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Aims Anti-tachycardia pacing (ATP) is a reliable electrotherapy to painlessly terminate ventricular tachycardia (VT). However, ATP is often ineffective, particularly for fast VTs. The efficacy may be enhanced by optimized delivery closer to the re-entrant circuit driving the VT. This study aims to compare ATP efficacy for different delivery locations with respect to the re-entrant circuit, and further optimize ATP by minimizing failure through re-initiation. Methods and results Seventy-three sustained VTs were induced in a cohort of seven infarcted porcine ventricular computational models, largely dominated by a single re-entrant pathway. The efficacy of burst ATP delivered from three locations proximal to the re-entrant circuit (septum) and three distal locations (lateral/posterior left ventricle) was compared. Re-initiation episodes were used to develop an algorithm utilizing correlations between successive sensed electrogram morphologies to automatically truncate ATP pulse delivery. Anti-tachycardia pacing was more efficacious at terminating slow compared with fast VTs (65 vs. 46%, P = 0.000039). A separate analysis of slow VTs showed that the efficacy was significantly higher when delivered from distal compared with proximal locations (distal 72%, proximal 59%), being reversed for fast VTs (distal 41%, proximal 51%). Application of our early termination detection algorithm (ETDA) accurately detected VT termination in 79% of re-initiated cases, improving the overall efficacy for proximal delivery with delivery inside the critical isthmus (CI) itself being overall most effective. Conclusion Anti-tachycardia pacing delivery proximal to the re-entrant circuit is more effective at terminating fast VTs, but less so slow VTs, due to frequent re-initiation. Attenuating re-initiation, through ETDA, increases the efficacy of delivery within the CI for all VTs.

Background Epicardial pacing increases risk of ventricular tachycardia (VT) in patients with ischemic cardiomyopathy (ICM) when pacing in proximity to scar. Endocardial pacing may be less arrhythmogenic as it preserves the physiological sequences of activation and repolarization. Objective The purpose of this study was to determine the relative arrhythmogenic risk of endocardial compared to epicardial pacing, and the role of the transmural gradient of action potential duration (APD) and pacing location relative to scar on arrhythmogenic risk during endocardial pacing. Methods Computational models of ICM patients (n = 24) were used to simulate left ventricular (LV) epicardial and endocardial pacing 0.2–3.5 cm from a scar. Mechanisms were investigated in idealized models of the ventricular wall and scar. Simulations were run with/without a 20-ms transmural APD gradient in the physiological direction and with the gradient inverted. Dispersion of repolarization was computed as a surrogate of VT risk. Results Patient-specific models with a physiological APD gradient predict that endocardial pacing decreases VT risk (34%; P

BACKGROUND Antitachycardia pacing (ATP), which may avoid unnecessary implantable cardioverter-defibrillator (ICD) shocks, does not always terminate ventricular arrhythmias (VAs). Mean entropy calculated using cardiac magnetic resonance texture analysis (CMR-TA) has been shown to predict appropriate ICD therapy. We examined whether scar heterogeneity, quantified by mean entropy, is associated with ATP failure and explore potential mechanisms using computer modeling. METHODS A subanalysis of 114 patients undergoing CMR-TA where the primary endpoint was delivery of appropriate ICD therapy (ATP or shock therapy) was performed. Patients receiving appropriate ICD therapy (n = 33) were dichotomized into "successful ATP" versus "shock therapy" groups. In silico computer modeling was used to explore underlying mechanisms. RESULTS A total of 16 of 33 (48.5%) patients had successful ATP to terminate VA, and 17 of 33 (51.5%) patients required shock therapy. Mean entropy was significantly higher in the shock versus successful ATP group (6.1 ± 0.5 vs 5.5 ± 0.7, P = .037). Analysis of patients receiving ATP (n = 22) showed significantly higher mean entropy in the six of 22 patients that failed ATP (followed by rescue ICD shock) compared to 16 of 22 that had successful ATP (6.3 ± 0.7 vs 5.5 ± 0.7, P = .048). Computer modeling suggested inability of the paced wavefront in ATP to successfully propagate from the electrode site through patchy fibrosis as a possible mechanism of failed ATP. CONCLUSIONS Our findings suggest lower scar heterogeneity (mean entropy) is associated with successful ATP, whereas higher scar heterogeneity is associated with more aggressive VAs unresponsive to ATP requiring shock therapy that may be due to inability of the paced wavefront to propagate through scar and terminate the VA circuit.

Objective: Interstitial fibrosis is a pathological expansion of the heart's inter-cellular collagen matrix. It is a potential complication of nonischemic cardiomyopathy (NICM), a class of diseases involving electrical and or mechanical dysfunction of cardiac tissue not caused by atherosclerosis. Patients with NICM and interstitial fibrosis often suffer from life threatening arrhythmias, which we aim to simulate in this study. Methods: Our methodology builds on an efficient discrete finite element (DFE) method which allows for the representation of fibrosis as infinitesimal splits in a mesh. We update the DFE method with a local connectivity analysis which creates a consistent topology in the fibrosis network. This is particularly important in nonischemic disease due to the potential presence of large and contiguous fibrotic regions and therefore potentially complex fibrosis networks. Results: In experiments with an image-based model, we demonstrate that our methodology is able to simulate reentrant electrical events associated with cardiac arrhythmias. These reentries depended crucially upon sufficient fibrosis density, which was marked by conduction slowing at high pacing rates. We also created a 2D test-case which demonstrated that fibrosis topologies can modulate transient conduction block, and thereby reentrant activations. Conclusion: Ventricular arrhythmias due to interstitial fibrosis in NICM can be efficiently simulated using our methods in medical image based geometries. Furthermore, fibrosis topology modulates transient conduction block, and should be accounted for in electrophysiological simulations with interstitial fibrosis. Significance: Our study provides methodology which has the potential to predict arrhythmias and to optimize treatments non-invasively for nonischemic cardiomyopathies.

The effect of chronic ischemic scar on repolarization is unclear, with conflicting results from human and animal studies. An improved understanding of electrical remodeling within scar and border zone tissue may enhance substrate-guided ablation techniques for treatment of ventricular tachycardia. Computational modeling studies have suggested increased dispersion of repolarization during epicardial, but not endocardial, left ventricular pacing, in close proximity to scar. However, the effect of endocardial pacing near scarThe purpose of this study was to investigate the effect of scar and pacing location on local repolarization in a porcine myocardial infarction model.Six model pigs underwent late gadolinium enhancement cardiac magnetic resonance (LGE-CMR) imaging followed by electroanatomic mapping of the left ventricular endocardium. LGE-CMR images were registered to the anatomic shell and scar defined by LGE. Activation recovery intervals (ARIs), a surrogate for action potential duration, and local ARI gradients were calculated from unipolar electrograms within areas of late gadolinium enhancement (aLGE) and healthy myocardium.There was no significant difference between aLGE and healthy myocardium in mean ARI (304.20 ± 19.44 ms vs 300.59 ± 19.22 ms;Our findings suggest that changes in ARI are not an intrinsic property of surviving myocytes within scar, and endocardial pacing close to scar does not affect local repolarization.

Catheter ablation is currently the only curative treatment for scar-related ventricular tachycardias (VTs). However, not only are ablation procedures long, with relatively high risk, but success rates are punitively low, with frequent VT recurrence. Personalized in-silico approaches have the opportunity to address these limitations. However, state-of-the-art reaction diffusion (R-D) simulations of VT induction and subsequent circuits used for in-silico ablation target identification require long execution times, along with vast computational resources, which are incompatible with the clinical workflow. Here, we present the Virtual Induction and Treatment of Arrhythmias (VITA), a novel, rapid and fully automated computational approach that uses reaction-Eikonal methodology to induce VT and identify subsequent ablation targets. The rationale for VITA is based on finding isosurfaces associated with an activation wavefront that splits in the ventricles due to the presence of an isolated isthmus of conduction within the scar; once identified, each isthmus may be assessed for their vulnerability to sustain a reentrant circuit, and the corresponding exit site automatically identified for potential ablation targeting. VITA was tested on a virtual cohort of 7 post-infarcted porcine hearts and the results compared to R-D simulations. Using only a standard desktop machine, VITA could detect all scar-related VTs, simulating activation time maps and ECGs (for clinical comparison) as well as computing ablation targets in 48 minutes. The comparable VTs probed by the R-D simulations took 68.5 hours on 256 cores of high-performance computing infrastructure. The set of lesions computed by VITA was shown to render the ventricular model VT-free. VITA could be used in near real-time as a complementary modality aiding in clinical decision-making in the treatment of post-infarction VTs.

Background Computational models of the heart built from cardiac MRI and electrophysiology (EP) data have shown promise for predicting the risk of and ablation targets for myocardial infarction (MI) related ventricular tachycardia (VT), as well as to predict paced activation sequences in heart failure patients. However, most recent studies have relied on low resolution imaging data and little or no EP personalisation, which may affect the accuracy of model-based predictions. Objective To investigate the impact of model anatomy, MI scar morphology, and EP personalisation strategies on paced activation sequences and VT inducibility to determine the level of detail required to make accurate model-based predictions. Methods Imaging and EP data were acquired from a cohort of six pigs with experimentally induced MI. Computational models of ventricular anatomy, incorporating MI scar, were constructed including bi-ventricular or left ventricular (LV) only anatomy, and MI scar morphology with varying detail. Tissue conductivities and action potential duration (APD) were fitted to 12-lead ECG data using the QRS duration and the QT interval, respectively, in addition to corresponding literature parameters. Paced activation sequences and VT induction were simulated. Simulated paced activation and VT inducibility were compared between models and against experimental data. Results Simulations predict that the level of model anatomical detail has little effect on simulated paced activation, with all model predictions comparing closely with invasive EP measurements. However, detailed scar morphology from high-resolution images, bi-ventricular anatomy, and personalized tissue conductivities are required for predict experimental VT outcome. Conclusion This study provides clear guidance for model generation based on clinical data. While a representing high level of anatomical and scar detail will require high-resolution image acquisition, EP personalisation based on 12-lead ECG can be readily incorporated into modelling pipelines, as such data is widely available.

Myocardial infarction leads to permanent tissue scars that impairs cardiac function and can result in heart failure. The use of engineered heart tissue (EHT) and conductive polymers (CP) in regenerative medicine aims to assist tissue recovery and improve of cardiac function. However, the attachment of EHT to the epicardium may disrupt tissue electrophysiology and lead to an increased arrhythmia risk. We investigated the role that material properties, i.e. EHT and CP conductivity and thickness and EHT-tissue contact area, play in cardiac recovery, in the presence of scars with different depth, length and conductivity. We created a 2D model to simulate EHT and CP placed over a scar in rabbit ventricle. We performed a Global Sensitivity Analysis (GSA) to identify which parameters had the largest impact on electrical propagation across the scar and the EHT. Our model showed that in case of non-transmural scar the main determinants were scar depth and conductivity, explaining 30% and 33% of the variance, respectively. However, in case of transmural scar, the model indicated the EHT conductivity and the extent of the EHT-tissue contact explain 40% and 46% of the variance, respectively.

The implanted cardioverter defibrillator (ICD) is an effective direct therapy for the treatment of cardiac arrhythmias, including ventricular tachycardia (VT). Anti-tachycardia pacing (ATP) is often applied by the ICD as the first mode of therapy, but is often found to be ineffective, particularly for fast VTs. In such cases, strong, painful and damaging backup defibrillation shocks are applied by the device. Here, we propose two novel electrode configurations: “bipolar” and “transmural” which both combine the concept of targeted shock delivery with the advantage of reduced energy required for VT termination. We perform an in silico study to evaluate the efficacy of VT termination by applying one single (low-energy) monophasic shock from each novel configuration, comparing with conventional ATP therapy. Both bipolar and transmural configurations are able to achieve a higher efficacy (93% and 85%) than ATP (45%), with energy delivered similar to and two orders of magnitudes smaller than conventional ICD defibrillation shocks, respectively. Specifically, the transmural configuration (which applies the shock vector directly across the scar substrate sustaining the VT) is most efficient, requiring typically less than 1 J shock energy to achieve a high efficacy. The efficacy of both bipolar and transmural configurations are higher when applied to slow VTs (100% and 97%) compared to fast VTs (57% and 29%). Both novel electrode configurations introduced are able to improve electrotherapy efficacy while reducing the overall number of required therapies and need for strong backup shocks., Highlights • Low-energy electrotherapy protocols suggest promise of reducing strong shocks. • Our 2 novel electrode configurations specifically target the arrhythmic substrate. • Their efficacies on terminating sustained VTs are higher than ATP. • Our ‘transmural’ configuration requires

Cardiac resynchronization therapy (CRT) is an effective treatment for heart failure (HF) patients with an electrical substrate pathology causing ventricular dyssynchrony. However 40-50% of patients do not respond to treatment. Cardiac modeling of the electrophysiology, electromechanics, and hemodynamics of the heart has been used to study mechanisms behind HF pathology and CRT response. Recently, multi-scale dyssynchronous HF models have been used to study optimal device settings and optimal lead locations, investigate the underlying cardiac pathophysiology, as well as investigate emerging technologies proposed to treat cardiac dyssynchrony. However the breadth of patient and experimental data required to create and parameterize these models and the computational resources required currently limits the use of these models to small patient numbers. In the future, once these technical challenges are overcome, biophysically based models of the heart have the potential to become a clinical tool to aid in the diagnosis and treatment of HF.

Aims Potential advantages of real-time magnetic resonance imaging (MRI)-guided electrophysiology (MR-EP) include contemporaneous three-dimensional substrate assessment at the time of intervention, improved procedural guidance, and ablation lesion assessment. We evaluated a novel real-time MR-EP system to perform endocardial voltage mapping and assessment of delayed conduction in a porcine ischaemia–reperfusion model. Methods and results Sites of low voltage and slow conduction identified using the system were registered and compared to regions of late gadolinium enhancement (LGE) on MRI. The Sorensen–Dice similarity coefficient (DSC) between LGE scar maps and voltage maps was computed on a nodal basis. A total of 445 electrograms were recorded in sinus rhythm (range: 30–186) using the MR-EP system including 138 electrograms from LGE regions. Pacing captured at 103 sites; 47 (45.6%) sites had a stimulus-to-QRS (S-QRS) delay of ≥40 ms. Using conventional (0.5–1.5 mV) bipolar voltage thresholds, the sensitivity and specificity of voltage mapping using the MR-EP system to identify MR-derived LGE was 57% and 96%, respectively. Voltage mapping had a better predictive ability in detecting LGE compared to S-QRS measurements using this system (area under curve: 0.907 vs. 0.840). Using an electrical threshold of 1.5 mV to define abnormal myocardium, the total DSC, scar DSC, and normal myocardium DSC between voltage maps and LGE scar maps was 79.0 ± 6.0%, 35.0 ± 10.1%, and 90.4 ± 8.6%, respectively. Conclusion Low-voltage zones and regions of delayed conduction determined using a real-time MR-EP system are moderately associated with LGE areas identified on MRI.

Cardiac resynchronization therapy (CRT) is an effective treatment for heart failure patients. Suboptimal pacing timings and locations have been identified as causes for nonresponse to CRT. Patient specific computer models allow for the prediction of the electrical activation pattern on the ventricles, which can then be used to optimise CRT lead location. The electrical activation of the heart depends on the underlying cardiac substrate. The electrical properties of the heart have been found to be heterogeneous, with scar, functional block, septal slowing, and fast endocardial conduction impacting the electrical activation across the ventricles. Non-Invasive data from 14 patients were used to create computer models of the heart. The patient specific models were then used to assess the importance of the heterogeneous cardiac substrates on accurately predicting the electrical activation pattern of the ventricles. Fast endocardial conduction was found to be the most important factor in accurately predicting the electrical activation of the heart in CRT patients.

Patients who present with non-ischemic dilated cardiomyopathy and enhancement on late gadolinium magnetic resonance imaging (LGE-CMR), are at high risk of sudden cardiac death. Further risk stratification of these patients based on LGE-CMR may be improved through better understanding of fibrosis micro-structure. Our aim is to examine variations in fibrosis micro-structure based on LGE imaging, and quantify the effect on reentry in-ducibility. 2D Computational models were created from a single short axis LGE-CMR image, with variations in fibrosis type (interstitial, replacement) and density. For each fibrosis-type density combination 10 different models were created, each representing a separate random realization. In total 200 models were tested. Reentry inducibility showed a dependence on fibrosis type and density as well as on the specific random realization of the type-density combination.

Cardiac Resynchronization Therapy (CRT) is associated with increased arrhythmogenic risk in infarct patients when pacing adjacent to a scar. We investigated the role of pacing location relative to scar on dispersion of repolarization, as a surrogate for arrhythmogenic risk. For this task, we developed a personalization and simulation pipeline that allows fast development of personalized computational models and simulation of cardiac electrophysiology. Twenty four models of left ventricular anatomy and scar morphology were built and repolarization sequences were simulated. Simulation results show that CRT increases dispersion of repolarization around a scar when pacing adjacent to it, thus, providing a mechanistic explanation of increased arrhythmogenic risk in infarct patients undergoing CRT.

Cardiac modeling is being used in a variety of ways to support the tests of new drugs, the development of new medical devices and of non-invasive diagnostic techniques. Computer models have become valuable tools for the study and comprehension of the complex phenomena of cardiac electrophysiology. However, the complexity, the multi-scale and multi-physics nature of cardiac modeling still restrict its use to a few specialized research centers in the world. In addition, the issue of sharing and re-using such models has proven to be particularly problematic, with published models often lacking information that is required to accurately reproduce published results. In this work, with the aim of tackling the aforementioned issues, we present a web portal that provides support for cardiac electrophysiology modeling. This framework integrates different computer tools and allows one to bypass many complex steps during the development and use of cardiac models. The process of model development is supported by a Web-based editor for CellML, a mark-up language dedicated to the description of biological structures, processes and the associated models. The implementation of the cardiac cell models is automatically provided by a code generator that translates models described in CellML language to executable code that allows one to manipulate and solve the models numerically. The set up and use of the simulator is supported by a user-friendly graphical interface that offers the tasks of simulation configuration and execution, storage of results and basic visualization. All the tools are integrated in a Web Portal. As a result, the complex techniques and the know-how behind cardiac modeling are all taken care of by the web distributed applications.

Advanced medical imaging technologies provide a wealth of information on cardiac anatomy and structure at a paracellular resolution, allowing to identify micro-structural discontinuities which disrupt the intracellular matrix. Current state-of-the-art computer models built upon such datasets account for increasingly finer anatomical details, however, structural discontinuities at the paracellular level are typically discarded in the model generation process, owing to the significant costs which incur when using high resolutions for explicit representation. In this study, a novel discontinuous finite element (dFE) approach for discretizing the bidomain equations is presented, which accounts for fine-scale structures in a computer model without the need to increase spatial resolution. In the dFE method this is achieved by imposing infinitely thin lines of electrical insulation along edges of finite elements which approximate the geometry of discontinuities in the intracellular matrix. Simulation results demonstrate that the dFE approach accounts for effects induced by microscopic size scale discontinuities, such as the formation of microscopic virtual electrodes, with vast computational savings as compared to high resolution continuous finite element models. Moreover, the method can be implemented in any standard continuous finite element code with minor effort.

We present ideas and first results on a GPU acceleration of a non-linear solver embedded into the biomedical application code CARP. The linear system solvers have been transferred already in the past and so we concentrate on how to extend the GPU acceleration to larger portions of the code. The finite element assembling of stiffness and mass matrices takes at least 50 % of the CPU time and therefore we investigate this process for the bidomain equations but with focus on later use in non-linear and/or time-dependent problems. The CUDA code for matrix calculation and assembling is faster by a factor up to \(90\) compared to a single CPU core. The routines were integrated to CARP’s main code and they are already used to assemble the FE matrices of the bidomain model. Further performance studies are still required for the bidomain-mechanics model.

Driven by recent advances in medical imaging, image segmentation and numerical techniques computer models of ventricular electrophysiology account for increasingly finer levels of anatomical and biophysical detail. However, considering the large number of model parameters involved parametrization poses a major challenge. A minimum requirement in combined experimental and modeling studies which aim at making specific predictions on a case by case basis is to achieve good agreement in activation and repolarization sequences between model and experiment or patient data. In this study we propose basic techniques which aide in determining bidomain parameters to match ventricular activation sequences. Two specific aspects will be considered. First, conduction velocity in the ventricles is orthotropic and varies in space. An iterative parametrization algorithm is implemented which determines appropriate conductivities which yield prescribed velocities. Secondly, impulse propagation in the ventricles is initiated subendocardially at Purkinje-ventricular junctions, the terminal endings of Purkinje system (PS), and, thus, the PS plays a key role in determining the shape of activation wave fronts as reflected in the QRS complex of the electro-cardiogram (ECG). While ventricular models equipped with generic PS topologies match well with experimental observation in terms of epicardial breakthrough sites, predicted ECGs match poorly with known key ECG characteristics.

The presence of connective tissue as well as interstitial clefts forms a natural barrier to the electrical propagation in the heart. At a microscopic scale, such uncoupling structures change the pattern of the electrical conduction from uniform towards complex and may play a role in the genesis of cardiac arrhythmias. The anatomical diversity of conduction structures and their topology at a microscopic size scale is overwhelming for experimental techniques. Mathematical models have been often employed to study the behavior of the electrical propagation at a sub-cellular level. However, very fine and computationally expensive meshes are required to capture all microscopic details found in the cardiac tissue. In this work, we present a numerical technique based on the finite element method which allows to reproduce the effects of microscopic conduction barriers caused by the presence of uncoupling structures without actually resolving these structures in a high resolution mesh, thereby reducing the computational costs significantly.

The cardiac Monodomain model is a mathematical model extensively used in studies of propagation of bioelectric wavefronts in the heart. To be able to use the model for complex and large cardiac simulations, such as the case of whole heart and 3D simulations, some parameters of the model that are known to physiologically vary in space, such as the intracellular conductivity, are traditionally kept constant at effective values. These effective values can be obtained via a mathematical procedure called homogenization. In this work we revisit the classical homogenized monodomain formulation to evaluate its ability to reproduce the situation of low gap junctional coupling. This situation arises in many pathological conditions such as during ischemia. Our numerical results suggest some limitations of the homogenized cardiac Monodomain model under these conditions in terms of computed conduction velocity and Action Potential waverforms.

We developed a computer model for the electrophysiology of cardiac cells from the mouse sinoatrial node. The available biophysical data have been incorporated into the model to quantify the ionic currents verified in these specific group of cardiac cells. The model is based on a previous approach describing the action potential in mouse ventricular cells and whenever possible, the mathematical expressions modeling ionic currents were based on whole cell voltage-clamp data from enzymatically isolated mouse sinoatrial node myocytes. The membrane model is coupled to equations describing the homeostasis of Na + , K + and Ca2 + , as well as intracellular Ca2 + dynamics. The resulting formulation is able to reproduce some important and distinguish aspects of the action potential of these myocytes.

Electrical propagation in cardiac tissue is a discrete or discontinuous phenomenon that reflects the complexity of the anatomical structures and their organization in the heart, such as myocytes, gap junctions, microvessels, and extracellular matrix, just to name a few. Discrete models or microscopic and discontinuous models are, so far, the best options to accurately study how structural properties of cardiac tissue influence electrical propagation. These models are, however, inappropriate in the context of large scale simulations, which have been traditionally performed by the use of continuum and macroscopic models, such as the monodomain and the bidomain models. However, continuum models may fail to reproduce many important physiological and physiopathological aspects of cardiac electrophysiology, for instance, those related to slow conduction. In this study, we develop a new mathematical model that combines characteristics of both continuum and discrete models. The new model was evaluated in scenarios of low gap-junctional coupling, where slow conduction is observed, and was able to reproduce conduction block, increase of the maximum upstroke velocity and of the repolarization dispersion. None of these features can be captured by continuum models. In addition, the model overcomes a great disadvantage of discrete models, as it allows variation of the spatial resolution within a certain range.