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:

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:

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:

We suggest a new regularization method for reconstruction of cardiac transmembrane voltages (TMV) from body surface potentials that is based on imposing similarity between time-aligned TMVs. An iterative scheme is proposed to update the delays needed for time-alignment. Evaluation of the method using simulated ventricular pacings showed a clear improvement over second order Tikhonov.

Abstract:

Activation times (AT) describe the sequence of cardiac depolarization and represent one of the most important parameters for analysis of cardiac electrical activity. However, estimation of ATs can be challenging due to multiple sources of noise such as fractionation or baseline wander. If ATs are estimated from signals reconstructed using electrocardiographic imaging (ECGI), additional problems can arise from over-smoothing or due to ambiguities in the inverse problem. Often, resulting AT maps show falsely homogeneous regions or artificial lines of block. As ATs are not only important clinically, but are also commonly used for evaluation of ECGI methods, it is important to understand where these errors come from. We present results from a community effort to compare methods for AT estimation on a common dataset of simulated ventricular pacings. ECGI reconstructions were performed using three different surface source models: transmembrane voltages, epi-endo potentials and pericardial potentials, all using 2nd-order Tikhonov and 6 different regularization parameters. ATs were then estimated by the community participants and compared to the ground truth. While the pacing site had the largest effect on AT correlation coefficients (CC larger for lateral than for septal pacings), there were also differences between methods and source models that were poorly reflected in CCs. Results indicate that artificial lines of block are most severe for purely temporal methods. Compared to the other source models, ATs estimated from transmembrane voltages are more precise and less prone to artifacts.

Abstract:

ECG imaging estimates the cardiac electrical activity from body surface potentials. As this involves solving a severly ill-posed problem, additional information is required to get a unique and stable solution. Recent progress is based on introducing more problem-specific information by exploiting the structure of cardiac excitation. However, added information must be either certain or general enough to not impair the solution. We have recently developed a method that uses a spatio-temporal basis to restrict the solution space. In the present work, we analyzed this method with respect to one of the most fundamental assumptions made during basis creation: cardiac (an)isotropy. We tested the reconstruction using simulations of ventricular pacings and then applied it to clinical data. In simulations, the overall median localization error was smallest with a basis including fiber orientation. For the clinical data, however, the overall error was smallest with an isotropic basis. This observation suggests that modeling priors should be introduced with care, whereby further work is needed.

Abstract:

Electrical impedance tomography is an accepted and validated tool to analyze and support mechanical ventilation at the bedside. In the future it could furthermore clinically provide information of the pulmonary perfusion and other blood volume changes within the thorax by exploiting a cardiosynchronous EIT component. In the presented study, the spatial forward sensitivity against different background lung tissue distributions was analyzed. Spheres with a 10% change of the background conductivity were introduced in the lungs and in the heart. The cranio-caudal distribution of sensitivity had a bell shape and was similar between all simulated scenarios, varying only in magnitude. If the background tissue conductivity within the lungs was chosen to be the one of deflated tissue, the overall sensitivity was 46% smaller compared to the overall sensitivity against inflated lung tissue conductivity. Within the heart region, the sensitivity was increased for fully deflated lung tissue conductivity (23% relative to the sensitivity in the lungs) compared to a homogeneous distribution of inflated lung tissue conductivity (10% relative to the sensitivity in the lungs).

Abstract:

The heart acts as the pump of the cardiovascular system due to the active stress developed in individ- ual cardiac muscle cells. The spatio-temporal distribution of this active stress could contain relevant diagnostic information but can currently not be measured in vivo. We introduce a method to esti- mate dynamic cardiac active stress fields from endocardial surface motion tracking derived from e.g. magnetic resonance imaging data. This ill-posed non-linear problem is solved using Tikhonov regu- larization in space and time in conjunction with a continuum mechanics forward model. We present a proof-of-concept using data from a biophysically detailed multiscale model of cardiac electrome- chanics (7649 tetrahedral elements) in which we could accurately reproduce cardiac motion (surface error <0.4 mm) and identify non-contracting regions due to myocardial infarction scars (active stress error <10 kPa). This inverse method could eventually be used to non-invasively derive personalized diagnostic information in terms of dynamic active stress fields which are not accessible today.

Abstract:

Electrocardiographic Imaging (ECGI) requires robust ECG forward simulations to accurately calculate cardiac activity. However, many questions remain regarding ECG forward simulations, for instance: there are not common guidelines for the required cardiac source sampling. In this study we test equivalent double layer (EDL) forward simulations with differing cardiac source resolutions and different spatial interpolation techniques. The goal is to reduce error caused by undersampling of cardiac sources and provide guidelines to reduce said source undersampling in ECG forward simulations. Using a simulated dataset sampled at 5 spatial resolutions, we computed body surface potentials using an EDL forward simulation pipeline. We tested two spatial interpolation methods to reduce error due to undersampling triangle weighting and triangle splitting. This forward modeling pipeline showed high frequency artifacts in the predicted ECG time signals when the cardiac source resolution was too low. These low resolutions could also cause shifts in extrema location on the body surface maps. However, these errors in predicted potentials can be mitigated by using a spatial interpolation method. Using spatial interpolation can reduce the number of nodes required for accurate body surface potentials from 9,218 to 2,306. Spatial interpolation in this forward model could also help improve accuracy and reduce computational cost in subsequent ECGI applications.

Abstract:

The boundary element method is widely used to solve the forward problem of electrocardiography, i.e. to calculate the body surface potentials (BSP) caused by the heart’s electrical activity. This requires discretization of boundary surfaces between compartments of a torso model. Often, the resolution of the surface bounding the heart is chosen above 1 mm, which can lead to spikes in resulting BSPs. We demonstrate that this artifact is caused by discontinuous propagation of the wavefront on coarse meshes and can be avoided by blurring cardiac sources before spatial downsampling. We evaluate different blurring methods and show that Laplacian blurring reduces the BSP error 5-fold for both transmembrane voltages and extracellular potentials downsampled to 3 different resolutions. We suggest a method to find the optimal blurring parameter without having to compute BSPs using a fine mesh.

Abstract:

Heterogeneous atrial substrate can induce, maintain and promote cardiac arrhythmias. The level of heterogeneity may be used to assess disease progression. One key parameter, suspected to be correlated with tissue vitality is the conduction velocity (CV). By measuring not only the current CV of the patient but rather its rate dependent changes, restitution information is gained. In the following, we show our approach towards a patient-specific quantitative atrial substrate characterization by combining sets of local and global CV restitution measurements to create a parametrization of the individual patient substrate characteristics.

Abstract:

Stroke is the third-most cause of death in developed countries. A new promising treatment method in case of an ischemic stroke is selective intracarotid blood cooling combined with mechanical artery recanalization. However, the control of the treatment requires invasive or MRI-assisted measurement of cerebral temperature. An auspicious alternative is the use of computational modeling. In this work, we extended an existing 1D hemodynamics model including the characteristics of the anterior, middle and posterior cerebral artery. Furthermore, seven ipsilateral anastomoses were additionally integrated for each hemisphere. A potential stenosis was placed into the M1 segment of the middle cerebral artery, due to the highest risk of occlusion there. The extended model was evaluated for various degrees of collateralization (“poor”, “partial” and “good”) and degrees of stenosis (0%, 50%, 75% and 99.9%). Moreover, cerebral autoregulation was considered in the model. The higher the degree of collateralization and the degree of stenosis, the higher was the blood flow through the collaterals. Hence, a patient with a good collateralization could compensate a higher degree of occlusion and potentially has a better outcome after an ischemic stroke. For a 99.9% stenosis, an increased summed mean blood flow through the collaterals of +97.7% was predicted in case of good collateralization. Consequently, the blood supply via the terminal branches of the middle cerebral artery could be compensated up to 44.4% to the physiological blood flow. In combination with a temperature model, our model of the cerebral collateral circulation can be used for tailored temperature prediction for patients to be treated with selective therapeutic hypothermia.

Abstract:

In Western countries, stroke is the third-most cause of death; 35- 55% of the survivors experience permanent disability. Mild therapeutic hypothermia (TH) showed neuroprotective effect in patients returning from cardiac arrest and is therefore assumed to decrease stroke induced cerebral damage. Recently, an intracarotid cooling sheath was developed to induce local TH in the penumbra using the cooling effect of cerebral blood flow via collaterals. Computational modeling provides unique opportunities to predict the resulting cerebral temperature without invasive procedures. In this work, we generated a simplified brain model to establish a cerebral temperature calculation using Pennes’ bio-heat equation and a 1D hemodynamics model of the cranial artery tree. In this context, we performed an extensive literature research to assign the terminal segments of the latter to the corresponding perfused tissue. Using the intracarotid cooling method, we simulated the treatment with TH for different degrees of stenosis in the middle cerebral artery (MCA) and analyzed the resulting temperature spatialtemporal distributions of the brain and the systemic body considering the influence of the collaterals on the effect of cooling.

Abstract:

Quantifying the atrial conduction velocity (CV) reveals important information for targeting critical arrhythmia sites that initiate and sustain abnormal electrical pathways, e.g. during atrial flutter. The knowledge about the local CV distribution on the atrial surface thus enhances clinical catheter ablation procedures by localizing pathological propagation paths to be eliminated during the intervention. Several algorithms have been proposed for estimating the CV. All of them are solely based on the local activation times calculated from electroanatomical mapping data. They deliver false values for the CV if applied to regions near scars or wave collisions. We propose an extension to all approaches by including a distinct preprocessing step. Thereby, we first identify scars and wave front collisions and provide this information for the CV estimation algorithm. In addition, we provide reliable CV values even in the presence of noise. We compared the performance of the Triangulation, the Polynomial Fit and the Radial Basis Functions approach with and without the inclusion of the aforementioned preprocessing step. The evaluation was based on different activation patterns simulated on a 2D synthetic triangular mesh with different levels of noise added. The results of this study demonstrate that the accuracy of the estimated CV does improve when knowledge about the depolarization pattern is included. Over all investigated test cases, the reduction of the mean velocity error quantified to at least 25 mm/s for the Radial Basis Functions, 14 mm/s for the Polynomial Fit and 14 mm/s for the Triangulation approach compared to their respective implementations without the preprocessing step. Given the present results, this novel approach can contribute to a more accurate and reliable CV estimation in a clinical setting and thus improve the success of radio-frequency ablation to treat cardiac arrhythmias.

Abstract:

In Western countries, stroke is the third-most widespread cause of death. 80% of all strokes are ischemic and show a mortality rate of about 25%. Furthermore, 35-55% of affected patients retain a permanent disability. Therapeutic hypothermia (TH) could decrease inflammatory processes and the stroke-induced cerebral damage. Currently, the standard technique to induce TH is cooling of the whole body, which can cause several side effects. A novel cooling sheath uses intra-carotid blood cooling to induce local TH. Unfortunately, the control of the temporal and spatial cerebral temperature course requires invasive temperature measurements. Computational modeling could be used to predict the resulting temperature courses instead. In this work, a detailed 1D hemodynamics model of the cerebral arterial system was coupled with an energetic temperature model. For physiological conditions, 50% and 100% M1-stenoses, the temperatures in the supply area of the middle cerebral artery (MCA) and of the systemic body was analyzed. A 2K temperature decrease was reached within 10min of cooling for physiological conditions and 50% stenosis. For 100% stenosis, a significant lower cooling effect was observed, resulting in a maximum cerebral temperature decrease of 0.7K after 30min of cooling. A significant influence of collateral flow rates on the cooling effect was observed. However, regardless of the stenosis degree, the temperature decrease was strongest within the first 20min of cooling, which demonstrates the fast and effective impact of intra-carotid blood cooling.

Abstract:

In Europe, the prevalence of chronic kidney disease lay at approximately 18.38% in 2016. A common treatment for patients in the end stage of this disease is haemodialysis. However, patients undergoing this therapy suffer from an increased risk of cardiac death. A hypothesis is that the cause is an inbalanced electrolyte concentration. To study the underlying mechanisms of this phenomenon and fight the consequences, a continous non-invasive monitoring technique is desired. In this work, we investigated the possibility to reconstruct the extracellular concentrations of potassium and calcium from ECG signals. Therefore, we extracted 71 ECGs using the simulation results of a modified Himeno et al. ventricular cell model comprising variations of the extracellular ionic concentrations of potassium and calcium. The changes dependent on the different extracellular ionic concentrations were captured with five ECG features. These were used to train an artificial neural network for regression. The study was performed both for noise-free and noisy data. The estimation error for the reconstruction of the potassium concentrations was -0.01±0.14 mmol/l (mean±standard deviation) in the noise- free case, -0.03±0.46mmol/l in the noisy case (30dB SNR). For calcium, the result was 0.01±0.11mmol/l in the noise- free case, 0.02±0.17mmol/l in the noisy case. For both ion types, the result was improved by augmenting the dataset. We therefore conclude that with the calculated features, we are able to reconstruct the extracellular ionic concentrations for both potassium and calcium with an acceptable precision. When analysing noisy signals, the accuracy of the estimation method is still sufficient but can be further improved by an augmentation of the dataset.

Abstract:

The outcomes of ablation targeting either reentry activations or fractionated activity during persistent atrial fibrillation (AF) therapy remain suboptimal due to, among others, the intricate underlying AF dynamics. In the present work, we sought to investigate such AF dynamics in a heterogeneous simulation setup using recurrence quantification analysis (RQA). AF was simulated in a spherical model of the left atrium, from which 412 unipolar atrial electrograms (AEGs) were extracted (2 s duration; 5 mm spacing). The phase was calculated using the Hilbert transform, followed by the identification of points of singularity (PS). Three regions were defined according to the occurrence of PSs: 1) no rotors; 2) transient rotors and; 3) long-standing rotors. Bipolar AEGs (1114) were calculated from pairs of unipolar nodes and bandpass filtered (30-300 Hz). The CARTO criterion (Biosense Webster) was used for AEGs classification (normal vs. fractionated). RQA attributes were calculated from the filtered bipolar AEGs: determinism (DET); recurrence rate (RR); laminarity (LAM). Sample entropy (SampEn) and dominant frequency (DF) were also calculated from the AEGs. Regions with longstanding rotors have shown significantly lower RQA attributes and SampEn when compared to the other regions, suggesting a higher irregular behaviour (P≤0.01 for all cases). Normal and fractionated AEGs were found in all regions (respectively; Region 1: 387 vs. 15; Region 2: 221 vs. 13; Region 3: 415 vs. 63). Region 1 vs. Region 3 have shown significant differences in normal AEGs (P≤0.0001 for all RQA attributes and SampEn), and significant differences in fractionated AEGs for LAM, RR and SampEn (P=0.0071, P=0.0221 and P=0.0086, respectively). Our results suggest the co-existence of normal and fractionated AEGs within long-standing rotors. RQA has unveiled distinct dynamic patterns–irrespective of AEGs classification–related to regularity structures and their nonstationary behaviour in a rigorous deterministic context.

Abstract:

Intracardiac electrograms (EGMs) form the basis for the diagnosis of arrhythmia mechanisms. Bipolar EGMs dominate clinical practice despite major disadvantages over unipolar EGMs since noise strongly distorts the latter. In this study, we quantified and reduced the noise level of uni- and bipolar EGMs recorded with Rhythmia HDx and the Orion catheter. Distinct noise frequencies in the power spectral density (PSD) were detected with a sliding win- dow of variable width and subsequently removed by notch filtering. The absolute peak to peak voltage remaining in the inactive segments after baseline removal quantified the noise level of the system. An international, multi-center selection of 33 patients served as a broad sample cohort. The case-specific detection and removal of noise peaks reduced the noise level in unipolar EGMs by 30% to 0.076 mV compared to standard clinical filtering. With a bipolar noise level of 0.01 mV, we saw that Rhythmia HDx meets the low noise floor claimed in the system specifica- tions. Certain noise frequencies presented permanently in all cases whereas others showed up only intermittently or in individual cases. The suggested extension of filter settings lowers the noise level, enhances the detailed segmentation of low volt- age areas, and encourages to exploit the advantages of unipolar over bipolar EGMs in clinical practice.

Abstract:

Improved understanding of the effects of variability in electrophysiological activity within the human heart is key to understanding and predicting cardiovascular response to disease and treatments. Previous studies have considered either regional variation in action potentials or inter-subject variability within a single region of the atria. In this study, we hypothesize that the regional differences in morphology derive not only from variation in dependence on individual conductances, but also from the relationship between multiple conductances. Using the Monte-Carlo Sampling Method and the Maleckar cellular model for electrophysiology, we created an In-Silico Population of Models. Each conductance was varied +/- 100% from the standard model. The population was divided into regional groups based on biomarkers. Results showed regional variation in the dependence on relationships between conductances. In the right atrial appendage the value of gK1 was found to be only twice as influential as the relationship between gK1 and gKur on the APD90 biomarker. Other relationships that had a significant impact included gTo-gKur; gKr-gK1; gNaK- gNaCa and gKur-gNaK for various regions. R2 values for first order linear regression models showed significant relationships were left out in the analysis. This was significantly improved in the second order R2 values.

Abstract:

Several works have studied arrhythmogenicity of a given atrial model using different methods to initiate and simulate the perpetuation of re-entrant activity. We evaluated and compared two state-of-the-art methods showing their influence on the estimated vulnerability to arrhythmia of an atrial model.

Abstract:

In silico studies are often used to analyze mechanisms of cardiac arrhythmias. The electrophysiological cell models that are used to simulate the membrane potential in these studies range from highly detailed physiological models to simplistic phenomenological models. To effectively cover the middle ground between those cell models, we utilize the manifold boundary approxi- mation method (MBAM) to systematically reduce the widely used O’Hara-Rudy ventricular cell model (ORd) and investigate the influence of parametrization of the model as well as different strategies of choosing input quantities, further called quantities of interest (QoI). As a result of the reduction process, we present three re- duced model variants of the ORd model that only contain a fraction of the original model’s ionic currents resulting in a twofold speedup in computation times compared to the original model. We find that the reduced models show similar action potential duration restitution and repolarization rates. Additionally, we are able to initialize and observe stable spiral wave dynamics on a 3D tissue patch for 2 out of the 3 reduced models.

Abstract:

Catheter ablation targeting low voltage areas (LVA) is commonly being used to treat atrial fibrillation (AF) in pa- tients with persistent AF. However, it is not always certain that the areas marked as low voltage (LV) are correct. This can be related to how the voltage is calculated. There- fore, this paper focuses on comparing different calculation methods, specifically, with regards to spatial distribution. Two voltage maps obtained in AF were used, removing points which did not meet the required specifications. The peaks for the remaining points, in regions of the left atrium, were then found and the voltage was calculated based on taking the peak to peak (p2p) for different beats. For around 30% of the points on the map, the voltage only changed by 0.1mV when taking one beat versus all beats. However, for some individual points, the difference was substantial, around 0.8mV, depending on the beat cho- sen. Additionally, the inter-method variability increased by around 0.1mV when considering all methods compared to only methods calculated using more than one point. It was found that taking a method which considers all p2p values would be a more appropriate method for cal- culating the voltage. Thus, providing a technique, which could improve the accuracy of identifying LVA in an AF map.

Abstract:

Nowadays, a large share of the global population is affected by heart rhythm disorders. Computational modelling is a useful tool for understanding the dynamics of cardiac arrhythmias. Several recent clinical and experimental studies suggest that atrial fibrillation is maintained by re-entrant drivers (e.g. rotors). As a consequence, numerous works have addressed atrial arrhythmogenicity of a given electrophysiological model using different methods to simulate the perpetuation of re-entrant activity. However, no common procedure to test atrial fibrillation vulnerability has yet been defined. Here, we systematically evaluate and compare two state-of-the-art methods. The first one is rapid extrastimulus pacing from rim of the four pulmonary veins. The second consists of placing phase singularities in the atria, estimating an activation time map by solving the Eikonal equation and finally using this as initial condition for the electrical cardiac propagation simulation. In this way, we are forcing the wavefronts to follow re-entrant circuits with low computational cost thus less simulation time. We aim to identify a methodology to quantify arrhythmia vulnerability on patient-specific atrial geometries and substrates. We will proceed with in-silico experiments, comparing the results of these two methods to initiate re-entrant activity, checking the influence of the different parameters on the dynamics on the re-entrant drivers and finally extracting a valid set of parameters allowing to reliably assess re-entry vulnerability. The final objective is to come up with an easily reproducible minimal set of simulations to assess vulnerability of a particular atrial substrate (cellular and tissue model) or of distinct anatomical atrial geometries to arrhythmic episodes. Given the great need of exploring susceptibility to atrial arrhythmias, i.e. after a first ablation procedure, this study can provide a useful tool to test new treatment strategies and to learn how to prevent the onset and progression of atrial fibrillation.

Abstract:

Atrial fibrillation is the most common cardiac arrhythmia characterized by a rapid and irregular atrial excitation rate. Mimicking this behaviour, the S1-S2 stimulation protocol is currently the clinically established method for measuring tissue rate dependency, leading to a need for an automated segmentation method. We propose a method for stimulus artefact removal tailored towards the S1-S2 protocol. We show that this method results in the detection of atrial signals minimizing distortion by the stimulus artefact and is therefore an effective segmentation tool and a building block for automation of signal analysis.

Abstract:

A catheter has a mapping assembly having a plurality of splines mounted at its distal portion. The splines each have a proximal end disposed at the distal portion of the catheter body and a distal end and configured as a Fibonacci spiral arm that diverges outwardly from the proximal end. The splines have a support arm with shape memory, a non-conductive covering in surrounding relation to the support arm, at least one location sensor mounted at or near the distal end, a plurality of electrodes mounted in surrounding relation to the non-conductive covering, and a plurality of electrode lead wires extending within the non-conductive covering. Each electrode lead wire is attached to a corresponding one of the electrodes.