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:

ECG imaging aims to reconstruct the cardiac electrical activity from non-invasive measurements of body surface potentials (BSP) by finding unique and physiologically meaningful solutions to the inverse problem of electrocardiography. This can be accomplished using regularization, which reduces the space of admissible solutions by demanding solution properties that are already known beforehand. Messnarz et. al. proposed a regularization scheme that requires transmembrane voltages (TMV) to not decrease over time. We suggest a generalization of this method that forces TMVs to decrease only slowly and as a result can also be applied to irregular cardiac activity. We first develop the method using a simplified spherical geometry and then show its benefit for imaging fibrillatory activity on a realistic geometry of the atria.

Abstract:

Cardiac arrhythmias such as atrial fibrillation occur frequently in industrialized countries. Radiofrequency ablation (RFA) is a standard treatment if drug therapy fails. This minimally invasive surgery aims at stabilizing the heart rhythm on a permanent basis. However, the procedure commonly needs to be repeated because of the high recurrence rate of arrhythmias. Non-transmural lesions as well as gaps within linear lesions are among the main problems during the RFA. The assessment of lesion formation is not adequate in state of the art procedures. Therefore, the aim of this study is to investigate the short-term reversibility of lesions using human electrograms recorded by a high-density mapping system during an electrophysiological study (EPS). A predefined measurement protocol was executed during the EPS in order to create three ablation points in the left atrium. Subsequently, after preprocessing the recorded signals, electrogram (EGM) paths were formed along the endocardial surface of the atrium. By analyzing changes of peak to peak amplitudes of unipolar EGMs before and after ablation, it was possible to distinguish lesion area and healthy myocardium. The peak to peak amplitudes of the EGMs decreased by 40-61% after 30 seconds of ablation. Furthermore, we analyzed the morphological changes of EGMs surrounding the lesion. High-density mapping data showed that not only the tissue, which had direct contact with the catheter tip during the RFA, but also the surrounding tissue was affected. This was demonstrated by low peak to peak amplitudes in large areas with a width of 14 mm around the center of the ablation lesion. After right pulmonary vein isolation, high-density mapping was repeated on the previous lesions. The outer region of RFA-treated tissue appears to recover as opposed to the central core of the ablation point. This observation suggests that the meaningfulness of an immediate remap after ablation during an EPS may lead the physician to false conclusions.

Abstract:

Atrial tachycardia and atrial flutter are frequent arrhythmia that occur spontaneously and after ablation of atrial fibrillation. Depolarization waves that differ significantly from sinus rhythm propagate across the atria with high frequency (typically 140 to 220 beats per minute). A detailed and personalized analysis of the spread of depolarization is imperative for a successful ablation therapy. Thus, catheters with several electrodes are employed to measure multichannel electrograms inside the atria. Here we propose a new concept for spatio-temporal analysis of multichannel electrograms during atrial tachycardia and atrial flutter. It is based on the calculation of simultaneously active areas. The method allows to identify atrial tachycardia and to automatically distinguish between subtypes of focal activity, micro-reentry and macro-reentry.

Abstract:

Background: Perimitral flutter commonly occurs following ablation of atrial fibrillation (AF) and can be cured by an anterior mitral line (AML). However, confirmation of bidirectional block can be challenging. Objective: We hypothesized that P-wave morphology and timing under left atrial appendage (LAA) pacing changes upon AML- block. Methods: We analyzed 129 consecutive patients (66±8 y, 64%male) who developed perimitral flutter after AF ablation. We designed ECG-criteria in a retrospective cohort (n=76) and analyzed them in a validation cohort (n=53). Results: Bidirectional AML-block was achieved in 110 patients (85%). For ablation performed during LAA-pacing without flutter (n=52), we found an immediate V1-jump (increase in LAA- stimulus to P-wave peak in lead V1) as a real-time marker of AML-block (V1-jump ≥30ms: sensitivity 95%, specificity 100%, PPV 100%, NPV 88%). Since 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 203ms indicating block (sensitivity 92%, specificity 84%, PPV 90%, NPV 87%). Furthermore, an initial negative P-wave portion in the inferior leads was observed, which was attenuated in case of additional cavotricuspid isthmus (CTI) ablation. Computational P-wave simulations provide mechanistic confirmation of these findings for diverse ablation scenarios (pulmonary vein isolation±AML±roof-line±CTI ablation). Conclusion: V1-jump and V1-delay are novel real-time ECG- criteria allowing fast and straightforward assessment of AML- block during ablation for perimitral flutter.

Abstract:

Background: For chronic kidney disease patients undergoing maintenance hemodialysis (HD), the risk to die from sudden cardiac death (SCD) is 14x higher compared to patients with a history of cardiovascular disease and normal kidney function. Traditional SCD risk factors cannot explain this high rate. Two recent human studies using implantable loop recorders surprisingly point towards bradycardia and asystole as the prevailing arrhythmias causing SCD in HD patients. This suggests a decisive role of the sinus node. Objective: To identify the effect of altered electrolyte levels (as systematically occurring in HD patients) on pacemaking in a computational model of human sinus node cells. Methods: We enhanced the Fabbri et al. model of human sinus node cells to account for the dynamic intracellular balance of all considered electrolytes. The model was exposed to clinically relevant extracellular electrolyte concentrations of potassium, sodium, and calcium to study their effect on spontaneous beating rate and underlying pacemaking mechanisms. The level of sympathetic stimulation was kept constant. Results: The beating rate showed a monotonic relationship with altered electrolyte concentrations starting from a baseline value of 72.5bpm. It increased with sodium (70.8-73.8bpm for [Na+]o from 120-150mM), with potassium (70.7-81.9bpm for [K+]o from 3-9mM), and most pronouncedly with calcium (33.5- 133.8bpm for [Ca2+]o from 0.8-3mM). The severe bradycardia under hypocalcemic conditions was due to hyperpolarized maximum diastolic potential and slower diastolic depolarization driven by attenuation of ICaT and INCX, the latter due to depletion of intracellular calcium. Conclusion: Our human computational study suggests that hypocalcemia causes a pronounced decrease of cellular sinus node pacing rate, which may be a relevant mechanism in HD patients. While increased sympathetic tone will likely compensate the lower basal beating rate, patients developing severe hypocalcaemia are at high risk to experience severe bradycardia and die from SCD during a sudden loss of sympathetic tone.

Abstract:

Contemporary surgical microscope systems have excellent optical properties but some desirable features re- main unavailable. The number of co-observers is currently re- stricted, by spatial and optical limitations, to only two. More- over, ergonomics poses are a problem: Current microscope systems impede free movement and sometimes demand that surgeons take uncomfortable postures over long periods of time. To rectify these issues, some companies developed surgi- cal microscope systems based on a streaming approach. These systems remove some of the limitations. Multi-observer po- sitions, for example, are not independent from each other, for example. In order to overcome the aforementioned limitations, we are currently developing an approach for the next genera- tion of surgical microscope: Namely the fully digital surgi- cal microscope, where the current observation system is re- placed with a camera array, allowing real-time 3D reconstruc- tion of surgical scenes and, consequently, the rendering of al- most unlimited views for multiple observers. These digital mi- croscopes could make the perspective through the microscope unnecessary allowing the surgeon to move freely and work in more comfortable postures. The requirements on the camera array in such a system have to be determined. For this purpose, we propose of estimation the minimal number of cameras and their positions needed for the 3D reconstruction of microsurgi- cal scenes. The method of estimation is based on the require- ments for the 3D reconstruction. Within the MATLAB simu- lation environment, we have developed a 3D model of a mi- crosurgical scene, used for the determination of the number of required cameras. In a next step a small, compact and cost- ef cient s ystem w ith f ew o pto-mechanical c omponents could be manufactured.

Abstract:

The segmentation and registration of structures are gaining importance due to the increasing demand of auto- mated image enhancement and understanding. Especially in medicine and life science, assistance systems could have a large impact on diagnosis, treatment and quality control. Dye driven procedures, such as uorescence imaging with Indocya- nine green (ICG), are nowadays indispensable because they enhance contrast, reveal structures and deliver the operator with important information. The contact free ICG angiography is providing the surgeon spatial and temporal information on blood ow w ithin a v essel. T he p rocessing o f t hose informa- tion is done manually or semi automated but is very helpful for the surgeon. Extending the degree of automatism, the amount of information processed and even augment or transfer it into another domain could deliver the operator useful support and improve surgical work ow. Using, analyzing and transferring those information from ICG-IR domain into the RGB domain is the focus of this project. We are introducing a vessel regis- tration method in the RGB domain driven by the spatial u- orescence behavior of the vessel in the ICG-IR domain. The method includes Superpixel based segmentation of the vessel in the ICG-IR domain, the spatial gradient based transfer and registration in the RGB domain and the continuous segmen- tation of the vessel in a RGB video. This paper show a proof of concept of the method. The results show an successful in- ter domain information transfer and registration of the vessel. Further tracking of the vessel over all frames is possible. Nev- ertheless limitations are revealed and discussed.

Abstract:

Image segmentation plays an increasingly important role in image processing. It allows for various applications including the analysis of an image for automatic image understanding and the integration of complementary data. During vascular surgeries, the blood flow in the vessels has to be checked constantly, which could be facilitated by a segmentation of the affected vessels. The segmentation of medical images is still done manually, which depends on the surgeon’s experience and is time-consuming. As a result, there is a growing need for automatic image segmentation methods. We propose an unsupervised method to detect the regions of no interest (RONI) in intraoperative images with low depth-of-field (DOF). The proposed method is divided into three steps. First, a color segmentation using a clustering algorithm is performed. In a second step, we assume that the regions of interest (ROI) are in focus whereas the RONI are unfocused. This allows us to segment the image using an edge-based focus measure. Finally, we combine the focused edges with the color RONI to determine the final segmentation result. When tested on different intraoperative images of aneurysm clipping surgeries, the algorithm is able to segment most of the RONI not belonging to the pulsating vessel of interest. Surgical instruments like the metallic clips can also be excluded. Although the image data for the validation of the proposed method is limited to one intraoperative video, a proof of concept is demonstrated.

Abstract:

The human heart is an organ of high complexity and hence, very challenging to simulate. To calculate the force developed by the human heart and therefore the tension of the muscle fibers, accurate models are necessary. The force generated by the cardiac muscle has physiologically imposed limits and depends on various characteristics such as the length, strain and the contraction velocity of the cardiomyocytes. Another characteristic is the activation time of each cardiomyocyte, which is a wave and not a static value for all cardiomyocytes. To simulate a physiologically correct excitation, the functionality of the cardiac simulation framework CardioMechanics was extended to incorporate inhomogeneous activation times. The functionality was then used to evaluate the effects of local activation times with two different tension models. The active stress generated by the cardiomyocytes was calculated by (i) an explicit function and (ii) an ode-based model. The results of the simulations showed that the maximum pressure in the left ventricle dropped by 2.3% for the DoubleHill model and by 5.3% for the Lumens model. In the right ventricle the simulations showed similar results. The maximum pressure in both the left and the right atrium increased using both models. Given that the simulation of the inhomogeneously activated cardiomyocytes increases the simulation time when used with the more precise Lumens model, the small drop in maximum pressure seems to be negligible in favor of a simpler simulation model.

Abstract:

The contraction of the heart is a complex process involving the interaction of the passive properties of the tissue and the active tension development, which is elicited by the electrical activation of the cells. In this study, the electro-mechanical delay (EMD) was investigated as well as its dependence on the length of the sarcomeres, which are the contractile units within the cell. EMD was defined as the time offset between the electrical activation of the cell and the time of maximal tension. On a simple bar geometry with unidirectional fibre orientation and a linear local activation time distribution, the EMD proved to be inhomogeneous. The contraction of the early activated regions caused an elongation of the sarcomere (stretch) in the neighbouring regions, which ware electrically activated at a later time. The tension in the stretched region reached twice the value of the cells in the not-stretched, early activated region . Furthermore, the EMD in the early electrically activated region was more than 0.2 s, which was about twice the EMD of the stretched regions. In conclusion, the stretched region developed higher tension within a shorter time interval compared to the early activated region. Future studies will investigate how the inhomogeneous EMD affects cardiac output.

Abstract:

Numerical modelling enables a quantitative evaluation of physiological and patho-physiological relationships within the human heart and the circulatory system. Surgical planning and optimisation of medical equipment using a virtual heart become possible by merging of empirical studies with physical and mathematical knowl- edge. These goals motivate a multi-physical coupling between electro-physiology, elasto-mechanics, blood flow and the circulatory system. In a first step a one-way coupling of all four relevant physical domains is considered. Simulation of electro- physiological excitation spread in conjunction with excitation contraction coupling yields the spatio-temporal distribution of cardiac active tension. This, as well as a closed loop model of the circulatory system, drive the continuum mechanics simulation of cardiac deformation and pressure, which in turn serve as a boundary condition for blood flow simulation. Physiological blood flow dynamics are dominated by the formation of a ring vortex that washes out the ven- tricles and thereby reduces the risk of thrombogenesis and flow stasis. This process is strongly affected by the heart valves. However, including the three dimensional leaflets and their interaction with the blood flow is computationally expensive. Further, the effort for construction is not negligible. Therefore, a simpler model is implemented as a first step. It comprises of three layers of porous cells that move with the valve plane and time dependently block or open the plane respectively. First results illustrate a high potential of the model to reliably reproduce the physiological vortex formation in the ventricles.

Abstract:

The sinoatrial node (SAN) is the normal pacemaker of the mammalian heart. Over several decades, a large amount of data on the ionic mechanisms underlying the spontaneous electrical activity of SAN pacemaker cells has been obtained, mostly in experiments on single cells isolated from rabbit SAN. This wealth of data has allowed the development of mathematical models of the electrical activity of rabbit SAN pacemaker cells. However, the translation of animal data/models to humans is not straightforward. Even less so for SAN pacemaker cells than working myocar- dial cells given the big di↵erence in their main output (i.e. pacing rate) between human and laboratory animals. The development of a comprehensive model of the electrical activity of a human SAN pacemaker cell strictly based on and constrained by the available electrophysiological data will be presented. We started from the Severi-DiFrancesco rabbit SAN model, which integrates the two principal mecha- nisms that determine the beating rate: the ”membrane clock” and ”calcium clock”. Several current formulations were updated based on available measurements. A set of parameters, for which no specific data were available, were automatically opti- mized to reproduce the measured AP and calcium transient data. The model was then validated by assessing the e↵ects of several mutations a↵ecting heart rate and rate modulation. Moreover, two recent applications of the model will be presented: i) We used our SAN AP computational model to assess the e↵ects of the inclu- sion of the small conductance K+ current (ISK) on the biomarkers that describe the AP waveform and calcium transient; ii) We analysed the e↵ect of altered elec- trolyte levels (as systematically occurring in hemodialysis patients) on pacemaking to investigate the possible mechanisms of the bradycardic sudden cardiac deaths pointed out by two recent human studies using implantable loop recorders.

Abstract:

Background: Noninvasive localization of premature ventricular complexes (PVCs) to guide ablation therapy is one of the emerging applications of electrocardiographic imaging (ECGI). Because of its increasing clinical use, it is essential to compare the many implementations of ECGI that exist to understand the specific characteristics of each approach. Objective: Our consortium is a community of researchers aiming to collaborate in the field of ECGI, and to objectively compare and improve methods. Here, we will compare methods to localize the origin of PVCs with ECGI. Methods: Our consortium hosts a repository of ECGI data on its website. For the current study, participants...

Abstract:

Despite extensive research, the mechanisms of atrial fibrillation are still not clear. The central scientific question is what are the necessary conditions for the induction and maintenance of atrial fibrillation. This thesis presents simulation-, clinical- and experimental- studies of atrial fibrillation beginning from simplified to complex models. Main topics are the understanding of influence parameters of signal recordings, understanding the impact of fibrosis on the development of AF sources, and the development of new methods and catheter designs for the detection of AF sources.

Abstract:

Atrial tachyarrhythmias such as atrial fibrillation (AFib) predispose to ventricular arrhythmias, sudden cardiac death and stroke. The complex and rapid atrial electrical activity makes it difficult to obtain detailed information on atrial activation during fibrillatory conditions. However, ectopic foci are often involved in initiating and sustaining AFib and therefore identifying the origin of atrial ectopic activity can help in diagnosis and treatment of AFib. Currently, invasive catheter mapping and ablation remains the cornerstone for the treatment of atrial arrhythmias. Non-invasive tools to guide electrophysiologists could significantly shorten catheter mapping procedures and may ultimately decrease the recurrence rate of ablations. Existing approaches are based on the analysis of the main characteristics of body body surface potential maps (BSPMs), such as the P-wave polarity, or rely on inverse reconstructions of the electric activity of the heart from BSPMs (ECG imaging). However, these methods have not yet shown to be accurate and reliable enough to be implemented in standard clinical practice. As the 12-lead electrocardiogram (ECG) is already routinely recorded in clinical settings, its use for classification of atrial ectopic foci into spatially differentiated atrial segments has been explored in this thesis. Atrial segments were defined with an automatic geodesic algorithm and a neural network (NN) was used for classification. Our simulation results with 8 atria-torso models show that ectopic foci with similar 12-lead ECG naturally cluster into differentiated atrial regions and that new patterns could correctly be classified into 29 segments with an accuracy of approximately 85%. Results also suggest that it is possible to predict whether the ECG signal belongs to the left atrium (LA) or the right atrium (RA) with an accuracy of 95%. If the classifier is applied to a new geometry that has not been used for training, however, the classification accuracy decreases drastically.

Abstract:

In western countries, stroke is the third-most widespread cause of death. 80% of all strokes are ischemic and caused by a cerebral thrombosis or an embolism. The mortality rate of ischemic strokes is about 25%, while 35–55% of affected patients experience permanent disability. Therapeutic hypothermia (TH) showed neuroprotective effect and can possibly decrease the stroke induced cerebral damage. Recently, an intracarotid cooling sheath was developed to induce local TH in the penumbra using the cooling effect of cranial blood flow via collaterals. Unfortunately, so far the control and regulation of the temporal and spatial cerebral temperature course is connected to invasive temperature measurements. Computational modeling provides unique opportunities to predict the resulting tempera- ture decrease of the brain tissue and could replace the invasive procedure. In this work a simplified brain model was generated to establish a cerebral temperature calculation using Pennes’ Bio-Heat-Equation and an existing cerebral hemodynamics model. In this context, an extensive literature research was performed and the terminal segments of the hemodynamics model were assigned to corresponding perfused brain tissue. For different degrees of stenosis in the MCA, TH was simulated using the intracarotid cooling method and local temperature curves and blood temperatures in the brain were analyzed. The lower the degree of stenosis, the faster and stronger a cooling could be achieved. Fur- thermore, the simulation results showed a significant influence of collateral flows on the penumbra cooling and the need to model different tissue types for simulation of the local brain temperature could be demonstrated. The anastomoses between the ACA and MCA had a cooling effect on the penumbra in addition to the blood flow from the internal carotid artery. The temperature model can be used in conjunction with the hemodynamic model to simulate the inducation of TH. It has been shown that for patients with the physical properties used in this work, intracarotid cooling in case of high degrees of stenosis is not sufficient to reach TH in the penumbra within one hour. In future simulation studies the influence of variations of the Circulus Willisii and anastomoses on cerebral cooling should be investigated.

Abstract:

Imaging systems are increasingly used in medical practice to improve the quality and accuracy of diagnosis and therapy. Although the data acquired reveals useful information, further processing is often needed to provide a comprehensive and valuable representation. As most processing should only be applied to the regions of interest (ROI) in the image, a previous segmentation step is necessary. For algorithms containing spatial low-pass filtering, a prior segmentation prevents the loss of information at the borders of different regions. Nowadays, the segmentation of medical images is mainly performed manually, which is extremely time-consuming. Additionally, the segmentation outcome highly depends on the experience of the clinician. For this reason, there exists an increasing demand for unsupervised image segmentation. In this work, a method to automatically detect the regions of no interest (RONI) in medical sceneries is proposed. The algorithm is aimed at images of surgical procedures on intracranial aneurysms, in which a low depth-of-field (DOF) is induced by the deep access channel and the high magnification of the surgical microscope. The developed approach consists of three parts. First, a color segmentation based on a clustering algorithm is applied. It identifies the RONI with colors different from the vessel of interest. Second, a focus segmentation is used to detect all RONI that are out of focus. This is realized by determining the focused edges in the image and enclosing the ROI by linking those edges. In the last part, the results from both previously applied methods are combined to obtain the final segmentation result. A proof of concept for the proposed method combining color and focus segmentation is presented in this work. The validation on six intraoperative images of aneurysm clipping surgeries shows a high sensitivity and specificity of the algorithm. In comparison to a separate color or focus segmentation, the combination of those methods is demonstrated to increase the accuracy of the segmentation results. An extensive validation of the method developed in this thesis could not be performed due to a lack of sufficient image data.

Abstract:

In western countries, stroke is the third-most widespread cause of death. 87% of all strokes are ischaemic strokes. A common treatment in case of an ischaemic stroke is therapeutic hypothermia. It is expected to prevent an inflammation of the undersupplied tissue and is usually caused by surface cooling of the whole body. This leads to side effects such as cardiac arrhymias. A new promising treatment method is selective intracarotid blood cooling combined with a mechanical artery recanalisation. This approach requires a detailed knowledge of the cerebral circulation and a precise resolution of the brain temperature. An auspicious solution is the usage of a computational model. In this work, we extended an existing haemodynamics model, including the characteristics of the anterior, middle and posterior cerebral arteries using the transmission-line approach. In case of an ischaemic stroke, the collaterals are an important part of the cerebral circulation. Therefore, seven end-to-end anastomoses between the three main cerebral arteries were additionally considered for each hemisphere. The underlying stenosis was integrated into the M1 segment of the middle cerebral artery, due to the highest risk of occlusion. The extended model was evaluated in a physiological as well as in a pathophysiological case. Under healthy conditions the resulting flow in the extended model corresponded to the flow of the initial model. The flow through the collaterals barely existed, which is in accordance to the literature. For the pathophysiologial case, the degree of collateralisation and the degree of stenosis were varied, respectively. The different degrees of collateralisation were divided into "poor", "partial" and "good" and were realised by different values of anastomoses radii. For a 100% stenosis, a significantly high blood flow of 1.2528cm3/s through the collaterals in case of a "good" collateralisation could be shown. Therefore, the blood supply into the terminal branches of the middle cerebral artery could almost by half (48.18%) be compensated. The higher the degree of collateralisation was the higher the blood supply of the terminal branches of the MCA. Hence, a patient with a "good" collateralisation can compensate a higher degree of occlusion and potentially has a better outcome after an ischaemic stroke. In this work, 50%, 75% and 100% stenoses were compared with one another. The higher the degree of stenosis was the higher was the flow through the collaterals. In combination with a temperature model, the introduced model of the cerebral collateral circulation can be used to monitor hypothermal patients who suffered from an ischaemic stroke. The monitoring shall examine the blood and brain temperature in every part of the brain and in case of a deviation of the intended temperature the degree of hypothermia shall be modified.

Abstract:

Despite their maturity, contemporary surgical microscope systems still leave aspects to be desired. The number of co-observers is currently restricted, by spatial and optical limitations, to only two. The co-observers also suffer from decreased stereoscopic depth perception. Moreover, ergonomics pose a problem, with current microscope systems impeding mobility and sometimes demanding that surgeons take uncomfortable postures over lengthy periods of time. The next evolutionary step in surgical microscope design should hence improve surgical microscope ergonomics and remove the limitations on co-viewing. A promising approach to this is the fully digital surgical microscope, where the current observation systems are replaced with a camera array; allowing real-time 3D reconstruction of surgical scenes and, consequently, the rendering of almost unlimited views for different observers. Digital microscopes could thus also relieve the surgeon of the necessity to look through the microscope, hence allowing him to move more freely and take more comfortable postures. The requirements on the camera array in such a system have yet to be determined. To this effort, we have have contributed an estimation of the minimal number and positions of cameras needed for the 3D reconstruction of microsurgical sites, based on the simulated reconstruction of reference models. With the simulation program we developed for this purpose, the requirements for a camera array in a compact and cost effective fully digital surgical microscope could be estimated.

Abstract:

Cardiac arrhythmias such as atrial fibrillation and atrial flutter occur more frequently in industrialized countries. If the drug therapy does not work, radiofrequency ablation (RFA) in the atria is a common treatment. This minimally invasive operation allows a lasting improvement in the heart rhythm disorder. However, this procedure often has to be repeated because of the high recurrence rate. A significant proportion, 46%, still needs to take anti- arrhythmic drugs. This thesis relates with the evaluation of electrograms (EGMs) which were recorded with a high-density mapping catheter and an ablation catheter. Furthermore, both methods should be tested for their respective advantages and compared with each other. For this purpose, two clinical data sets were evaluated, which were recorded in the Städtisches Klinikum Karlsruhe in interventions performed on humans during an electrophysiological study. A predefined measurement protocol was performed during RFA in the left atrium (LA). A newly defined procedure, the stable holding of the ablation catheter during the ablation and subsequent measurement process, was introduced and proved to be particularly practicable. Three ablation points in the LA were placed near the left pulmonary veins, where later a pulmonary vein isolation was performed to cure the heart arrhythmia. First, the data from each catheter were recorded and then evaluated using self-developed software. Afterwards, the signals were filtered and classified into individual EGMs using the Non-linear Energy Operator. Subsequently, EGM paths were formed along the endocardium. By precisely locating the recorded EGMs, it was possible to assess the ablation areas before and after ablation. With high-density maps, the in vivo data were also analyzed in three-dimensional space. As a result the peak to peak amplitudes of the EGMs decrease by about 40-61% after every 30 seconds of ablation. This procedure forms the basis for studies on how the duration of ablation affects the morphological change of the measured EGMs. With the Orion data high-density voltage maps were generated. High-density mapping showed that not only the tissue, which had direct contact with the catheter tip during the RFA had changed, but also the surrounding tissue was affected. This was demonstrated by low peak-to-peak amplitudes, which existed in large areas, widths up to 14 mm, around the ablation lesions. After the right pulmonary vein isolation, high-density mapping was repeated and the influence of the time factor on the ablation lesions was examined. RFA-treated tissue appears to recover, except at the ablation point itself. In summary, both types of catheters are useful, but a closer examination of the scar can be achieved with the Orion high-density mapping catheter.

Abstract:

Die vorliegende Arbeit beschreibt eine Konzeptionierung und Realisierung eines Daten- und Energieübertragungsverfahrens für ein räumlich verteiltes Netzwerk von elektronischen implantierbaren Geräten in einer Master-Slave-Topologie. Zunächst wurden die technischen und medizinischen Anforderungen im Hinblick auf die möglichen Einsatzszenarien erarbei- tet. Daraufhin wurde ein Konzept vorgeschlagen, welches die aufgeführten Anforderungen erfüllt. Dieses Konzept wurde anhand eines Prototyps realisiert und evaluiert. Letztendlich wurden die Ergebnisse der Evaluierung ausgewertet und diskutiert.

Abstract:

When analyzing biosignals it is common practice to estimate the instantaneous phase (IP) in order to better follow signal propagation or to find phase singularities. However, the IP is often used despite the fact that the reliability of the methods for estimating the IP are not yet well known enough. Their effectiveness is therefore heavily debated. In this thesis, different methods for estimating the IP of biosignals are examined. For this purpose six methods for estimating the IP were applied to artificially generated biosignals mimicking intracardiac signals and those from the EIT. Subsequently, a signal processing study was performed in which noise was added and/or the signal morphology was varied. In the instance of intracardiac signals the effects of baseline drift were also studied. The resulting phase signals were then compared to the phase of the unaltered signals in order to test their robustness. Additionally, in the case of intracardiac signals the phase signals were compared to a linearly interpolated phase between Local Activation Times (LAT)s. The results show that the methods are reliable in the case of EIT signals. In comparison, the phase estimation of atrial signals was unreliable in many cases. As a result, two new methods based on the Non-Linear-Energy-Operator were developed that produce a far more reliable phase estimation of atrial signals. One of those methods is a peak-detection algorithm that interpolates the phase linearly between two peaks. It is shown that the phase estimation by peak detection yields results that are as good or better than the best preceding phase estimation method. This result was also confirmed when the methods were applied to clinical data.

Abstract:

Die vorliegende Arbeit untersucht die Signalmorphologie eines Photoplethysmogramms (PPG) und eines kamerabasierten Photoplethysmogramms (cbPPG). Aus dem Signal des PPGs werden medizinisch relevante Parameter extrahiert, die mit denen des cbPPGs ver- glichen werden können. Aufgrund unzureichender und nicht auswertbarer Ergebnisse des cbPPGs wird eine Simulation zur Untersuchung der Ursachen durchgeführt. Die Simulation ergibt den Schluss, dass insbesondere das Rauschen reduziert werden muss, um mit Hilfe des cbPPGs eine auswertbare Signalmorphologie zu erhalten. The present thesis examines the signal morphology of the pulse signal of a photoplethysmo- gram (PPG) and a camera-based photoplethysmogram (cbPPG). Medical relevant parameters of the PPG signal get extracted to be compared to those of the cbPPG. Because of insufficient and not evaluable results regarding the cbPPG, a simulation of the cbPPG signal is realized to analyze the cause. The result of the simulation is that mainly noise has to be reduced in order to get an analyzable cbPPG signal.

Abstract:

Pulmonary diseases belong to the most common causes of death worldwide according to the World Health Organization [1]. The Electrical Impedance Tomography (EIT) is already a reliable tool to monitor the distribution of the aeration inside the lungs. However, the possibility to also measure pulmonary perfusion using EIT would provide further important information to the physicians. Therefore, the indicator dilution method has shown promising results in former studies [2], [3], [4], where an injected saline solution acts as a contrast agent for EIT due to its relatively high conductivity. This thesis was about further investigating if an approximation and separation of the com- ponents observed in the resulting signals, i.e. showing the passage of the injected saline solution and a drift over the entire signal, might enable to better calculate pulmonary perfu- sion parameters than just using raw, unmodified EIT indicator signals. Three main approaches were implemented and evaluated using porcine data from a big ani- mal study. The accuracy and robustness of the components approximations was determined by calculating the correlation and the root mean square error (RMS) between the sum of the approximated components in each pixel and the respective origin signals. Furthermore, relative blood flow (rBF) was calculated using the component that is assumed to refer to pulmonary perfusion, and compared against Positron Emission Tomography (PET) scans to validate if the performed approximations have been made reasonable. Although no significant improvement in calculating rBF was achieved compared to the case that simply raw EIT indicator signals instead of approximated components are used, the results even though showed a high consistency to the values received from PET. The good results allowed to further investigate and explain the reasons for the observed behavior of indicator signals in EIT. Moreover, the separation of the different indicator dilution compo- nents enables the estimation of additional hidden information about the state of the regional perfusion such as blood transit times.

Abstract:

Pelvic floor disorders affect an important number of women. They are characterized by a debilitating mechanical stability of pelvic organs. This brings symptoms that disturb immensely the patient’s quality of life. Available treatment options range from drug therapy, to implants and in some cases surgical repair. To maximize the success of surgery and reduce the probability of recurrence a precise planning based on Medical Imaging is required. Traditional techniques such as Fluoroscopy, Ultrasound and Magnetic Resonance Imaging are normally used for qualitative assessment of pelvic floor disorders. The aim of this project is to perform a quantitative assessment of pelvic organ deformation using a shape descriptor based on image moments. A novel method of acquisition was used for imaging of the pelvic organs. Semiautomatic, segmentation was done, coupled with an interpolation method to reconstruct 3D volumes of the bladder. A shape descriptor based on Zernike moments was implemented and tested based on two different algorithms: Novotni and Pozo. Simulation and in vivo experiments were performed on the bladder to validate its performance. Deformation maps are proposed as a method for visualization of the dynamic deformations of the bladder. The Novotni method showed a better visualization of the deformations for every case, the Pozo method only showed a clear correlation when used with the simulated data.

Abstract:

The focus of this work is the extraction and processing of information from bi-domain surgical video data to detect a vessel. The examined videos in the infrared and visible spectrum were recorded with a neurosurgical microscope during aneurysm procedures. The detection of a vessel is realized using the following three steps: Firstly, the automatic frame selection in the IR domain. Secondly, the segmentation of the vessel. Thirdly, the information matching and overlay using mutual information as metric. The methods were tested with four clinical video pairs and the highest average jaccard index achieved was 68%. The results show that the combination of information from multiple sensors is possible and enables a higher jaccard index than a single domain approach. It is now possible to use the geometric information about the vessel obtained from the indocyanine green (ICG) in combination with the RGB video over longer periods.

Abstract:

Optical Coherence Tomography (OCT) is a noninvasive, label-free imaging modality. It has been widely used in medical imaging due to its unique characteristics in resolution and penetration depth. OCT has larger penetration depth than confocal microscopy and resolution higher than ultrasound imaging systems. The goal for this project was to develop and characterize a Spectral Domain Optical Co- herence Tomography (SDOCT) system. Graphical User Interface (GUI) was developed to improve the system in terms of signal acquisition and online reconstruction of the depth re- flectivity profile (A-scan). Dispersion compensation was realized by retrieving the nonlinear compartment of the phase, introducing the dispersion term and correcting the signal by this term. Developed system was characterised with axial resolution, Signal to Noise Ratio (SNR) and signal drop-off. After dispersion compensation axial resolution improved twofold and reached the value of 13.7 μm and SNR value increased by 6 dB. To investigate OCT signal in a scattering environment, experiments with Intralipid solution were conducted.

Abstract:

In many medical devices camera systems are implemented. Some of these devices are e.g. laboratory or surgical microscopes and also endoscopes. In some others they are used to provide an additional feature, like the position tracking in computed tomography or positioning systems in refractive surgery. Often they are used for only one specific purpose, like the above mentioned position controlling, motion tracking or simply to show the image of the actual scenery and record it. These camera systems deliver much more information than is actually used. Extracting just a part of it could lead to valuable additional data without increasing the amount of devices necessary next to the patient. Focusing on surgical microscopes or endoscopes, usually showing tissue, e.g. a wireless detection of the heart rate with camera-based photoplethysmography (cbPPG) is possible, since heart rate and color changes are correlated [1, 2]. Regarding the color changes in a video of the tissue, especially vessels, it might also be possible to extract the blood flow direction or estimating the pulse wave velocity (PWV). Both parameters were valuable information for a doctor, e.g. in order to verify without use of dye the clipping of an aneurysm during surgery. Or, using the PWV estimation, to evaluate the arterial distensibility and using it as a marker of cardiovascular risk in hypertensive patients [3]. The problem is to extract these small signals of color changes and enhance their quality in order to reveal valuable information and visualize it in an appropriate way.

Abstract:

Durch den zunehmenden Einsatz von digitalen Operationsmikroskopen in der Chirurgie entstehen neue Möglichkeiten Mediziner durch automatische Bildverarbeitung bei ihren Entscheidungen zu unterstützen. Speziell Neuro- und Gefäßchirurgen arbeiten dabei häufig mit sehr feinen Strukturen, bei denen eine exakte Schätzung der Ausmaße durch einen Mensch selbst mit viel Erfahrung nahezu unmöglich ist. Obwohl bereits verschiedene Ansätze zur geometrischen Analyse von Adern-Aufnahmen verfolgt wurden, ist die optische Vermessung von Gefäßlänge und -durchmesser ein stark vernachlässigtes Thema. Insbesondere existieren keine Arbeiten, die eine objektive sowie statistisch relevante Evaluation der vorgestellten Methoden durchführen. Ziel dieser Arbeit ist es daher, nicht nur Methoden zu finden, die eine Vermessung ermögli- chen, sondern auch ihre Performanz im Sinne einer akkuraten Messung zu beurteilen. Dabei soll untersucht werden, ob Länge und Durchmesser der Gefäße im Allgemeinen bis auf einem Fehler von 5% bestimmt werden können. Die Arbeit besteht aus zwei großen Paketen, deren Zusammenspiel Abb. 1 zeigt. Zunächst wird ein Modell für Segmentierungen von Gefäßbildern aufgestellt und implemen- tiert. Mit diesem werden synthetische Testbilder in großer Zahl automatisch generiert, bei denen die Ground Truth vollständig bekannt ist. Im zweiten Teil werden die Erosions- und die Voronoi-Methode zur Gewinnung der Mittelli- nie(Centerline) aus einer Segmentierung, sowie drei (diskrete und kontinuierliche) Methoden zur Vermessung der Länge dieser Linie und eine Methode zum Ermitteln von Durchmessern in der Segmentierung vorgestellt. Zur Bewertung werden über 1200 Bilder aus dem Modell mit den verschiedenen Methoden untersucht. Mit der besten Kombination der Methoden lassen sich dabei Länge und Durch- messer mit durchschnittlichen relativen Fehlern von 2,6% bzw. 3,9% ermitteln. Bei der Implementierung wurde viel Wert auf Modularität gelegt, sodass sowohl Erweite- rungen im Modell leicht zu integrieren sind als auch weitere Methoden zur Verarbeitung entwickelt und getestet werden können.

Abstract:

Since it is proved that the alternations of the cutaneous vasculature are involved in most cases of skin disorders, the segmentation and quantification of skin lesions with the aid of computer science are of great interest for medical research. In this master thesis, an optical coherence tomography angiography (OCTA) system is adopted to provide volumetric tissue and vascu- lar morphological information of human skin. Then an algorithm is developed to segment the lesion zones and extract the parameters automatically. By studying several common skin lesions such as cherry angiomas, basal cell carcinomas (BCCs) and benign nevi, OCTA is proved to be a powerful modality for the imaging of the microvascular architectures with high resolution. The feasibility of our algorithm is also verified by the results. Furthermore, the relationship among the parameters are discussed so as to find out the characteristics of skin lesions. At the end, a new sample/probe arm is assembled to improve the performance of the current OCTA system.

Abstract:

An increased respiration rate is an indicator of several diseases, such as sepsis. Even nowadays, the common way to measure the respiration rate on the general ward, is the manual counting of breaths within a minute. These measurements are inaccurate and thus unreliable. A contactless respiration measurement technique at the general ward could solve this problem and could contribute to the early detection of diseases. In this thesis, three feature extraction methods were implemented and evaluated which measured the respiration rate from 3D data of a Time of Flight camera. The spectral approach determined the respiration rate by analyzing the pixel signals in the frequency domain. In the second approach, the principal component analysis was applied to the pixel signals with the aim of extracting the respiration signal from the noisy data. The third approach computed volume changes over time. Additionally, a movement detection was implemented to avoid failures. The performance of each approach was evaluated by comparing the results to a reference capnography signal. 85 recordings from six subjects were analyzed. The spectral and the PCA approach achieved positive predictive values of more than 99 %. The volume approach showed, in contrast to the others, dependencies on the subject’s pose. The work in this thesis showed that a respiration signal can be obtained from 3D data. Two out of three of the proposed methods can be used for further development to enable the usage in a medical device.

Abstract:

Cardiac diseases, including myocardial infarction (MI), are the leading cause of death worldwide. Dysfunction of the heart results from remodeling processes affecting electrophysiology and electro-mechanical tissue properties. Conceptual and computational models of diseases rely on accurate microstructural parameters, such as passive conductivity tensors, and their alteration during remodeling. However, our knowledge on these parameters is limited. To close this knowledge gap, a comprehensive computational framework for the reconstruction and analysis of normal and infarcted myocardial microstructure was implemented, particularly focusing on the derivation of passive conductivity tensors. 3D image stacks of control and MI ventricular tissue were acquired by confocal microscopy with a sub-micrometer resolution. Myocardial microstructure was assessed with a multi-label staining protocol, simultaneously acquiring signals from five fluorescent labels. Two synergistic segmen- tation approaches were used to predict the mask and boundaries of cardiomyocytes. Intended for scenarios when no previously annotated image stacks are available, a method requiring minor human interaction, based on hand-crafted image features and ensembles of decision trees, was implemented. For the scenario when multiple annotated stacks are available, e.g. due to segmen- tation using latter method based on ensembles of decision trees, a fully automated segmentation pipeline utilizing convolutional neural networks was implemented. The predictions were used to generate comprehensive 3D reconstructions of cardiac microstructure, including cardiomyocytes, extracellular space, fibroblasts, myofibroblasts, and vessels. To overcome bottlenecks in the reconstruction pipeline, a graph-based agglomeration method was used in the reconstruction process. 3D reconstructions of tissue microstructure (control: 5 stacks, MI: 5 stacks) were used to construct computational models of passive intra- and extracellular conductivity tensors. Predictions of the decision tree-based segmentation approach resulted in mean Matthews corre- lation coefficients (MCCs) between 0.90 and 0.96 for increasing amounts of available training data. The deep learning-based segmentation approach yielded mean MCCs of 0.87 and 0.91 for the prediction of the mask and boundary of cardiomyocytes, respectively. The graph-based agglomeration method achieved a mean V-Measure of 0.84. Computational models of passive intra- and extracellular conductivity tensors were verified against analytic solutions and yielded errors in the order of 107 and 108, respectively. The mean intracellular conductivities in control tissue were 0.257, 0.021, and 0.001 S/m in fiber, transverse, and normal direction, respectively. For MI tissue, the mean intracellular conductivities were 0.090, 0.051 and 0.0002 S/m in fiber, transverse, and normal direction, respectively. The mean extracellular conductivities in control tissue were 0.388, 0.174, and 0.117 S/m in fiber, transverse, and normal direction, respectively. For MI tissue, the mean extracellular conductivities were 0.556, 0.433 and 0.224 S/m in fiber, transverse, and normal direction, respectively. Overall, this work implemented a computational framework capable of reconstructing normal and infarcted cardiac microstructure with minimal human interaction. Proposed segmentation algo- rithms showed promising results. Intra- and extracellular conductivity tensors in MI tissue were significantly altered compared to control tissue. The next step is the application to newly acquired and large-scale image data, putting the new framework into practice. The novel quantitative data can serve as a foundation for future modeling studies on, for instance, cardiac conduction in hearts with MI.