to that, it was possible to determine the most probable conductivity values for a given BSPM signal. This was achieved by probing hundreds of different conductivity combinations with a numerical optimization scheme. In conclusion, our method allows to efficiently predict forward-calculated BSPMs over a wide range of conductivity values from few sample simulations.

Abstract:

Conduction velocity (CV) and CV restitution are important substrate parameters for understanding atrial arrhythmias. The aim of this work is to (i) present a simple but feasible method to measure CV restitution in-vivo using standard circular catheters, and (ii) validate its feasibility with data measured during incremental pacing. From five patients undergoing catheter ablation, we analyzed 8 datasets from sinus rhythm and incremental pacing sequences. Every wavefront was measured with a circular catheter and the electrograms were analyzed with a cosine-fit method that calculated the local CV. For each pacing cycle length, the mean local CV was determined. Furthermore, changes in global CV were estimated from the time delay between pacing stimulus and wavefront arrival. Comparing local and global CV between pacing at 500 and 300 ms, we found significant changes in 7 of 8 pacing sequences. On average, local CV decreased by 2015% and global CV by 1713%. The method allows for in-vivo measurements of absolute CV and CV restitution during standard clinical procedures. Such data may provide valuable insights into mechanisms of atrial arrhythmias. This is important both for improving cardiac models and also for clinical applications, such as characterizing arrhythmogenic substrates during sinus rhythm.

Abstract:

Acute cardiac ischemia, which is caused by the occlusion of a coronary artery, often leads to lethal ventricular arrhythmias or heart failure. The early diagnosis of this pathology is based on changes of the electrocardiogram (ECG), i.e. mainly shifts of the ST segment. However, the underlying mechanisms responsible for these shifts are not completely understood. Furthermore, clinical observations indicate that some acute ischemia cases can hardly be detected using standard 12-lead ECG only. Therefore, multi-scale computer simulations of cardiac ischemia using realistic models of human ventricles were carried out in this work. For this purpose, the transmembrane voltage distributions in the heart and the corresponding body surface potentials were computed with varying transmural extent of the ischemic region at different ischemia stages. Some of the simulated ischemia cases were electrically silent, i.e. they could hardly be identified in the 12-lead ECG.

Abstract:

Purpose: Three-dimensional (3-D) reconstruction of the coronary arteries during a cardiac catheter-based intervention can be performed from a C-arm based rotational x-ray angiography sequence. It can support the diagnosis of coronary artery disease, treatment planning, and intervention guidance. 3-D reconstruction also enables quantitative vessel analysis, including vessel dynamics from a time-series of reconstructions.Methods: The strong angular undersampling and motion effects present in gated cardiac reconstruction necessitate the development of special reconstruction methods. This contribution presents a fully automatic method for creating high-quality coronary artery reconstructions. It employs a sparseness-prior based iterative reconstruction technique in combination with projection-based motion compensation.Results: The method is tested on a dynamic software phantom, assessing reconstruction accuracy with respect to vessel radii and attenuation coefficients. Reconstructions from clinical cases are presented, displaying high contrast, sharpness, and level of detail.Conclusions: The presented method enables high-quality 3-D coronary artery imaging on an interventional C-arm system.

Abstract:

This paper examined the effects that different tissue conductivities had on forward-calculated ECGs. To this end, we ranked the influence of tissues by performing repetitive forward calculations while varying the respective tissue conductivity. The torso model included all major anatomical structures like blood, lungs, fat, anisotropic skeletal muscle, intestine, liver, kidneys, bone, cartilage, and spleen. Cardiac electrical sources were derived from realistic atrial and ventricular simulations. The conductivity rankings were based on one of two methods: First, we considered fixed percental conductivity changes to probe the sensitivity of the ECG regarding conductivity alterations. Second, we set conductivities to the reported minimum and maximum values to evaluate the effects of the existing conductivity uncertainties. The amplitudes of both atrial and ventricular ECGs were most sensitive for blood, skeletal muscle conductivity and anisotropy as well as for heart, fat, and lungs. If signal morphology was considered, fat was more important whereas skeletal muscle was less important. When comparing atria and ventricles, the lungs had a larger effect on the atria yet the heart conductivity had a stronger impact on the ventricles. The effects of conductivity uncertainties were significant. Future studies dealing with electrocardiographic simulations should consider these effects.

Abstract:

Biventricular pacing (BVP) could be improved by identifying the patient-specific optimal electrode positions. Body surface potential map (BSPM) is a non-invasive technique for obtaining the electrophysiology and pathology of a patient. The study proposes the use of BSPM as input for an automated non-invasive strategy based on a personalized computer model of the heart, to identify the patient pathology and specific optimal treatment with BVP devices. The anatomy of a patient suffering from left bundle branch block and myocardial infarction is extracted from a series of MR data sets. The clinical measurements of BSPM are used to parameterize the computer model of the heart to represent the individual pathology. Cardiac electrophysiology is simulated with ten Tusscher cell model and excitation propagation is calculated with adaptive cellular automaton, at physiological and pathological conduction levels. The optimal electrode configurations are identified by evaluating the QRS error between healthy and pathology case with/without pacing. Afterwards, the simulated ECGs for optimal pacing are compared to the post-implantation clinically measured ECGs. Both simulation and clinical optimization methods identified the right ventricular (RV) apex and the LV posterolateral regions as being the optimal electrode configuration for the patient. The QRS duration is reduced both in measured and simulated ECG after implantation with 20 and 14%, respectively. The optimized electrode positions found by simulation are comparable to the ones used in hospital. The similarity in QRS duration reduction between measured and simulated ECG signals indicates the success of the method. The computer model presented in this work is a suitable tool to investigate individual pathologies. The personalized model could assist therapy planning of BVP in patients with congestive heart failure. The proposed method could be used as prototype for further clinically oriented investigations of computerized optimization of biventricular pacing.

Abstract:

The waveguide invariant in shallow water environments has been widely studied in the context of passive sonar. The invariant provides a relationship between the frequency content of a moving broadband source and the distance to the receiver, and this relationship is not strongly affected by small perturbations in environment parameters such as sound speed or bottom features. Recent experiments in shallow water suggest that a similar range-frequency structure manifested as striations in the spectrogram exists for active sonar, and this property has the potential to enhance the performance of target tracking algorithms. Nevertheless, field experiments with active sonar have not been conclusive on how the invariant is affected by the scattering kernel of the target and the sonar configuration (monostatic vs bistatic). The experimental work presented in this paper addresses those issues by showing the active invariance for known scatterers under controlled conditions of bathymetry, sound speed profile and high SNR. Quantification of the results is achieved by introducing an automatic image processing approach inspired on the Hough transform for extraction of the invariant from spectrograms. Normal mode simulations are shown to be in agreement with the experimental results.

Abstract:

OBJECT: Most functional magnetic resonance imaging (fMRI) experiments use gradient-echo echo planar imaging (GE EPI) to detect the blood oxygenation level-dependent (BOLD) effect. This technique may fail in the presence of anatomy-related susceptibility-induced field gradients in the human head. In this work, we present a novel 3D compensation method in combination with a template-based correction that can be optimized over particular regions of interest to recover susceptibility-induced signal loss without acquisition time penalty. MATERIALS AND METHODS: Based on an evaluation of B(0) field maps of eight subjects, slice-dependent gradient compensation moments are derived for maximal BOLD sensitivity in two compromised regions: the orbitofrontal cortex and the amygdala areas. A modified EPI sequence uses these additional gradient moments in all three imaging directions. The method is compared to non-compensated, template-based and subject-specific correction gradients and also in a breath-holding experiment. RESULTS: The slice-dependent gradient compensation method significantly improves signal intensity/BOLD sensitivity by about 35/43% in the orbitofrontal cortex and by 17/30% in the amygdala areas compared to a conventional acquisition. Template-based correction and subject-specific correction perform equally well. The BOLD sensitivity in the breath hold experiment is effectively increased in compensated regions. CONCLUSION: The new method addresses the problem of susceptibility-induced signal loss, without compromising temporal resolution. It can be used for event-related functional experiments without requiring additional subject-specific calibration or calculation time.

Abstract:

Deep hypothermic circulatory arrest is necessary for some types of cardiac and aortic surgery. Perfusion of the brain can be maintained using a heart-lung machine and unilateral antegrade cerebral perfusion (ACP). Cooling rates during extracorporeal circulation depend on local perfusion. A core temperature of 24-25 degrees C is aimed at to extend ischemic tolerance of tissues. Information on cerebral perfusion and temperature is important for the safety of patients but hardly accessible to measurement. A combined simulation model of haemodynamics and temperature is presented in this paper. The haemodynamics model employs the transmission line approach and integrates the Circle of Willis. This allows for parametrization of individual aberrations. Simulation results of cerebral perfusion are shown for two configurations of the Circle of Willis. The temperature model provides spatial information on temperature fields. It considers heat transfer in the various tissues retrieving data of local tissue perfusion from the haemodynamics model. The combined model is evaluated by retrospective simulation of two aortic operations.

Abstract:

In this work, a new framework is presented that is suitable to solve the cardiac bidomain equation efficiently using the scientific computing library PETSc. Furthermore, the framework is able to modularly combine different ionic channels and is flexible enough to include arbitrary heterogeneities in ionic or coupling channel density. The ability of this framework is demonstrated in an example simulation in which the three-dimensional electrophysiological heterogeneity was adjusted in order to get a positive T-wave in the body electrocardiogram (ECG).

Abstract:

Simulations of the electrophysiological behavior of the heart improve the comprehension of the mechanisms of the cardiovascular system. Furthermore, the mathematical modeling will support diagnosis and therapy of patients suffering from heart diseases. In this paper, the chain of modeling of the electrical function in the heart is described. The components are explained briefly, namely modeling of cardiac geometry, reconstructing the cardiac electrophysiology and excitation propagation. Additionally, the mathematical methods allowing to implement and solve these models are outlined. The three recently more investigated cases atrial fibrillation, ischemia and long-QT syndrome are described and show how cardiac modeling can support cardiologists in answering their open questions.

Abstract:

This work presents a new approach toward a fast, simultaneous amplitude of radiofrequency field (B(1)) and T(1) mapping technique. The new method is based on the "actual flip angle imaging" (AFI) sequence. However, the single pulse repetition time (TR) pair used in the standard AFI sequence is replaced by multiple pulse repetition time sets. The resulting method was called "multiple TR B(1)/T(1) mapping" (MTM). In this study, MTM was investigated and compared to standard AFI in simulations and experiments. Feasibility and reliability of MTM were proven in phantom and in vivo experiments. Error propagation theory was applied to identify optimal sequence parameters and to facilitate a systematic noise comparison to standard AFI. In terms of accuracy and signal-to-noise ratio, the presented method outperforms standard AFI B(1) mapping over a wide range of T(1). Finally, the capability of MTM to determine T(1) was analyzed qualitatively and quantitatively, yielding good agreement with reference measurements. Magn Reson Med, 2010. (c) 2010 Wiley-Liss, Inc.

Abstract:

Atrial arrhythmias, such as atrial flutter or fibrillation, are frequent indications for catheter ablation. Recorded intracardiac electrograms (EGMs) are, however, mostly evaluated subjectively by the physicians. In this paper, we present a method to quantitatively extract the wave direction and the local conduction velocity from one single beat in a circular mapping catheter signal. We simulated typical clinical EGMs to validate the method. We then showed that even with noise, the average directional error was below 10(°) and the average velocity error was below 5.4 cm/s. In a realistic atrial simulation, the method could clearly distinguish between stimuli from different pulmonary veins. We further analyzed eight clinical data segments from three patients in normal sinus rhythm and with stimulation. We obtained stable wave directions for each segment and conduction velocities between 70 and 115 cm/s. We conclude that the method allows for easy quantitative analysis of single macroscopic wavefronts in intracardiac EGMs, such as during atrial flutter or in typical clinical stimulation procedures after termination of atrial fibrillation. With corresponding simulated data, it can provide an interface to personalize electrophysiological (EP) models. Furthermore, it could be integrated into EP navigation systems to provide quantitative data of high diagnostic value to the physician

Abstract:

Bioelectric source measurements are influenced by the measurement location as well as the conductive properties of the tissues. Volume conductor effects such as the poorly conducting bones or the moderately conducting skin are known to affect the measurement precision and accuracy of the surface electroencephalography (EEG) measurements. This paper investigates the influence of age via skull conductivity upon surface and subdermal bipolar EEG measurement sensitivity conducted on two realistic head models from the Visible Human Project. Subdermal electrodes (a.k.a. subcutaneous electrodes) are implanted on the skull beneath the skin, fat, and muscles. We studied the effect of age upon these two electrode types according to the scalp-to-skull conductivity ratios of 5, 8, 15, and 30 : 1. The effects on the measurement sensitivity were studied by means of the half-sensitivity volume (HSV) and the region of interest sensitivity ratio (ROISR). The results indicate that the subdermal implantation notably enhances the precision and accuracy of EEG measurements by a factor of eight compared to the scalp surface measurements. In summary, the evidence indicates that both surface and subdermal EEG measurements benefit better recordings in terms of precision and accuracy on younger patients.

Abstract:

The message of this article is that patient safety must be an essential part of thinking and planning in research for medical technology. Which aspects must be considered already in an early phase of any project are presented. The most important standards are listed briefly. Then the topics technical safety and electromagnetic compatibility (EMC), clinical evaluation, risk analysis, biological evaluation of materials, ergonomics, the special aspects of medical devices that include pharmacological components, and the requirements of software packages and implemented algorithms are discussed.Im vorliegenden Beitrag wird begründet, warum die Patientensicherheit vom ersten Tag an ein wesentlicher Bestandteil der Überlegungen und Planungen in der medizintechnischen Forschung sein muss. Es wird dargestellt, welche Aspekte insbesondere schon in den frühen Phasen eines Projektes berücksichtigt werden müssen. Die wichtigsten Normen werden nur kurz angesprochen. Dann werden die Themen technische Sicherheit und Elektromagnetische Verträglichkeit (EMV), klinische Prüfung, Risikoanalyse, biologische Bewertung von Materialien, Ergonomie, die Problematik von Medizintechnik mit pharmakologischen Komponenten und die Anforderungen an reine Softwarepakete für die Medizin und an implementierte Algorithmen genauer betrachtet.

Abstract:

Non-invasive localization of premature ventricular beat (PVB) foci is very important for medical treatment of numerous cardiac diseases. In this work a model-based method of reconstruction of ectopic center locations is investigated.Within the scope of this method patient's multichannel ECG is used as a reference for optimization of an electrophysiological cardiac model. This model is based on the cellular automaton principle and utilizes anatomical data of the patient. Optimized are coordinates of the ectopic focus as well as excitation conduction velocity of ventricular myocardium. Initial values for these parameters are obtained by solving the linearized problem of electrocardiography in terms of activation times. Optimization is performed by minimization of discrepancy between the simulated and reference ECGs.The aim of the current work is to estimate the quality of ectopic focus localization delivered by this method. Four sample ectopic beats have been simulated, with their foci located in different regions of the left ventricle. 1% Gaussian noise has been introduced into the resulting ECGs. In this way the "measured" ECG signals for this investigation have been obtained. Afterwards the origin of each ectopic beat has been reconstructed using the model-based approach. The method has demonstrated reliable localization of PVB foci, reconstruction errors have not exceeded 6.1 mm.

Abstract:

The distributions of transmembrane voltage (TMV) within the cardiac tissue are linearly connected with the patient's body surface potential maps (BSPMs) at every time instant. The matrix describing the relation between the respective distributions is referred to as the transfer matrix. This matrix can be employed to carry out forward calculations in order to find the BSPM for any given distribution of TMV inside the heart. Its inverse can be used to reconstruct the cardiac activity non-invasively, which can be an important diagnostic tool in the clinical practice.The computation of this matrix using the finite element method can be quite time-consuming. In this work, a method is proposed allowing to speed up this process by computing an approximate transfer matrix instead of the precise one. The method is tested on three realistic anatomical models of real-world patients. It is shown that the computation time can be reduced by 50% without loss of accuracy.

Abstract:

Over the last years, nonfluoroscopic in vivo cardiac mapping and navigation systems have been developed and successfully applied in clinical electrophysiology. Clearly, a trend can be observed to introduce more sensors into the measurement system so that physiological information can be gathered simultaneously and more efficiently and the duration of procedure can be shortened significantly. However, it would not be realistic to equip each catheter electrode with a localizer, e.g., by embedding a miniature magnetic location sensor. Therefore, in this paper, an alternate approach has been worked out to efficiently localize multiple catheter electrodes by considering the impedance between electrodes in the heart and electrode patches on the body surface. In application of the new technique, no additional expensive and sophisticated hardware is required other than the currently existing cardiac navigation system. A tank model and a computerized realistic human model are employed to support the development of the positioning system. In the simulation study, the new approach achieves an average localization error of less than 1 mm, which proves the feasibility of the impedance-based catheter positioning system. Consequently, the new positioning system can provide an inexpensive and accurate solution to improve the efficiency and efficacy of catheter ablation.

Abstract:

The electric conductivity can potentially be used as an additional diagnostic parameter, e.g., in tumour diagnosis. Moreover, the electric conductivity, in connection with the electric field, can be used to estimate the local SAR distribution during MR measurements. In this study, a new approach, called electric properties tomography (EPT) is presented. It derives the patient's electric conductivity, along with the corresponding electric fields, from the spatial sensitivity distributions of the applied RF coils, which are measured via MRI. Corresponding numerical simulations and initial experiments on a standard clinical MRI system underline the principal feasibility of EPT to determine the electric conductivity and the local SAR. In contrast to previous methods to measure the patient's electric properties, EPT does not apply externally mounted electrodes, currents, or RF probes, thus enhancing the practicability of the approach. Furthermore, in contrast to previous methods, EPT circumvents the solution of an inverse problem, which might lead to significantly higher spatial image resolution.

Abstract:

An improvement of biventricular pacing (BVP) could be possible by detecting the patient specific optimal pacemaker parameters. Body surface potential map (BSPM) is used to obtain the electrophysiology and pathology of an individual patient non-invasively. The clinical measurements of BSPM are used to parameterize the computer model of the heart to represent the individual pathology. The computer model of the heart is used to simulate the dyssynchrony of the ventricles and myocardial infarction (MI). Cardiac electrophysiology is simulated with ten Tusscher cell model, while excitation propagation is intended with adaptive cellular automaton at physiological and pathological conduction stages. The optimal electrode configurations are identified by minimizing the QRS duration error of healthy and pathology case with/without pacing between pre and post-implantation. Afterwards, the simulated ECGs for optimal pacing are compared to the post implantation clinically measured ECGs. The optimal electrode positions found by simulation are comparable to the ones meausured in hospital. The QRS duration reduction error between measured and simulated 12 ECG signals are similar with a constant offset of 15 ms. The personalized model present in this research is an effective tool for therapy planning of BVP in patients with congestive heart failure.

Abstract:

BACKGROUND: The efficacy of cardiac resynchronization therapy through biventricular pacing (BVP) has been demonstrated by numerous studies in patients suffering from congestive heart failure. In order to achieve a guideline for optimal treatment with BVP devices, an automated non-invasive strategy based on a computer model of the heart is presented. MATERIALS AND METHODS: The presented research investigates an off-line optimization algorithm regarding electrode positioning and timing delays. The efficacy of the algorithm is demonstrated in four patients suffering from left bundle branch block (LBBB) and myocardial infarction (MI). The computer model of the heart was used to simulate the LBBB in addition to several MI allocations according to the different left ventricular subdivisions introduced by the American Heart Association. Furthermore, simulations with reduced interventricular conduction velocity were performed in order to model interventricular excitation conduction delay. More than 800,000 simulations were carried out by adjusting a variety of 121 pairs of atrioventricular and interventricular delays and 36 different electrode positioning set-ups. Additionally, three different conduction velocities were examined. The optimization measures included the minimum root mean square error (E(RMS)) between physiological, pathological and therapeutic excitation, and also the difference of QRS-complex duration. Both of these measures were computed automatically. RESULTS: Depending on the patient's pathology and conduction velocity, a reduction of E(RMS) between physiological and therapeutic excitation could be reached. For each patient and pathology, an optimal pacing electrode pair was determined. The results demonstrated the importance of an individual adjustment of BVP parameters to the patient's anatomy and pathology. CONCLUSION: This work proposes a novel non-invasive optimization algorithm to find the best electrode positioning sites and timing delays for BVP in patients with LBBB and MI. This algorithm can be used to plan an optimal therapy for an individual patient.

Abstract:

Fibroblasts are abundant in cardiac tissue. Experimental studies suggested that fibroblasts are electrically coupled to myocytes and this coupling can impact cardiac electrophysiology. In this work, we present a novel approach for mathematical modeling of electrical conduction in cardiac tissue composed of myocytes, fibroblasts, and the extracellular space. The model is an extension of established cardiac bidomain models, which include a description of intra-myocyte and extracellular conductivities, currents and potentials in addition to transmembrane voltages of myocytes. Our extension added a description of fibroblasts, which are electrically coupled with each other and with myocytes. We applied the extended model in exemplary computational simulations of plane waves and conduction in a thin tissue slice assuming an isotropic conductivity of the intra-fibroblast domain. In simulations of plane waves, increased myocyte-fibroblast coupling and fibroblast-myocyte ratio reduced peak voltage and maximal upstroke velocity of myocytes as well as amplitudes and maximal downstroke velocity of extracellular potentials. Simulations with the thin tissue slice showed that inter-fibroblast coupling affected rather transversal than longitudinal conduction velocity. Our results suggest that fibroblast coupling becomes relevant for small intra-myocyte and/or large intra-fibroblast conductivity. In summary, the study demonstrated the feasibility of the extended bidomain model and supports the hypothesis that fibroblasts contribute to cardiac electrophysiology in various manners.

Abstract:

BACKGROUND AND PURPOSE: Atomoxetine is a selective noradrenaline reuptake inhibitor, recently approved for the treatment of attention-deficit/hyperactivity disorder. So far, atomoxetine has been shown to be well tolerated, and cardiovascular effects were found to be negligible. However, two independent cases of QT interval prolongation, associated with atomoxetine overdose, have been reported recently. We therefore analysed acute and subacute effects of atomoxetine on cloned human Ether-a-Go-Go-Related Gene (hERG) channels. EXPERIMENTAL APPROACH: hERG channels were heterologously expressed in Xenopus oocytes and in a human embryonic kidney cell line and hERG currents were measured using voltage clamp and patch clamp techniques. Action potential recordings were made in isolated guinea-pig cardiomyocytes. Gene expression and channel surface expression were analysed using quantitative reverse transcriptase polymerase chain reaction, Western blot and the patch clamp techniques. KEY RESULTS: In human embryonic kidney cells, atomoxetine inhibited hERG current with an IC(50) of 6.3 micromol.L(-1). Development of block and washout were fast. Channel activation and inactivation were not affected. Inhibition was state-dependent, suggesting an open channel block. No use-dependence was observed. Inhibitory effects of atomoxetine were attenuated in the pore mutants Y652A and F656A. In guinea-pig cardiomyocytes, atomoxetine lengthened action potential duration without inducing action potential triangulation. Overnight incubation with high atomoxetine concentrations resulted in a decrease of channel surface expression. CONCLUSIONS AND IMPLICATIONS: Whereas subacute effects of atomoxetine seem negligible under therapeutically relevant concentrations, hERG channel block should be considered in cases of atomoxetine overdose and when administering atomoxetine to patients at increased risk for the development of acquired long-QT syndrome.

Abstract:

The motion of the heart is a major challenge for cardiac imaging using CT. A novel approach to decrease motion blur and to improve the signal to noise ratio is motion compensated reconstruction which takes motion vector fields into account in order to correct motion. The presented work deals with the determination of local motion vector fields from high contrast objects and their utilization within motion compensated filtered back projection reconstruction. Image registration is applied during the quiescent cardiac phases. Temporal interpolation in parameter space is used in order to estimate motion during strong motion phases. The resulting motion vector fields are during image reconstruction. The method is assessed using a software phantom and several clinical cases for calcium scoring. As a criterion for reconstruction quality, calcium volume scores were derived from both, gated cardiac reconstruction and motion compensated reconstruction throughout the cardiac phases using low pitch helical cone beam CT acquisitions. The presented technique is a robust method to determine and utilize local motion vector fields. Motion compensated reconstruction using the derived motion vector fields leads to superior image quality compared to gated reconstruction. As a result, the gating window can be enlarged significantly, resulting in increased SNR, while reliable Hounsfield units are achieved due to the reduced level of motion artefacts. The enlargement of the gating window can be translated into reduced dose requirements.

Abstract:

A ray-based approach that models the geometric mapping properties of a flat optical detector based on a microlens array is presented. The investigated optical detector substitutes a single-aperture lens optic for planar and tomographic data acquisition in space-constrained small-animal imaging applications. The formalism implements forward mapping of a three-dimensional object volume onto a two-dimensional sensor surface as well as the backprojection (inverse mapping) of acquired sensor data sets. The object focus distance is the sole free parameter for the inverse mapping. By variation of the object focus distance, arbitrary object surface areas within the computed object images can be focused. The inverse mapping algorithm was applied to an experimentally acquired sensor data set from a three-dimensional phantom. The results are compared with focal point image formation.

Abstract:

Cardiac tissue exhibits spatially heterogeneous electrophysiological properties. In cardiac diseases, these properties also change in time. This study introduces a framework to investigate their role in cardiac ischemia using mathematical modeling and computational simulations at cellular and tissue level. Ischemia was incorporated by reproducing effects of hyperkalemia, acidosis, and hypoxia with a human electrophysiological model. In tissue, spatial heterogeneous ischemia was described by central ischemic (CIZ) and border zone. Anisotropic conduction was simulated with a bidomain approach in an anatomical ventricle model including realistic fiber orientation and transmural, apico-basal, and interventricular electrophysiological heterogeneities. A model of electrical conductivity in a human torso served for ECG calculations. Ischemia increased resting but reduced peak voltage, action potential duration, and upstroke velocity. These effects were strongest in subepicardial cells. In tissue, conduction velocity decreased towards CIZ but effective refractory period increased. At 10 min of ischemia 19% of subepi- and 100% of subendocardial CIZ cells activated with a delay of 34.6+/-7.8 ms and 55.9+/-18.8 ms, respectively, compared to normal. Significant ST elevation and premature T wave end appeared only with the subepicardial CIZ. The model reproduced effects of ischemia at cellular and tissue level. The results suggest that the presented in silico approach can complement experimental studies, e.g., in understanding the role of ischemia or the onset of arrhythmia.

Abstract:

In open heart surgery the patient is connected to a heart-lung machine which pumps and oxygenizes the blood. The body core temperature is reduced by cooling the blood in a heat exchanger to reduce oxygen consumption of the tissues and so protect organs from hypoxia. Monitoring of vital parameters is crucial for safety of the patient. However, only little information is available from direct measurement. Models of haemodynamics and heat exchange in the human body are presented in this paper which provide the perfusionist with detailed data on blood flow and temperature in regions of the body which cannot be accessed by measurement devices. Simulation is performed on a real-time hardware platform which receives measured signals from the heart-lung machine via a serial interface.

Abstract:

Niflumic acid [2-((3-(trifluoromethyl)phenyl)amino)-3-pyridinecarboxylic acid, NFA] is a nonsteroidal anti-inflammatory drug that also blocks or modulates the gating of a wide spectrum of ion channels. Here we investigated the mechanism of channel activation by NFA on ether-a-go-go-related gene (ERG) K(+) channel subtypes expressed in Xenopus laevis oocytes using two-electrode voltage-clamp techniques. NFA acted from the extracellular side of the membrane to differentially enhance ERG channel currents independent of channel state. At 1 mM, NFA shifted the half-point for activation by -6, -18, and -11 mV for ERG1, ERG2, and ERG3 channels, respectively. The half-point for channel inactivation was shifted by +5 to +9 mV by NFA. The structural basis for the ERG subtype-specific response to NFA was explored with chimeric channels and site-directed mutagenesis. The molecular determinants of enhanced sensitivity of ERG2 channels to NFA were isolated to an Arg and a Thr triplet in the extracellular S3-S4 linker.

Abstract:

A 3-D reconstruction of the coronary arteries offers great advantages in the diagnosis and treatment of cardiovascular disease, compared to 2-D X-ray angiograms. Besides improved roadmapping, quantitative vessel analysis is possible. Due to the heart's motion, rotational coronary angiography typically provides only 5-10 projections for the reconstruction of each cardiac phase, which leads to a strongly undersampled reconstruction problem. Such an ill-posed problem can be approached with regularized iterative methods. The coronary arteries cover only a small fraction of the reconstruction volume. Therefore, the minimization of the mbiL(1) norm of the reconstructed image, favoring spatially sparse images, is a suitable regularization. Additional problems are overlaid background structures and projection truncation, which can be alleviated by background reduction using a morphological top-hat filter. This paper quantitatively evaluates image reconstruction based on these ideas on software phantom data, in terms of reconstructed absorption coefficients and vessel radii. Results for different algorithms and different input data sets are compared. First results for electrocardiogram-gated reconstruction from clinical catheter-based rotational X-ray coronary angiography are presented. Excellent 3-D image quality can be achieved.

Abstract:

The quality of three-dimensional (3D) reconstructions of the coronary arteries from rotational coronary angiography depends on the selected phase point. Inconsistencies in the projection data, due to heart motion, degrade the image quality. Here, a method for the automatic selection of the optimum phase points for reconstruction is presented.The method aims at determining heart phases with minimum inconsistency of the motion state in the selected projection data. This is achieved by calculating an error measure which describes the inconsistency of the vessel centerline geometry in three dimensions for all cardiac phases. The phases with minimum inconsistency are then selected as optimum reconstruction phases. The method's feasibility was tested on 22 clinical cases. One late-diastolic and one end-systolic optimum phase were determined automatically for each case. For comparison, three observers visually determined the optimum phases.Overall, 82% of the 44 automatically determined phases delivered optimum image quality, only 5% showed considerably lower quality than the visually determined optimum phase. For all 22 cases at least one of the two automatically determined phases yielded optimum quality.In a first test the method proved to robustly determine optimum reconstruction phase points.

Abstract:

Three-dimensional reconstruction of coronary arteries can be performed during x-ray-guided interventions by gated reconstruction from a rotational coronary angiography sequence. Due to imperfect gating and cardiac or breathing motion, the heart's motion state might not be the same in all projections used for the reconstruction of one cardiac phase. The motion state inconsistency causes motion artefacts and degrades the reconstruction quality. These effects can be reduced by a projection-based 2D motion compensation method. Using maximum-intensity forward projections of an initial uncompensated reconstruction as reference, the projection data are transformed elastically to improve the consistency with respect to the heart's motion state. A fast iterative closest-point algorithm working on vessel centrelines is employed for estimating the optimum transformation. Motion compensation is carried out prior to and independently from a final reconstruction. The motion compensation improves the accuracy of reconstructed vessel radii and the image contrast in a software phantom study. Reconstructions of human clinical cases are presented, in which the motion compensation substantially reduces motion blur and improves contrast and visibility of the coronary arteries.

Abstract:

BACKGROUND: Genetic predisposition is believed to be responsible for most clinically significant arrhythmias; however, suitable genetic animal models to study disease mechanisms and evaluate new treatment strategies are largely lacking. METHODS AND RESULTS: In search of suitable arrhythmia models, we isolated the zebrafish mutation reggae (reg), which displays clinical features of the malignant human short-QT syndrome such as accelerated cardiac repolarization accompanied by cardiac fibrillation. By positional cloning, we identified the reg mutation that resides within the voltage sensor of the zebrafish ether-à-go-go-related gene (zERG) potassium channel. The mutation causes premature zERG channel activation and defective inactivation, which results in shortened action potential duration and accelerated cardiac repolarization. Genetic and pharmacological inhibition of zERG rescues recessive reg mutant embryos, which confirms the gain-of-function effect of the reg mutation on zERG channel function in vivo. Accordingly, QT intervals in ECGs from heterozygous and homozygous reg mutant adult zebrafish are considerably shorter than in wild-type zebrafish. CONCLUSIONS: With its molecular and pathophysiological concordance to the human arrhythmia syndrome, zebrafish reg represents the first animal model for human short-QT syndrome.

Abstract:

Atrial fibrillation (AF) is a common cardiac disease of genuine clinical concern with high rates of morbidity, leading to major personal and National Health Service costs. Computer modelling of AF using biophysically detailed cellular models with realistic 3D anatomical geometry allows investigation of the underlying ionic mechanisms in far more detail than with experimental physiology. We have developed a 3D virtual human atrium that combines detailed cellular electrophysiology including ion channel kinetics and homeostasis of ionic concentrations with anatomical details. The segmented anatomical structure and the multi- variable nature of the system make the 3D simulations of AF computationally large and intensive.

Abstract:

Velocity of electrical conduction in cardiac tissue is a function of mechanical strain. Although strain-modulated velocity is a well established finding in experimental cardiology, its underlying mechanisms are not well understood. In this work, we summarized potential factors contributing to strain-velocity relationships and reviewed related experimental and computational studies. We presented results from our experimental studies on rabbit papillary muscle, which supported a biphasic relationship of strain and velocity under uni-axial straining conditions. In the low strain range, the strain-velocity relationship was positive. Conduction velocity peaked with 0.59 m/s at 100% strain corresponding to maximal force development. In the high strain range, the relationship was negative. Conduction was reversibly blocked at 118+/-1.8% strain. Reversible block occurred also in the presence of streptomycin. Furthermore, our studies revealed a moderate hysteresis of conduction velocity, which was reduced by streptomycin. We reconstructed several features of the strain-velocity relationship in a computational study with a myocyte strand. The modeling included strain-modulation of intracellular conductivity and stretch-activated cation non-selective ion channels. The computational study supported our hypotheses, that the positive strain-velocity relationship at low strain is caused by strain-modulation of intracellular conductivity and the negative relationship at high strain results from activity of stretch-activated channels. Conduction block was not reconstructed in our computational studies. We concluded this work by sketching a hypothesis for strain-modulation of conduction and conduction block in papillary muscle. We suggest that this hypothesis can also explain uni-axially measured strain-conduction velocity relationships in other types of cardiac tissue, but apparently necessitates adjustments to reconstruct pressure or volume related changes of velocity in atria and ventricles

Abstract:

Ablation strategies to prevent episodes of paroxysmal atrial fibrillation (AF) have been subject to many clinical studies. The issues mainly concern pattern and transmurality of the lesions. This paper investigates ten different ablation strategies on a multilayered 3-D anatomical model of the atria with respect to 23 different setups of AF initiation in a biophysical computer model. There were 495 simulations carried out showing that circumferential lesions around the pulmonary veins (PVs) yield the highest success rate if at least two additional linear lesions are carried out. The findings compare with clinical studies as well as with other computer simulations. The anatomy and the setup of ectopic beats play an important role in the initiation and maintenance of AF as well as the resulting therapy. The computer model presented in this paper is a suitable tool to investigate different ablation strategies. By including individual patient anatomy and electrophysiological measurement, the model could be parameterized to yield an effective tool for future investigation of tailored ablation strategies and their effects on atrial fibrillation.

Abstract:

With scanning confocal microscopy we obtained three-dimensional (3D) reconstructions of the transverse tubular system (t-system) of rabbit ventricular cells. We accomplished this by labeling the t-system with dextran linked to fluorescein or, alternatively, wheat-germ agglutinin conjugated to an Alexa fluor dye. Image processing and visualization techniques allowed us to reconstruct the t-system in three dimensions. In a myocyte lying flat on a coverslip, t-tubules typically progressed from its upper and lower surfaces. 3D reconstructions of the t-tubules also suggested that some of them progressed from the sides of the cell. The analysis of single t-tubules revealed novel morphological features. The average diameter of single t-tubules from six cells was estimated to 448172nm (mean SD, number of t-tubules 348, number of cross sections 5323). From reconstructions we were able to identify constrictions occurring every 1.871.09m along the principal axis of the tubule. The cross-sectional area of these constrictions was reduced to an average of 57.727.5% (number of constrictions 170) of the adjacent local maximal areas. Principal component analysis revealed flattening of t-tubular cross sections, confirming findings that we obtained from electron micrographs. Dextran- and wheat-germ agglutinin-associated signals were correlated in the t-system and are therefore equally good markers. The 3D structure of the t-system in rabbit ventricular myocytes seems to be less complex than that found in rat. Moreover, we found that t-tubules in rabbit have approximately twice the diameter of those in rat. We speculate that the constrictions (or regions between them) are sites of dyadic clefts and therefore can provide geometric markers for colocalizing dyadic proteins. In consideration of the resolution of the imaging system, we suggest that our methods permit us to obtain spatially resolved 3D reconstructions of the t-system in rabbit cells. We also propose that our methods allow us to characterize pathological defects of the t-system, e.g., its remodeling as a result of heart failure.

Abstract:

Markovian models of ion channels have proven useful in the reconstruction of experimental data and prediction of cellular electrophysiology. We present the stochastic Galerkin method as an alternative to Monte Carlo and other stochastic methods for assessing the impact of uncertain rate coefficients on the predictions of Markovian ion channel models. We extend and study two different ion channel models: a simple model with only a single open and a closed state and a detailed model of the cardiac rapidly activating delayed rectifier potassium current. We demonstrate the efficacy of stochastic Galerkin methods for computing solutions to systems with random model parameters. Our studies illustrate the characteristic changes in distributions of state transitions and electrical currents through ion channels due to random rate coefficients. Furthermore, the studies indicate the applicability of the stochastic Galerkin technique for uncertainty and sensitivity analysis of bio-mathematical models.

Abstract:

In this paper, a new method for QRS complex analysis and estimation based on principal component analysis (PCA) and polynomial fitting techniques is presented. Multi-channel ECG signals were recorded and QRS complexes were obtained from every channel and aligned perfectly in matrices. For every channel, the covariance matrix was calculated from the QRS complex data matrix of many heartbeats. Then the corresponding eigenvectors and eigenvalues were calculated and reconstruction parameter vectors were computed by expansion of every beat in terms of the principal eigenvectors. These parameter vectors show short-term fluctuations that have to be discriminated from abrupt changes or long-term trends that might indicate diseases. For this purpose, first-order poly-fit methods were applied to the elements of the reconstruction parameter vectors. In healthy volunteers, subsequent QRS complexes were estimated by calculating the corresponding reconstruction parameter vectors derived from these functions. The similarity, absolute error and RMS error between the original and predicted QRS complexes were measured. Based on this work, thresholds can be defined for changes in the parameter vectors that indicate diseases.

Abstract:

Reduced cardiac output, dysfunction of the conduction system, atrio-ventricular block, bundle branch blocks and remodeling of the chambers are results of congestive heart failure (CHF). Biventricular pacing as Cardiac Resynchronization Therapy (CRT) is a recognized therapy for the treatment of heart failure. The present paper investigates an automated non-invasive strategy to optimize CRT with respect to electrode positioning and timing delays based on a complex threedimensional computer model of the human heart. The anatomical model chosen for this study was the segmented data set of the Visible Man and a set of patient data with dilated ventricles and left bundle branch block. The excitation propagation and intra-ventricular conduction were simulated with Ten Tusscher electrophysiological cell model and adaptive cellular automaton. The pathologies simulated were a total atrioventricular (AV) block and a left bundle branch block (LBBB) in conjunction with reduced interventricular conduction velocities. The simulated activation times of different myocytes in the healthy and diseased heart model are compared in terms of root mean square error. The outcomes of the investigation show that the positioning of the electrodes, with respect to proper timing delay influences the efficiency of the resynchronization therapy. The proposed method may assist the surgeon in therapy planning.

Abstract:

Activation of human ether-a-go-go-related gene 1 (hERG1) K+ channels mediates cardiac action potential repolarization. Drugs that activate hERG1 channels represent a mechanism-based approach for the treatment of long QT syndrome, a disorder of cardiac repolarization associated with ventricular arrhythmia and sudden death. Here, we characterize the mechanisms of action and the molecular determinants for binding of RPR260243 [(3R,4R)-4-[3-(6-methoxy-quinolin-4-yl)-3-oxo-propyl]-1-[3-(2,3,5-trifluoro-phenyl)-prop-2-ynyl]-piperidine-3-carboxylic acid] (RPR), a recently discovered hERG1 channel activator. Channels were heterologously expressed in Xenopus laevis oocytes, and currents were measured by using the two-microelectrode voltage-clamp technique. RPR induced a concentration-dependent slowing in the rate of channel deactivation and enhanced current magnitude by shifting the voltage dependence of inactivation to more positive potentials. This mechanism was confirmed by demonstrating that RPR slowed the rate of deactivation, but did not increase current magnitude of inactivation-deficient mutant channels. The effects of RPR on hERG1 kinetics and magnitude could be simulated by reducing three rate constants in a Markov model of channel gating. Point mutations of specific residues located in the S4S5 linker or cytoplasmic ends of the S5 and S6 domains greatly attenuated or ablated the effects of 3 &#956;M RPR on deactivation (five residues), inactivation (one residue), or both gating mechanisms (four residues). These findings define a putative binding site for RPR and confirm the importance of an interaction between the S4S5 linker and the S6 domain in electromechanical coupling of voltage-gated K+ channels.

Abstract:

OBJECTIVE:The outward current flowing through the two-pore domain acid-sensitive potassium channel TASK-1 (I(TASK)) and its inhibition via alpha1-adrenergic receptors was studied in rat ventricular cardiomyocytes.METHODS:Quantitative RT-PCR experiments were carried out with mRNA from rat heart. Patch-clamp recordings were performed in isolated rat cardiomyocytes. TASK-1 and other K+ channels were expressed in Xenopus oocytes to study the pharmacological properties of a new TASK-1 channel blocker, A293.RESULTS:TASK-1 channels were found to be strongly expressed in rat heart. Analysis of the sensitivity of various K+ channels to A293 in Xenopus oocytes showed that at low concentrations A293 was a selective blocker of TASK-1 channels. I(TASK) in rat cardiomyocytes was dissected by application of A293 and by extracellular acidification to pH 6.0; it had an amplitude of approximately 0.30 pA/pF at +30 mV. Application of 200 nM A293 increased action potential duration (APD(50)) by 31+/-3% at a stimulation rate of 4 Hz. The plausibility of the effects of A293 on APD50 was checked with a mathematical action potential model. Application of the alpha1-adrenergic agonist methoxamine inhibited I(TASK) in Xenopus oocytes co-injected with cRNA for TASK-1 and alpha1A-receptors. In cardiomyocytes, methoxamine inhibited an outward current with characteristics similar to I(TASK). This effect was abolished in the presence of the alpha1A-antagonist 5-methyl-urapidil.CONCLUSIONS:Our results suggest that in rat cardiomyocytes I(TASK) makes a substantial contribution to the outward current flowing in the plateau range of potentials and that this current component can be inhibited via alpha1A-adrenergic receptors.

Abstract:

BackgroundMultiple wavelets and rotors are accused of maintaining atrial fibrillation (AF). However, snake-like excitation patterns have recently been observed in AF. So far, computer models have investigated AF in a simplified anatomical model. In this work, pulmonary vein firing is simulated to investigate the initiation and maintenance of AF in a realistic anatomical model.Methods and ResultsThirty-five ectopic foci situated around all pulmonary veins were simulated by a unidirectional conduction block. The excitation propagation was simulated by an adaptive cellular automaton on a realistic 3-dimensional atrial anatomy. Atrial fibrillation was initiated in 65.7% of the simulations. Stable excitation patterns were broken up in anatomically heterogeneous regions, creating a streak-like excitation pattern similar to snakes. Multiple wavelets and rotors could be observed in anatomically smooth areas at the atria's roofs.ConclusionsThe influence of macroscopic anatomical structures on the course of AF seems to play an important role in the excitation propagation in AF. The computer simulations indicate that multiple mechanisms contribute to the maintenance of AF.

Abstract:

An optimal electrode position, atrio-ventricular (AV) and interventricular (VV) delay in cardiac resynchronization therapy (CRT) improves its success. An optimization strategy does not yet exist. A computer model of the Visible Man and a patient heart was used to simulate an atrio-ventricular and a left bundle branch block with 0%, 20% and 40% reduction in interventricular conduction velocity, respectively. The minimum error between physiological excitation and pathology/therapy was automatically computed for 12 different electrode positions. AV and VV delay timing was adjusted accordingly. The results show the importance of individually adjusting the electrode position as well as the timing delays to the patient's anatomy and pathology, which is in accordance with current clinical studies. The presented methods and strategy offer the opportunity to carry out non-invasive, automatic optimization of CRT preoperatively. The model is subject to validation in future clinical studies.

Abstract:

OBJECTIVE: Optimization of cardiac resynchronization therapy (CRT) is still unsolved. It has been shown that optimal electrode position,atrioventricular (AV) and interventricular (VV) delays improve the success of CRT and reduce the number of non-responders. However, no automatic, noninvasive optimization strategy exists to date. METHODS: Cardiac resynchronization therapy was simulated on the Visible Man and a patient data-set including fiber orientation and ventricular heterogeneity. A cellular automaton was used for fast computation of ventricular excitation. An AV block and a left bundle branch block were simulated with 100%, 80% and 60% interventricular conduction velocity. A right apical and 12 left ventricular lead positions were set. Sequential optimization and optimization with the downhill simplex algorithm (DSA) were carried out. The minimal error between isochrones of the physiologic excitation and the therapy was computed automatically and leads to an optimal lead position and timing. RESULTS: Up to 1512 simulations were carried out per pathology per patient. One simulation took 4 minutes on an Apple Macintosh 2 GHz PowerPC G5. For each electrode pair an optimal pacemaker delay was found. The DSA reduced the number of simulations by an order of magnitude and the AV-delay and VV - delay were determined with a much higher resolution. The findings are well comparable with clinical studies. CONCLUSION: The presented computer model of CRT automatically evaluates an optimal lead position and AV-delay and VV-delay, which can be used to noninvasively plan an optimal therapy for an individual patient. The application of the DSA reduces the simulation time so that the strategy is suitable for pre-operative planning in clinical routine. Future work will focus on clinical evaluation of the computer models and integration of patient data for individualized therapy planning and optimization.

Abstract:

The anticholinergic antiparkinson drug orphenadrine is an antagonist at central and peripheral muscarinic receptors. Orphenadrine intake has recently been linked to QT prolongation and Torsade-de-Pointes tachycardia. So far, inhibitory effects on I Kr or cloned HERG channels have not been examined. HERG channels were heterologously expressed in a HEK 293 cell line and in Xenopus oocytes and HERG current was measured using the whole cell patch clamp and the double electrode voltage clamp technique. Orphenadrine inhibits cloned HERG channels in a concentration dependent manner, yielding an IC50 of 0.85 &#956;M in HEK cells. Onset of block is fast and reversible upon washout. Orphenadrine does not alter the half-maximal activation voltage of HERG channels. There is no shift of the half-maximal steady-state-inactivation voltage. Time constants of direct channel inactivation are not altered significantly and there is no use-dependence of block. HERG blockade is attenuated significantly in mutant channels lacking either of the aromatic pore residues Y652 and F656. In conclusion, we show that the anticholinergic agent orphenadrine is an antagonist at HERG channels. These results provide a novel molecular basis for the reported proarrhythmic side effects of orphenadrine

Abstract:

Elucidation of the cellular basis of arrhythmias in ion channelopathy disorders is complicated by the inherent difficulties in studying human cardiac tissue. Thus we used a computer modeling approach to study the mechanisms of cellular dysfunction induced by mutations in inward rectifier potassium channel (Kir)2.1 that cause Andersen-Tawil syndrome (ATS). ATS is an autosomal dominant disorder associated with ventricular arrhythmias that uncommonly degenerate into the lethal arrhythmia torsade de pointes. We simulated the cellular and tissue effects of a potent disease-causing mutation D71V Kir2.1 with mathematical models of human ventricular myocytes and a bidomain model of transmural conduction. The D71V Kir2.1 mutation caused significant action potential duration prolongation in subendocardial, midmyocardial, and subepicardial myocytes but did not significantly increase transmural dispersion of repolarization. Simulations of the D71V mutation at shorter cycle lengths induced stable action potential alternans in midmyocardial, but not subendocardial or subepicardial cells. The action potential alternans was manifested as an abbreviated QRS complex in the transmural ECG, the result of action potential propagation failure in the midmyocardial tissue. In addition, our simulations of D71V mutation recapitulate several key ECG features of ATS, including QT prolongation, T-wave flattening, and QRS widening. Thus our modeling approach faithfully recapitulates several features of ATS and provides a mechanistic explanation for the low frequency of torsade de pointes arrhythmia in ATS.

Abstract:

Experimental investigations of the nonlinear properties of superconducting niobium coplanar waveguide resonators are reported. The nonlinearity due to a current dependent kinetic inductance of the center conductor is strong enough to realize bifurcation of the nonlinear oscillator. When driven with two frequencies near the threshold for bifurcation, parametric amplification with a gain of +22.4 dB is observed.

Abstract:

Pyramidal GaAs structures on top of GaAs/AlAs distributed Bragg reflectors are investigated as candidates for true three-dimensional cavities with potentially low mode volume and high quality-factor. Different types of single and coupled resonators with base lengths of a few microns are realized using a combination of molecular-beam epitaxy, electron-beam lithography, and wet chemical etching. Embedded InGaAs quantum dots are utilized as light sources to verify the resonator modes. Furthermore, a spatially localized emission through the pyramid facets indicates the future possibility of coupling cavity modes to optical fibers. This could be interesting within the context of single photon emitters.

Abstract:

Aims This computational study examined the influence of fibre orientation on the electrical processes in the heart. In contrast to similar previous studies, human diffusion tensor magnetic resonance imaging measurements were used.Methods The fibre orientation was extracted from distinctive regions of the left ventricle. It was incorporated in a single tissue segment having a fixed geometry. The electrophysiological model applied in the computational units considered transmural heterogeneities. Excitation was computed by means of the monodomain model; the accompanying pseudo-electrocardiograms (ECGs) were calculated.Results The distribution of fibre orientation extracted from the same transversal section showed only small variations. The fibre information extracted from the equal circumferential but different longitudinal positions showed larger differences, mainly in the imbrication angle. Differences of the endocardial myocyte orientation mainly affected the beginning of the activation sequence. The transmural propagation was faster in areas with larger imbrication angles leading to a narrower QRS complex in pseudo-ECGs.Conclusion The model can be expanded to simulate electrophysiology and contraction in the whole heart geometry. Embedded in a torso model, the impact of fibre orientation on body surface ECGs and their relation to local pseudo-ECGs can be identified.

Abstract:

In dynamic magnetic resonance imaging (MRI) studies, the motion kinetics or the contrast variability are often hard to predict, hampering an appropriate choice of the image update rate or the temporal resolution. A constant azimuthal profile spacing (111.246 degrees), based on the Golden Ratio, is investigated as optimal for image reconstruction from an arbitrary number of profiles in radial MRI. The profile order is evaluated and compared with a uniform profile distribution in terms of signal-to-noise ratio (SNR) and artifact level. The favorable characteristics of such a profile order are exemplified in two applications on healthy volunteers. First, an advanced sliding window reconstruction scheme is applied to dynamic cardiac imaging, with a reconstruction window that can be flexibly adjusted according to the extent of cardiac motion that is acceptable. Second, a contrast-enhancing k-space filter is presented that permits reconstructing an arbitrary number of images at arbitrary time points from one raw data set. The filter was utilized to depict the T1-relaxation in the brain after a single inversion prepulse. While a uniform profile distribution with a constant angle increment is optimal for a fixed and predetermined number of profiles, a profile distribution based on the Golden Ratio proved to be an appropriate solution for an arbitrary number of profiles.

Abstract:

The paper is addressed to detect the parameters of a sphere-center coordinates and radius based on a stack of CT slices. It is proposing a new hierarchical Hough transform approach. In the first step, all slices are taken into consideration sequentially and a 2D accumulator array is used to obtain the coordinates (x"0,y"0), the projecting value of the sphere center into every X-Y-plane. In this step, also a new type of 2D Hough transform for circle or circular detection is proposed based on an effective point filtering. In the second step, the radii of the circles in the different slices are obtained using 1D accumulator arrays. In the last step, the coordinate z"0 and the radius R of the sphere are acquired using a 2D planar Hough transform based on the correlation between the radii of circles, the coordinates z of the slice and the sphere radius. The hierarchical Hough transform is applied to analyze the structure of femoral head of human hip joints. Compared to the established Hough transform techniques for 3D object detection, the hierarchical Hough transform reduces storage space and calculation time significantly and it has a good robustness to noise in the images.

Abstract:

Cardiac arrhythmia is currently investigated from two different points of view. One considers ECG bio-signal analysis and investigates heart rate variability, baroreflex control, heart rate turbulence, alternans phenomena, etc. The other involves building computer models of the heart based on ion channels, bio-domain models and forward calculations to finally reach ECG and body surface potential maps. Both approaches aim to support the cardiologist in better understanding of arrhythmia, improving diagnosis and reliable risk stratification, and optimizing therapy. This article summarizes recent results and aims to trigger new research to bridge the different views.

Abstract:

Streamline techniques are frequently applied for scientific visualization of two- and three-dimensional electric fields. Streamline distributions are expected to reflect important features of the underlying fields such as the locations of sources and sinks as well as variations of the field density. Streamline techniques fulfilling these demands in arbitrary fields are currently not developed.In this work, we present a heuristic technique, which aims at creating a linear relationship between a streamline distribution and the density of an underlying electric current field. The technique is based on a sequential optimization algorithm for placement of seed points of streamlines. In each step, a set of random trial seed points is created. Each point of the trial set is temporarily added to the set of best seed points. Streamlines are generated from the enhanced set and the fit of their distribution and the field density is determined. The best point is selected and added to the set of best seed points. The iteration ends after generation of a pre-given number of best seed points. Several examples illustrate results of this technique applied to electric current fields of small complexity and in more extensive cardiothoracic electric fields. Additionally, we characterized, with statistical studies, the influence of parameters of the algorithm on the relationship between streamline distribution and field density.

Abstract:

Investigating the mechanisms underlying the genesis and conduction of electrical excitation in the atria at physiological and pathological states is of great importance. To provide knowledge concerning the mechanisms of excitation, we constructed a biophysical detailed and anatomically accurate computer model of human atria that incorporates both structural and electrophysiological heterogeneities. The three-dimensional geometry was extracted from the visible female dataset. The sinoatrial node (SAN) and atrium, including crista terminalis (CT), pectinate muscles (PM), appendages (APG) and Bachmann's bundle (BB) were segmented in this work. Fibre orientation in CT, PM and BB was set to local longitudinal direction. Descriptions for all used cell types were based on modifications of the Courtemanche et al. model of a human atrial cell. Maximum conductances of Ito, IKr and ICa,L were modified for PM, CT, APG and atrioventricular ring to reproduce measured action potentials (AP). Pacemaker activity in the human SAN was reproduced by removing IK1, but including If, ICa,T, and gradients of channel conductances as described in previous studies for heterogeneous rabbit SAN. Anisotropic conduction was computed with a monodomain model using the finite element method. The transversal to longitudinal ratio of conductivity for PM, CT and BB was 1:9. Atrial working myocardium (AWM) was set to be isotropic. Simulation of atrial electrophysiology showed initiation of APs in the SAN centre. The excitation spread afterwards to the periphery near to the region of the CT and preferentially towards the atrioventricular region. The excitation extends over the right atrium along PM. Both CT and PM activated the right AWM. Earliest activation of the left atrium was through BB and excitation spread over to the APG. The conduction velocities were 0.6ms-1 for AWM, 1.2ms-1 for CT, 1.6ms-1 for PM and 1.1ms-1 for BB at a rate of 63bpm. The simulations revealed that bundles form dominant pathways for atrial conduction. The preferential conduction towards CT and along PM is comparable with clinical mapping. Repolarization is more homogeneous than excitation due to the heterogeneous distribution of electrophysiological properties and hence the action potential duration.

Abstract:

OBJECT: Multiple contrasts are often helpful for a comprehensive diagnosis. In 3D abdominal MRI, breath-hold techniques are preferred for single contrast acquisitions to avoid respiratory artifacts. In this paper, highly accelerated parallel MRI is used to acquire large 3D abdominal volumes with two different contrasts within a single breath-hold. MATERIAL AND METHODS: In vivo studies have been performed on six healthy volunteers, combining T (1)- and T (2)-weighted, gradient- or spin-echo based scans, as well as water/fat resolved imaging in a single breath-hold. These 3D scans were acquired with an acceleration factor of six, using a prototype 32-element receive array. RESULTS: The presented approach was tested successfully on all volunteers. The whole liver area was covered by a FOV of 350 x 250 x 200 mm(3) for all scans with reasonable spatial resolution. Arbitrary scan protocols generating different contrasts have been shown to be combinable in this single breath-hold approach. Good spatial correspondence with negligible spatial offset was achieved for all different scan combinations acquired in overall breath-hold times between 15 and 25 s. CONCLUSION: Enabled by highly parallel imaging technology, this study demonstrates the technical feasibility and the promising image quality of single breath-hold dual contrast MRI.

Abstract:

PURPOSE: To demonstrate a rapid MR technique that combines imaging and R2* mapping based on a single radial multi-gradient-echo (rMGE) data set. The technique provides a fast method for online monitoring of the administration of (super-)paramagnetic contrast agents as well as image-guided drug delivery. MATERIALS AND METHODS: Data are acquired using an rMGE sequence, resulting in interleaved undersampled radial k-spaces representing different echo times (TEs). These data sets are reconstructed separately, yielding a series of images with different TEs used for pixelwise R2* mapping. A fast numerical algorithm implemented on a real-time reconstruction platform provides online estimation of the relaxation rate R2*. Simultaneously the images are summed for the computation of a high-resolution image. RESULTS: Convenient high-resolution R2* maps of phantoms and the liver of a healthy volunteer were obtained. In addition to stable intrinsic baseline maps, the proposed technique provides particularly accurate results for the high relaxation rates observed during the presence of (super-)paramagnetic contrast agents. Assuming that the change in R2* is proportional to the concentration of the agent, the technique offers a rough estimate for dynamic dosage. CONCLUSION: The simultaneous online display of morphological and parametric information permits convenient, quantitative surveillance of contrast-agent administration.

Abstract:

In this work an optimization-based method of modeling the cardiac activity is presented. The method employs a personalized anatomical 3D model of the patients thorax provided by the segmentation of MRI data as well as an electrophysiological model of the heart.Cellular automaton is used to model the propagation of depolarization and repolarization fronts through the myocardium. The form of action potential (AP) curves was previously derived from the coupled myocardium cell models developed by Noble, Priebe-Beuckelmann and ten Tusscher. The results provided by these three cell models are compared.A series of body surface potential maps (BSPMs) is calculated, the signals on the nodes representing the electrodes are recorded, providing thus a simulated multichannel ECG. A root-mean-square of the difference between simulated and measured ECGs is taken as a criterion for optimization of heart model parameters.The method provides a time-dependent distribution of transmembrane voltages within the heart muscle of a patient.

Abstract:

The application of strong electrical stimuli is a common method used for terminating irregular cardiac behaviour. The study presents the influence of electrophysiological heterogeneity on the response of human hearts to electrical stimulation. The human electrophysiology was simulated using the ten Tusscher-Noble-Noble-Panfilov cell model. The anisotropic propagation of depolarisation in three-dimensional virtual myocardial preparations was calculated using bidomain equations. The research was carried out on different types of virtual cardiac wedge. The selection of the modelling parameters emphasises the influence of cellular electrophysiology on the response of the human myocardium to electrical stimulation. The simulations were initially performed on a virtual cardiac control model characterised by electrophysiological homogeneity. The second preparation incorporated the transmural electrophysiological heterogeneity characteristic of the healthy human heart. In the third model type, the normal electrophysiological heterogeneity was modified by the conditions of heart failure. The main currents responsible for repolarisation (Ito, IKs and IKI) were reduced by 25%. Successively, [Na+]i was increased by the regulation of the Na+-Ca2+ exchange function, and fibrosis was represented by decreasing electrical conductivity. Various electrical stimulation configurations were used to investigate the differences in the responses of the three different models. Monophasic and biphasic electrical stimuli were applied through rectangular paddles and needle electrodes. A whole systolic period was simulated. The distribution of the transmembrane voltage indicated that the modification of electrophysiological heterogeneity induced drastic changes during the repolarisation phase. The results illustrated that each of the heart failure conditions amplifies the modification of the response of the myocardium to electrical stimulation. Therefore a theoretical model of the failing human heart must incorporate all the characteristic features.

Abstract:

In this study the performance of a planar array for magnetic induction tomography (MIT) was investigated and the results of measurements to determine the precision and sensitivity of the sensor were undertaken. A planar-array MIT system utilizing flux-linkage minimization for the primary field has been constructed and evaluated. The system comprises 4 printed excitation coils of 4 turns which were shielded, 8 surface-mount inductors of inductance 10 microH as sensor, mounted such that in principle no primary-field flux threads them, and a calibration coil to produce a strong primary field. The excitation current was multiplexed via relays to drive the excitation and reference coils. The noise values were similar in real and imaginary components in the lower frequencies and the factor to which the primary field could be reduced was greatest in the nearest coil. Methods for determining the true real and imaginary components and for flux-linkage minimization for the primary field for variations in channel sensitivities are described and the results of measurements of the system's noise and drift are given. A SNR of 47 dB was observed at 4 MHz when a 0.3 Sm-1 saline filled tank of dimensions 20 cmx20 cmx10 cm was placed centrally over the array. Finally, images were reconstructed from measurements of saline samples in a free space background, with the samples moved past the array in 21 1 cm steps to emulate mechanical scanning of the array. The image reconstruction characteristics of the planar array in conjunction with the reconstruction technique employed are discussed.

Abstract:

A shortcoming of today's coronary magnetic resonance angiography (MRA) is its low total scan efficiency (<5%), as only small well-defined fractions of the respiratory (50%) and cardiac (10%) cycle are used for data acquisition. These precautions are necessary to prevent blurring and artifacts related to respiratory and cardiac motion. Hence, scan times range from 4 to 9 min, which may not be tolerated by patients. To overcome this drawback, an ECG-triggered, navigator-gated free breathing radial 3D balanced FFE sequence with intra-RR motion correction is investigated in this study. Scan efficiency is increased by using a long cardiac acquisition window during the RR interval. This allows the acquisition of a number of independent k-space segments during each cardiac cycle. The intersegment motion is corrected using a self-guided epicardial fat tracking procedure in a postprocessing step. Finally, combining the motion-corrected segments forms a high-resolution image. Experiments on healthy volunteers are presented to show the basic feasibility of this approach.

Abstract:

BACKGROUND: There are no published data showing the three-dimensional sequence of repolarization and the associated potential fields in the ventricles. Knowledge of the sequence of repolarization has medical relevance because high spatial dispersion of recovery times and action potential durations favors cardiac arrhythmias. In this study we describe measured and simulated 3-D excitation and recovery sequences and activation-recovery intervals (ARIs) (measured) or action potential durations (APDs) (simulated) in the ventricular walls.METHODS: We recorded from 600 to 1400 unipolar electrograms from canine ventricular walls during atrial and ventricular pacing at 350-450 ms cycle length. Measured excitation and recovery times and ARIs were displayed as 2-D maps in transmural planes or 3-D maps in the volume explored, using specially developed software. Excitation and recovery sequences and APD distributions were also simulated in parallelepipedal slabs using anisotropic monodomain or bidomain models based on the Lou-Rudy version 1 model with homogeneous membrane properties.RESULTS: Simulations showed that in the presence of homogeneous membrane properties, the sequence of repolarization was similar but not identical to the excitation sequence. In a transmural plane perpendicular to epicardial fiber direction, both activation and recovery pathways starting from an epicardial pacing site returned toward the epicardium at a few cm distance from the pacing site. However, APDs were not constant, but had a dispersion of approximately 14 ms in the simulated domain. The maximum APD value was near the pacing site and two minima appeared along a line perpendicular to fiber directions, passing through the pacing site. Electrical measurements in dog ventricles showed that, for short cycle lengths, both excitation and recovery pathways, starting from an epicardial pacing site, returned toward the epicardium. For slower pacing rates, pathways of recovery departed from the pathway of excitation. Highest ARI values were observed near the pacing site in part of the experiments. In addition, maps of activation-recovery intervals showed mid-myocardial clusters with activation-recovery intervals that were slightly longer than ARIs closer to the epi- or endocardium, suggesting the presence of M cells in those areas. Transmural dispersion of measured ARIs was on the order of 20-25 ms. Potential distributions during recovery were less affected by myocardial anisotropy than were excitation potentials

Abstract:

In magnetic induction tomography reducing the influence of the primary excitation field on the sensors can provide a significant improvement in SNR and/or allow the operating frequency to be reduced. For the purposes of imaging, it would be valuable if all, or a useful subset, of the detection coils could be rendered insensitive to the primary field for any excitation coil activated. Suitable schemes which have been previously suggested include the use of axial gradiometers and coil-orientation methods (Bx sensors). This paper examines the relative performance of each method through computer simulation of the sensitivity profiles produced by a single sensor, and comparison of reconstructed images produced by sensor arrays. A finite-difference model was used to determine the sensitivity profiles obtained with each type of sensor arrangement. The modelled volume was a cuboid of dimensions 50 cmx50 cmx12 cm with a uniform conductivity of 1 S m-1. The excitation coils were of 5 cm diameter and the detection coils of 5 mm diameter. The Bx sensors provided greater sensitivity than the axial gradiometers at all depths, other than on the surface layer of the volume. Images produced using a single-planar array were found to contain distortion which was reduced by the addition of a second array.

Abstract:

Parallel imaging techniques, which use several receive coils simultaneously, have been shown to enable a significant scan time reduction by subsampling k-space. Nevertheless, the data acquired with multiple coils in parallel exhibit some redundancy if the number of receive coils exceeds the subsampling factor. This redundancy leads to an overdetermination of the reconstruction problem, which is generally used to optimize the signal-to-noise ratio (SNR). However, it can yield further information about the quality of the reconstructed image, and can thus be used to identify and correct image artifacts. While some known approaches try to solve this problem in k-space, this study addresses it in the spatial domain and uses a modified SENSE reconstruction to reduce or completely remove ghost-type artifacts arising from processes such as motion or flow during data acquisition. Phantom and in vivo studies show significant improvements in image quality after correction, and serve as a basis for the discussion of the performance and limitations of this new approach.

Abstract:

Parallel imaging techniques, which in principle represent procedures of unfolding a reduced dataset, are well known and well established in MR imaging. This paper presents a further application of one particular reconstruction method, the SENSE algorithm, considered from a different point of view to remove potential foldover in conventional images acquired with multiple receive coils. Based on the coil sensitivity information, a body coverage map in the excited plane is calculated. This is used together with the measured raw data in a SENSE-type reconstruction to optimize the signal-to-noise ratio (SNR) as well as to remove foldover reliably by unfolding the image to a larger field of view. The reconstruction is performed automatically, without any user interaction, and does not affect data acquisition. Based on phantom and in vivo studies, which retain high image quality after the removal, the potential and limits of this approach are discussed, also taking into account future scanner hardware that will support a large number of parallel receiver channels.

Abstract:

The steady-state free precessing (SSFP) sequences, widely used in MRI today, acquire data only during a short fraction of the repetition time (TR). Thus, they exhibit a poor scan efficiency. In this paper, a novel approach to extending the acquisition window for a given TR without considerably modifying the basic sequence is explored for radial SSFP sequences. The additional data are primarily employed to increase the signal-to-noise ratio, rather than to improve the temporal resolution of the imaging. The approach is analyzed regarding its effect on the image SNR (signal to noise ratio) and the reconstruction algorithm. Results are presented for phantom experiments and cardiac functions studies. The gain in SNR is most notable in rapid imaging, since SNR enhancement for a constant repetition time may be used to compensate for the increase in noise resulting from angular undersampling.

Abstract:

Die kurzzeitige Kalzium-Akkumulation im myokardialen Gewebe bei isotoner Kontraktion ist von klinischer Bedeutung, da die Kalziumüberladung des Zytosols ursächlich an der Entstehung von Rhythmusstörungen beteiligt ist. Unklar ist derzeit, woher das überschüssige Kalzium stammt, ob aus intrazellulären Speichern, modifizierten Membranströmen oder von Seiten des kontraktilen Apparates. Ziel dieser Arbeit ist es zu klären, 1) an welcher Stelle in der Zelle das Kalzium freigesetzt wird und 2) ob das Ausmaß der Aktin-Myosin- Überlappung oder die Anzahl angelagerter Querbrücken die Pufferkapazität des kontraktilen Apparates für Kalzium mitbestimmen.Methoden Muskeltrabekel von 18 Patienten, die sich einer Herzoperation unterzogen, wurden untersucht. Während isometrischer Kontraktion der Präparate setzte kurzzeitige, sinusoidale Längenvibration (Frequenz: 125 Hz, Amplitude: 14% ML) ein. Besonderes Augenmerk lag hierbei auf der Reaktion des Kalzium-Signals (Indikator: Fura-2/AM). In einer zweiten Messreihe wurde dieser Versuch nach Zugabe von 10 mM BDM wiederholt, das bekannt ist für seine Kraftminderung durch Senkung der Kalzium-Sensitivität des Troponin C. Im dritten Versuchsblock wurde permanente Vibration angewandt.Ergebnisse 1) Induzierte Vibration reduzierte die aktive Kraft auf das Niveau der Ruhekraft. Zeitgleich kam es zu einer messbaren Zunahme des Kalziums im Zytosol. 2) Bei subtotaler Inhibition der elektromechanischen Kopplung durch BDM erreichte die aktive Kraft 10,4% der Kontrolle bei nahezu unverändertem Kalziumsignal (Kalzium-Zeit-Integral unter BDM: 91,9±3,2% der Kontrolle). Vibration führte unter diesen Bedingungen zu einer Kraftinhibition, ohne dass eine zusätzliche Kalzium-Freisetzung erreicht wurde. 3) Permanente Vibration reduzierte die Kraftamplitude des supramaximal aktivierten Präparates auf 28% (1,3±0,4 mN). Gleichzeitig stieg das Kalzium-Zeit-Integral auf 114,5±4,7%.Schlussfolgerung Die Befunde sprechen dafür, dass die Reduktion der Anzahl angelagerter Querbrücken beim Verkürzungsvorgang zu einer Verminderung der Empfindlichkeit des kontraktilen Apparates für Kalzium führt. Die verminderte Pufferkapazität des kontraktilen Apparates für Kalzium wird messbar durch eine Zunahme der Kalziumkonzentration im Zytosol, wenn bereits angelagerte Querbrücken durch Vibration mechanisch gelöst werden oder wenn die Anlagerung von Querbrücken durch permanente Vibration verhindert wird. Dieser Befund erklärt die klinische Beobachtung, dass die akute Nachlastsenkung häufig mit dem Auftreten von Rhythmusstörungen verbunden ist.

Abstract:

BACKGROUND: This article presents a study, which examines the effects of biphasic electrical shocks on human ventricular tissue. The effects of this type of shock are not yet fully understood. Animal experiments showed the superiority of biphasic shocks over monophasic ones in defibrillation. A mathematical computer simulation can increase the knowledge of human heart behavior. METHODS: The research presented in this article was done with different models representing a three-dimensional wedge of ventricular myocardium. The electrophysiology was described with Priebe-Beuckelmann model. The realistic fiber twist, which is specific to human myocardium was included. Planar electrodes were placed at the ends of the longest side of the virtual cardiac wedge, in a bath medium. They were sources of electrical shocks, which varied in magnitude from 0.1 to 5 V. In a second arrangement ring electrodes were placed directly on myocardium for getting a better view on secondary electrical sources. The electrical reaction of the tissue was generated with a bidomain model. RESULTS: The reaction of the tissue to the electrical shock was specific to the initial imposed characteristics. Depolarization appeared in the first 5 ms in different locations. A further study of the cardiac tissue behavior revealed, which features influence the response of the considered muscle. It was shown that the time needed by the tissue to be totally depolarized is much shorter when a biphasic shock is applied. Each simulation ended only after complete repolarization was achieved. This created the possibility of gathering information from all states corresponding to one cycle of the cardiac rhythm. CONCLUSIONS: The differences between the reaction of the homogeneous tissue and a tissue, which contains cleavage planes, reveals important aspects of superiority of biphasic pulses.

Abstract:

A shortcoming of current coronary MRA methods with thin-slab 3D acquisitions is the time-consuming examination necessitated by extensive scout scanning and precise slice planning. To improve ease of use and cover larger parts of the anatomy, it appears desirable to image the entire heart with high spatial resolution instead. For this purpose, an isotropic 3D-radial acquisition was employed in this study. This method allows undersampling of k-space in all three spatial dimensions, and its insensitivity to motion enables extended acquisitions per cardiac cycle. We present initial phantom and in vivo results obtained in volunteers that demonstrate large volume coverage with high isotropic spatial resolution. We were able to visualize all major parts of the coronary arteries retrospectively from the volume data set without compromising the image quality. The scan time ranged from 10 to 14 min during free breathing at a heart rate of 60 bpm, which is comparable to that of a thin-slab protocol comprising multiple scans for each coronary artery.

Abstract:

BACKGROUND: Previous studies suggest that auditory evoked potentials (AEP) may be used to monitor anaesthetic depth. However, during surgery and anaesthesia, the quality of AEP recordings may be reduced by artefacts. This can affect the interpretation of the data and complicate the use of the method. We assessed differences in expert ratings of the signal quality of perioperatively recorded AEPs. METHODS: Signal quality of 180 randomly selected AEP, recorded perioperatively during a European multicentre study, was rated independently by five experts as 'invalid' (0), 'poor' (1), or 'good' (2). Average (n=5) quality rating was calculated for each signal. Differences between quality ratings of the five experts were calculated for each AEP: inter-rater variability (IRV) was calculated as the difference between the worst and best classification of a signal. RESULTS: Average signal quality of 57% of the AEPs was rated as 'invalid', 39% as 'poor', and only 4% as 'good'. IRV was 0 in only 6%, 1 in 62%, and 2 in 32% of the AEP, that is in 32% one expert said signal quality was good, whereas a different expert thought the identical signal was invalid. CONCLUSIONS: There is poor agreement between experts regarding the signal quality of perioperatively recorded AEPs and, as a consequence, results obtained by one expert may not easily be reproduced by a different expert. This limits the use of visual AEP analysis to indicate anaesthetic depth and may affect the comparability of AEP studies, where waveforms were analysed by different experts. An objective automated method for AEP analysis could solve this problem.

Abstract:

Computer models of the electrophysiological processes in the human heart become increasingly precise and detailed. The dream of supporting diagnosis of arrhythmias and planning of therapeutic interventions comes into reach. Recent progress in the field of cellular models (including e.g. pathological cases), in the field of coupled cell patches (including e.g. heterogeneity) and in the field of validation (including e.g. intracardial multi-channel recordings) are reported.

Abstract:

Numerical field calculations and experimental investigations were performed to examine the heating of the surface of human skin during the application of a new electrode design for the patient return electrode. The new electrode is characterised by an equipotential ring around the central electrode pads. A multi-layer thigh model was used, to which the patient return electrode and the active electrode were connected. The simulation geometry and the dielectric tissue parameters were set according to the frequency of the current. The temperature rise at the skin surface due to the flow of current was evaluated using a two-step numerical solving procedure. The results were compared with experimental thermographical measurements that yielded a mean value of maximum temperature increase of 3.4 degrees C and a maximum of 4.5 degrees C in one test case. The calculated heating patterns agreed closely with the experimental results. However, the calculated mean value in ten different numerical models of the maximum temperature increase of 12.5 K (using a thermodynamic solver) exceeded the experimental value owing to neglect of heat transport by blood flow and also because of the injection of a higher test current, as in the clinical tests. The implementation of a simple worst-case formula that could significantly simplify the numerical process led to a substantial overestimation of the mean value of the maximum skin temperature of 22.4 K and showed only restricted applicability. The application of numerical methods confirmed the experimental assertions and led to a general understanding of the observed heating effects and hotspots. Furthermore, it was possible to demonstrate the beneficial effects of the new electrode design with an equipotential ring. These include a balanced heating pattern and the absence of hotspots.

Abstract:

Mathematical models of cardiac anatomy and physics provide information, which help to understand structure and behavior of the heart. Miscellaneous cardiac phenomena can only be adequately described by combination of models representing different aspects or levels of detail. Coupling of these models necessitates the definition of appropriate interfaces. Adequateness and efficiency of interfaces is crucial for efficient application of the combined models.In this work an integrated model is presented consisting of several models interconnected by interfaces. The integrated model allows the reconstruction of macroscopic electro-mechanical processes in the heart. The model comprises a three-dimensional are of left ventricular anatomy represented as truncated ellipsoid. The integrated model includes electrophysiological, tension development and elastomechanical models of myocardium at levels of single cell, proteins, and tissue patches, respectively.The model is exemplified by simulations of extracorporated left ventricle of small mammals. These simulations yield temporal distributions of electrophysiological parameters as well as descriptions of electrical propagation and mechanical deformation. The simulations show characteristic macroscopic ventricular function resulting from the interplay between cellular electrophysiology, electrical excitation propagation, tension development, and mechanical deformation.

Abstract:

Computer models of the heart can improve the understanding of the electrophysiological processes in healthy and diseased heart. They become more and more important for detailled diagnosis of arrhythmias and for optimization of therapy. Models of myocardium cells known today are described - they are based on the properties of all relevant ion channels in the cell membrane. Then it is demonstrated, how many cells can be joined to form a cell patch and how finally the complete heart can be modelled. A simpler approach is using a so called cellular automaton that allows for a significant reduction of calculation time while sacrifying some accordance to reality. Adaptive cellular automatons allow for a fast simulation with acceptable accuracy. Using them some results were gained for the simulation of typical arrhythmias, in the field of validation using an animal model and for therapy planning with RF-ablation.

Abstract:

The measurement of the surface-EMG during electrical stimulation requires the suppression of the stimulus pulse close to the source. This is necessary because of the discharge currents spreading within the human body caused by the stimulation pulse and the drift effects at the electrodes distorting the EMG-signal. A measurement-system will be presented, which splits the EMG in a detection and a processing path. A special converter keeps the base line at zero level. The detection path sets the gain of the recording amplifier and identifies the stimulation pulse to control its suppression. The processing of the EMG is conducted in the main path way. By these means the EMG including M-wave is undistorted and unbiased presented. The results will be discussed taking the physiology relevance into account.

Abstract:

PURPOSE: To assess respiratory motion models for coronary magnetic resonance angiography (CMRA). In this study various motion models that describe the respiration-induced 3D displacements and deformations of the main coronary arteries were compared.MATERIALS AND METHODS: Multiple high-resolution 3D coronary MR images were acquired in healthy volunteers using navigator-based respiratory gating, each depicting the coronary vessels at different respiratory motion states. In the images representing the different inspiratory states the displacements and deformations of the main coronary vessels with respect to the end-expiratory state were determined, by means of elastic registration. Several correction models (superior-inferior (SI) translation, 3D translation, and 3D affine transformation) were tested and compared with respect to their ability to map a selected inspiratory to the end-expiratory motion state.RESULTS: 3D translation was found to be superior over SI translation, which is commonly used for prospective motion correction in CMRA. The 3D affine transformation was found to be the best correction model considered in this study. Furthermore, a large intersubject variability of the model parameters was observed.CONCLUSION: The results of this study indicate that a patient-adapted 3D correction model (3D translation or better 3D affine) will considerably improve prospective motion correction in CMRA.

Abstract:

Image processing was used as a fundamental tool to derive motion information from magnetic resonance (MR) images, which was fed back into prospective respiratory motion correction during subsequent data acquisition to improve image quality in coronary MR angiography (CMRA) scans. This reduces motion artifacts in the images and, in addition, enables the usage of a broader gating window than commonly used today to increase the scan efficiency. The aim of the study reported in this paper was to find a suitable motion model to be used for respiratory motion correction in cardiac imaging and to develop a calibration procedure to adapt the motion model to the individual patient. At first, the performance of three motion models [one-dimensional translation in feet-head (FH) direction, three-dimensional (3-D) translation, and 3-D affine transformation] was tested in a small volunteer study. An elastic image registration algorithm was applied to 3-D MR images of the coronary vessels obtained at different respiratory levels. A strong intersubject variability was observed. The 3-D translation and affine transformation model were found to be superior over the conventional FH translation model used today. Furthermore, a new approach is presented, which utilizes a fast model-based image registration to extract motion information from time series of low-resolution 3-D MR images, which reflects the respiratory motion of the heart. The registration is based on a selectable global 3-D motion model (translation, rigid, or affine transformation). All 3-D MR images were registered with respect to end expiration. The resulting time series of model parameters were analyzed in combination with additionally acquired motion information from a diaphragmatic MR pencil-beam navigator to calibrate the respiratory motion model. To demonstrate the potential of a calibrated motion model for prospective motion correction in coronary imaging, the approach was tested in CMRA examinations in five volunteers.

Abstract:

BACKGROUND: Middle latency auditory evoked responses (MLAER) as a measure of depth of sedation are critically dependent on data quality and the analysis technique used. Manual peak labeling is subject to observer bias. This study investigated whether a user-independent index based on wavelet transform can be derived to discriminate between awake and unresponsive states during propofol sedation. METHODS: After obtaining ethics committee approval and written informed consent, 13 volunteers and 40 patients were studied. In all subjects, propofol was titrated to loss of response to verbal command. The volunteers were allowed to recover, then propofol was titrated again to the same end point, and subjects were finally allowed to recover. From three MLAER waveforms at each stage, latencies and amplitudes of peaks Pa and Nb were measured manually. In addition, wavelet transform for analysis of MLAER was applied. Wavelet transform gives both frequency and time information by calculation of coefficients related to different frequency contents of the signal. Three coefficients of the so-called wavelet detail level 4 were transformed into a single index (Db3d4) using logistic regression analysis, which was also used for calculation of indices for Pa, Nb, and Pa/Nb latencies. Prediction probabilities for discrimination between awake and unresponsive states were calculated for all MLAER indices. RESULTS: During propofol infusion, subjects were unresponsive, and MLAER components were significantly depressed when compared with the awake states (P < 0.001). The wavelet index Db3d4 was positive for awake and negative for unresponsive subjects with a prediction probability of 0.92. CONCLUSION: These data show that automated wavelet analysis may be used to differentiate between awake and unresponsive states. The threshold value for the wavelet index allows easy recognition of awake versus unresponsive subjects. In addition, it is independent of subjective peak identification and offers the advantage of easy implementation into monitoring devices.

Abstract:

The implementation and first in vivo results of a novel coronary magnetic resonance angiography (MRA) protocol allowing simultaneous acquisition of multiple geometrically independent 3D imaging stacks are presented. Each imaging stack is acquired in a separate cardiac phase using an individual magnetization preparation and navigator-based gating and prospective motion correction. Each stack covers one of the main coronary vessels. Thus, an improvement of scan efficiency was achieved, which was used in this study to reduce total scan time at standard image quality. Experiments performed in healthy volunteers and in patients using a two-stack approach yielded a total scan time reduction of 50% with an image quality equivalent to standard single-stack coronary MRA.

Abstract:

Computer aided simulations of the heart provide knowledge for cardiologic diagnosis and therapy. A model of the myocardium is presented which allows the reconstruction of electrical and mechanical processes with inclusion of feedback mechanisms. The model combines detailed models of cellular electrophysiology and force development with models of the electrical current flow and the mechanical behavior of the myocardium. Results of simulations show the connection between the electrical excitation process and the following mechanical deformation in a three dimensional, anisotropic area of the myocardium. Keywords: Mechano-Electrical Feedback, Electro-Mechanical Feedback, Cellular Models, Electrophysiology, Excitation-Propagation

Abstract:

Mapping of electrical endocardial activity is an important task for cardiac diagnosis and surgical treatment planning. Different kinds of catheters measure this activity with a limited number of electrodes. In recent years an increasing number of mapping systems is used in clinical routine. Various systems have been introduced and discussed in literature. This work deals with the localization of catheter electrodes in the heart with advanced techniques of digital image processing. The catheters - developed by various enterprises - differ in shape, handling and amount of electrodes. They are specified and presented in detail. Digital image analysis techniques like filters, Fourier and Hough transformation build the background and basics for this work. The main part describes the methods for the detection of the electrodes and the catheter strings. With these methods, it is possible to setup computer models for each catheter. The computer models can be used e. g. in numerical field calculation together with medical tomographic datasets.

Abstract:

More than 20 years of research in imaging of bioelectric sources in the human heart have passed and a lot of effort has been devoted to the topic. In spite of that the method is not established in clinical practice but still just an interesting research topic of enthusiastic scientist. A review together with a comprehensive literature survey is given in this article. Recent developments and new trends are outlined.

Abstract:

Motion is one major problem of magnetic resonance imaging (MRI) of the coronary vessels. Despite of cardiac motion of the beating heart itself respiratory motion has to be considered (see MR movie of respiratory motion of the heart). Respiratory motion is commonly suppressed by gating techniques, which reduce scan efficiency. In principle modern MR scanners are able to correct those motion patterns prospectively, which can be described by a 3D affine transformation. A prospective motion correction approach could be used to increase the respiratory gating window and in consequence to reduce scan time. However, in order to achieve a sufficient correction the motion must be described quantitatively. In this initial study the respiratory motion of the heart (coronary vessels) was analysed and a new motion model described by an affine transformation was compared to two rigid motion models. The affine transformation model achieved a better fit (mean error < 1 mm for coronary vessels) than a rigid motion model describing translation in all directions (mean error < 2 mm) and a rigid motion model covering only superior-inferior motion (mean error <6 mm).

Abstract:

A model of the electromechanical behavior of a myocardial region is presented. The model combines an electrophysiological, a force development and an excitation propagation model. All of these models incorporate the effects of deformation of the myocardium. An extension of the traditional bidomain model for excitation propagation is proposed. The extension describes the stretch dependency of the conductivity tensor of the intra- and extracellular space and is constructed outgoing from physically motivated assumptions, which simplify the behavior of the conductivity tensor. The extension makes usage of the deformation gradient tensor, which is a foundation in the theory of continuums mechanics. The performed simulations illustrate some effects of myocardial electromechanical behavior.

Abstract:

Knowledge of the distribution of electrical fields in the human body is of importance for scientists, engineers and physicians. This paper shows one way to achieve this knowledge by numerical calculation based on macroscopic models of the human body. An anatomical model is created by preprocessing, segmentation and classification of the digital images within the Visible Man data set. Conductivity models are derived, which describe the distribution of electrical conductivity in the human body. A conductivity model is applied to solve an exemplary forward problem in electrophysiology, which consist of the calculation of the electrical field distribution arising from cardiac sources. The cardiac sources are obtained by a model of the excitation process within the heart. The calculation of electrical fields is carried out numerically by employing the finite difference method.

Abstract:

This paper describes the measurement of a data set used to create a three-dimensional (3-D) parametric model of atrial anatomy. A short introduction to porcine and human atrial anatomy is given and important anatomical differences are noted. The data acquisition techniques are described. A pig heart was arrested in diastole and perfusion fixed in-situ at physiological pressures with the chest open but the pericardium intact, then excised, cast and mounted. A six-degree-of-freedom measurement arm was used to measure three-dimensional epicardial surface geometry and fiber angles. An epicardial surface model was created using a computer aided design (CAD ) software program for reverse engineering. The model was used to direct the dissection of the heart into small tissue blocks from which endocardial fiber angles and wall thicknesses were measured. Tissue blocks were then cryo-sectioned for histology and the identification of conducting system structures. Figures and images illustrate the resulting surface model, the acquired fiber angles and wall thickness. This preliminary work provides a foundation for building a three-dimensional anatomically detailed model suitable as a mesh for computational analysis of atrial mechanics and electrophysiology.

Abstract:

This work deals with the simulation of the electrical cardiac excitation propagation based on anatomical models of the human heart and body. The generation of anatomical models applying different techniques of digital image processing to medical image data is described as well as the generation of electrophysiological models based on these anatomical models. Different spatial and temporal physical field distributions, e.g. the transmembrane potential, the current sources and the extracellular potentials, are calculated and visualized in sinus rhythm case as well as in pathological cases.

Abstract:

OBJECTIVE: To develop and test a method for standardized calibration of pulse oximeters. METHODS: A novel pulse oximeter calibration technique capable of simulating the behavior of real patients is discussed. It is based on an artificial finger with a variable spectral-resolved light attenuator in conjunction with an extensive clinical database of time-resolved optical transmission spectra of patients fingers in the wavelength range 600-1000 nm. The arterial oxygen saturation of the patients at the time of recording was derived by analyzing a corresponding blood sample with a CO-oximeter. These spectra are used to compute the modulation of the light attenuator which is attached to the artificial finger. This calibration method was tested by arbitrarily playing back recorded spectra to pulse oximeters and comparing their display to the value they displayed when the spectra were recorded. RESULTS: We were able to demonstrate that the calibrator could generate physiological signals which are accepted by a pulse oximeter. We also present some experience of playing back recorded patient spectra. The mean difference between the original reading of the pulse oximeters and the display when attached to the calibrator is 1.2 saturation points (displayed oxygen saturation SpO2) with a standard deviation of 1.9 saturation points. CONCLUSIONS: The tests have shown the capabilities of a spectral light modulator for use as a possible calibration standard for pulse oximeters. If some improvements of the current prototype can be achieved we conclude from the experience with the device that this novel concept for the calibration of pulse oximeters is feasible and that it could become an important tool for assessing the performance of pulse oximeters.

Abstract:

UNLABELLED: The electroencephalogram (EEG) and middle latency auditory evoked responses (MLAER) have been proposed for assessment of the depth of anesthesia. However, a reliable monitor of the adequacy of anesthesia has not yet been defined. In a multicenter study, we tested whether changes in the EEG and MLAER after a tetanic stimulus applied to the wrist could be used to predict subsequent movement in response to skin incision in patients anesthetized with 1 minimum alveolar anesthetic concentration (MAC) isoflurane in N2O. We also investigated whether the absolute values of any of these variables before skin incision was able to predict subsequent movement. After the induction of anesthesia with propofol and facilitation of tracheal intubation with succinylcholine, 82 patients received 1 MAC isoflurane (0.6%) in N2O 50% without an opioid or muscle relaxant. Spontaneous EEG and MLAER to auditory click-stimulation were recorded from a single frontoparietal electrode pair. MLAER were severely depressed at 1 MAC isoflurane. At least 20 min before skin incision, a 5-s tetanic stimulus was applied at the wrist, and the changes in EEG and MLAER were recorded. EEG and MLAER values were evaluated before and after skin incision for patients who did not move in response to tetanic stimulation. Twenty patients (24%) moved after tetanic stimulation. The changes in the EEG or MLAER variables were unable to predict which patients would move in response to skin incision. Preincision values were not different between patients who did and did not move in response to skin incision for any of the variables. MLAER amplitude increased after skin incision. We conclude that it is unlikely that linear EEG measures or MLAER variables can be of practical use in titrating isoflurane anesthesia to prevent movement in response to noxious stimulation. IMPLICATIONS: Reliable estimation of anesthetic adequacy remains a challenge. Changes in spontaneous or auditory evoked brain activity after a brief electrical stimulus at the wrist could not be used to predict whether anesthetized patients would subsequently move at the time of surgical incision.

Abstract:

BACKGROUND: The absorption of irrigation fluid during transurethral resection of the prostate (TURP) is determined primarily by hydrostatic pressure in the bladder and prostatic venous pressure. In comparison to spontaneously breathing patients, patients undergoing mechanical ventilation with positive pressure have a raised central venous pressure and a reduced venous return, both of which can influence intravascular absorption. The purpose of the prospective study was to compare the effects of general (GA) and spinal anaesthetic (SA) techniques on the perioperative absorption of irrigating fluid in patients undergoing TURP. METHODS: Forty patients undergoing TURP were randomised and assigned either to group GA or SA. Irrigating fluid absorption was traced by adding 1.5% (w/v) ethanol to the irrigating fluid. Perioperative blood ethanol concentration (BEC), haemoglobin concentration, haematocrit, serum sodium concentration and central venous pressure (CVP) were measured at 10-min intervals during TURP and at 30-min intervals while patients were recovering. Absorption routes were indexed by the BEC and changes in serum sodium concentrations. Where the BEC was greater than 0.05 mg.mL-1, absorption of irrigating fluid was assumed. For assessing the volume of irrigating fluid absorbed, the maximum BEC, the absorption rate, the area under the BEC curve (AUC), and the volumes calculated according to the Hahn nomogram (Volin) for each patient were taken into consideration. RESULTS: There were 15 cases of irrigating fluid absorption in patients receiving GA (75%), and 11 in those receiving SA (55%). CVP was significantly lower in spontaneously breathing patients with SA as compared to those with GA (P < 0.05). In patients with irrigating fluid absorption the maximum BEC (P < 0.02), as well as the rate of irrigant fluid absorption (P < 0.01), were significantly higher amongst patients receiving SA. In this group, the calculated area under the curve and the absorbed fluid volumes determined with the nomogram were significantly increased (P < 0.05). CONCLUSION: The absorption of irrigation fluid during the TURP is significantly more marked amongst spontaneously breathing patients with regional anaesthesia in comparison to patients undergoing general anaesthesia with positive pressure ventilation. The markedly lower central venous pressure before the start of irrigation should be considered as a possible cause of this effect.

Abstract:

BACKGROUND: The most common complication during percutaneous nephrolithotripsy (PNL) is the destruction of organ structures with extravasation of the irrigation fluid into the retroperitoneal space. Consequently, there is an increased risk of a urosepsis and a complicated therapeutic course. In this study we aimed to show that extravascular absorption could be differentiated from intravascular absorption due to their unique absorption characteristics, and that these characteristics enable a prediction of possible post-operative complications. METHODS: In a prospective study of 31 patients with PNL, ethanol was added to the irrigating fluid and blood ethanol concentration (BEC) was measured by gas chromatography during the endoscopic procedure and in the recovery room. Following the guidelines of Hahn, patients were divided into two groups: group EVA, in whom extravasation had occurred with subsequent absorption; group IVA, those with intravascular absorption. Patients' post-operative progress along with diagnoses of renal perforations or bleeding, or signs of infection or sepsis, were comprehensively listed. RESULTS: EVA was diagnosed in 19 cases, and IVA in 12 cases. Maximum BEC levels were achieved after 20 min (median) in the IVA group, and 75 min in the EVA group (P < 0.05). Apart from their significantly higher demand for opioids (P < 0.05), EVA patients had been hospitalised for a substantially and significantly longer period of time (P < 0.01). Although without statistical significance, there was a higher rate of peri-operatively confirmed complications and prolonged intensive therapeutic treatment in the extravasation group. CONCLUSION: Retroperitoneal extravasation can be identified by using ethanol monitoring during and after PNL. Afflicted patients require considerably longer hospitalisation, probably because of the additional injury to surrounding organ structures.

Abstract:

The imaging performance of metal plate/phosphor screens which are used for the creation of portal images in radiotherapy is investigated by using Monte Carlo simulations. To this end the modulation transfer function, the noise power spectrum and the detective quantum efficiency [DQE(f)] are calculated for different metals and phosphors and different thicknesses of metal and phosphor for a range of spatial resolutions. The interaction of x-rays with the metal plate/phosphor screen is modeled with the EGS4 electron gamma shower code. Optical transport in the phosphor is modeled by simulating scattering and reabsorption events of individual optical photons. It is shown that metals with a high atomic number perform better than lighter metals in maximizing the DQE(f). It is furthermore shown that the DQE(f) for the metal plate/phosphor screen alone is nearly x-ray quantum absorption limited up to spatial frequencies of 0.4 cycles/mm. In addition, it is argued that the secondary quantum sink of optical photons imposed by the optical chain (mirror, lenses and video camera) leads to a significant degradation of the signal-to-noise ratio at spatial frequencies which are most important for successful registration of portal images. Therefore, the conclusion is that a replacement of the optical chain by a flat array of photodiodes placed directly under the phosphor will lead to a substantial improvement in image quality of portal images.

Abstract:

Considering the fundamental difficulties to define the term 'depth of anaesthesia', a more feasible concept for assessment of 'adequacy of anaesthesia' will be explained. The basic requirements for a monitoring index are definite response, gradual scaling and independence from the anaesthetic technique used. Additionally the index should be predictive for appearance of clinical signs of an inadequate anaesthesia. Different signal-processing methods will be discussed to extract the relevant information from both the spontaneous and the evoked brain electrical activity. In this context well established methods like spectral analysis are investigated in combination with new and more sophisticated methods like bispectral analysis or wavelet decomposition. Since no single-parameter index has been defined for monitoring depth of anaesthesia, a set of EEG parameters may be more useful to take into account intra- and interindividual variability. In parallel to the description of the monitor concept, the investigation of neural nets and fuzzy techniques, in addition to or in substitution of conventional statistical methods, will be introduced. Examples are given for data quality assessment, parameter extraction and re-classification.

Abstract:

Thermography enables the measurement of patients skin temperature profiles without stress caused by direct contact of probes to the skin. In previous incubator studies, frontal recordings were made through a hole in the top wall of the incubator hood. Using this method it is not possible to record the lateral temperature gradient from the back to the abdomen of the infant (in supine position), which is due to very limited heat loss near the incubator mattress. In this study temperature recordings were made from a lateral position. For this purpose a new front door of the incubator (Draeger 8000) was designed, which replaced the standard front door during measurements. In a clinical study thermography was compared to temperature measurements by standard thermistors. The mean difference between thermography and thermistors was 0.16 degree C. These results verify the use of thermography for measuring skin temperature of preterm infants in incubators.

Abstract:

A prerequisite for the further improvement in the quality of warming therapy is an accurate knowledge of the interactions between the microclimate in warming therapy devices and the thermal balance of the infant. For generating this knowledge, thermal manikins can be helpful. Suitable models capable of also simulating evaporative heat loss in preterm infants have, however, not been available to date. A thermal manikin representing an infant weighing 530 g and capable of simulating convective, radiative and also evaporative heat loss has now been developed. It comprises an outer shell made of porous, anatomically shaped clay, and is divided into six compartments each of which can be heated individually. Water-filled Gore-Tex bags located immediately beneath the shell are provided to simulate evaporation. In a clinical study, temperature profiles of 8 very small preterm infants were measured thermographically. Measurements in the manikin showed that highly comparable temperature profiles with only minor differences could be obtained. Total heat and water losses by the manikin were in good agreement with clinical values. Using the model described here it is possible to simulate the heat exchange of premature infants under extreme and accurately reproducible environmental conditions. This manikin may thus serve as a tool for comparative studies, for the development of warming therapy equipment, or for training purposes.

Abstract:

The present paper examined the question as to the extent to which the taking of gas samples for the purpose of measuring the breath alcohol concentration (BAC) in the expired air of patients on artificial respiration is influenced by temperature and humidity. For this purpose a lung model standardized at different alcohol concentrations was used, in which the temperature (T: 25, 30 and 35 degrees C) and the relative humidity (RH: 50, 75 and 95%) were varied.

Abstract:

PURPOSE: There is controversy about relevant EEG signal changes indicating adequate or inadequate anaesthesia. Differences of drug-induced and nociceptive mediated signal changes have not been studied in detail. The present study investigates whether signal changes during decreases of depth of anaesthesia due to surgical stimulation depend on different isoflurane concentrations during sufentanil anaesthesia. METHODS: Following IRB approval and written informed consent 28 patients (ASA: I; age 43 +/- 11 y) scheduled for elective abdominal surgery were included in the study. Anaesthesia: propofol (2.0 mg/kg) and sufentanil (1.0 micrograms/kg). Following endotracheal intubation (vecuronium 0.1 mg/kg) patients were normoventilated (P(ET)CO2: 36-38 mmHg). Randomly assigned to steady-state anaesthesia (group 1: P(ET)Isoflurane 0.2%, (14n); group 2: P(ET)Isoflurane 0.6%, (14n) during the start of surgery. Monitoring: heart rate (HF), mean arterial blood pressure (MAP), P(ET)CO2, arterial oxygen saturation and rectal temperature. EEG (16 channels referenced to Cz; CATEEM, Medisyst, Linden) recorded 5 min before until 10 min after the start of surgery. EEG-analysis (FFT: 4s, 256/s, 0.45-35.0 Hz): topographical distribution of power spectral densities (delta, theta, alpha 1, and alpha 2). Artifact control: ECG and EOG. RESULTS: Surgical stimulation resulted in increases of MAP in both groups (p < 0.05 vs BL), whereas HR was only slightly affected in group 2 when compared with BL. Other variables except of EEG data did not change over time. In group 1 (0.2% isoflurane) surgical stimulation resulted in decreases of delta over the whole cortex (F2, C3, P3, O1) and in marked increases of alpha predominantly at central leads (C3)(p < 0.05 vs BL). In group 2 (0.6% isoflurane) nociceptive stimulation was associated with decreases of faster waves (alpha: F3)(p < 0.05 vs BL) and increases in delta at fronto-central areas (F3, C3)(p < 0.05 vs BL). CONCLUSIONS: EEG recordings are useful in assessing pharmacodynamic drug effects. In contrast, intraoperative EEG recordings have a low correlation to clinical signs of changes in the anaesthetic state. Previous studies demonstrate paradoxical EEG-arousal reactions during isoflurane anaesthesia. The present data suggest that classical or even paradoxical EEG arousal due to nociceptive stimulation may depend on the isoflurane concentration. It seems reasonable that the ascending reticular formation is functionally blocked by isoflurane in a dose-dependent manner.

Abstract:

In the last few years, radioactive stents has been proved to inhibit neointima formation. This paper describes the actual status of producing such radioactive stents. After a short discussion of the different radioisotopes suitable for radioactive stents, potential production methods are discussed. The ion beam implantation of P-32 applied at the Karlsruhe Research Centre shall be described in more detail.

Abstract:

In radiotherapy, portal images are used to ensure a correct patient position during every radiation session. A reliable on-line verification is of clinical interest to interrupt the radiation in time in case the patient is not at the right position. A great problem for successful image registration is the poor image quality of portal images. They are corrupted by noise and of very low contrast. A method directly based on the grey levels is not sufficient. Therefore a structure-based method was developed which is almost insensitive to distrubances (air bubbles, noise, slowly varying grey levels). In most cases the selection of a region of interest (ROI) can be omitted. Besides the automatical segmentation of the radiation field, only the structures relevant for matching the anatomy are enhanced by using a bandpass filter. It is possible to detect the maximum correlation between different image modalities reliably (simulator image, digitally reconstructed radiograph, portal image). By using Fast Fourier Transformation (FFT), the calculation time is smaller than five seconds, which enables a clinical on-line verification. We have matched 1139 pairs of images of different modalities and various regions of the body (pelvis, nasopharyngeal space, head, lung). The success rate is greater than 95%.

Abstract:

The noise of two integrated YBa2Cu3O7-SrTiO3-YBa2Cu3O7 multilayer magnetometers in static magnetic fields up to 110 µT is investigated: An inductively coupled magnetometer with integrated flux transformer and a multiloop magnetometer. In both samples, only a moderate increase of the low frequency flux noise is found in high fields, due to the high epitaxial quality of the involved multilayer films. So for moderately shielded or unshielded applications in the earth's magnetic field, high-quality integrated YBa2Cu3O7 magnetometers can be operated with low excess noise.

Abstract:

This paper is the extension of a detailed anatomical model (Sachse et al., 1996a) (Sachse et al., 1996b) with the three-dimensional orientation of skeletal muscle fibres (Figure 1). The orientation is interpolated basing on two sets with restrictions of different types. The first set consists of points for which the orientation is known. The second set consists of points with an assigned normal of orientation. These sets are created by detection with manual or automatic methods using techniques of digital image processing. The interpolation works iteratively employing the averaging orientations in the 6-neighbourhood. The average of neighbouring orientations is calculated by determination of their principal axis.

Abstract:

UNLABELLED: When looking for the possible cause of distortions in values measured for the determination of breath ethanol concentration (BEC) in artificially respirated patients, consideration must be given to the humidity and temperature of the gas examined. In the present study, the effects of humidified and warmed and of dry and cold air on the accuracy of a newly developed BEC measuring device, as compared to a reference model and to a conventional system, were examined in a lung model. METHODS: A temperature-regulated pediatric incubator was used containing a 10 I gas reservoir and a breath humidifier with temperature regulated water bath. This setup provided constant temperature and humidity in the gas examined during measurement period. In the 'expiration' the air was directed from the breath humidifier through a measuring unit via a 'mouthpiece' into the reference system (Alcotest 7110, Dräger Inc., Lübeck) and then out. The measuring unit consisted of sensors for the temperature and relative humidity, and of a connector for the three sample extraction systems (PES). PES I was the conventional system with a 100-cm gas-sample pipe (Alcomed 3010), PES II the newly developed system (AlcoMed 3011, both from Envitec, Wismar) with a 10-cm gas-sample pipe, and PES III with a 20-cm heated gas-sample pipe. During 'inspiration' 2 l of air was fed into the system to rinse the measuring unit and to fill the reservoir. 61 measurements were performed with dry and cold air, and 71 with humidified and warmed air, in the course of which the ethanol concentration was increased from 0 to 1.5/1000. Data were evaluated using regression analysis and the Bland & Altman method. RESULTS AND CONCLUSIONS: The constancy of the values set for temperature, relative humidity and absolute humidity in the lung model was given for all measurements. In the dry and cold air, the results from all three test systems coincided almost perfectly with the reference values. The measured BEC in the humidified and warmed air using sample-extraction systems II and III corresponded to a high degree with the reference, while in the case of PES I, only a moderate linear correlation was achieved. The temperature and humidity of the expired gas during artificial respiration influence the gas samples extracted for the purposes of BEC measurement. Newly developed sample-extraction systems II and III coincide with the reference system, even under respiration-simulated gas conditions.