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Hypertrophic cardiomyopathy (HCM) is associated with risk of sudden cardiac death (SCD) due to ventricular arrhythmias (VAs) arising from the proliferation of fibrosis in the heart. Current clinical risk stratification criteria inadequately identify at-risk patients in need of primary prevention of VA. Here, we use mechanistic computational modeling of the heart to analyze how HCM-specific remodeling promotes arrhythmogenesis and to develop a personalized strategy to forecast risk of VAs in these patients. We combine contrast-enhanced cardiac magnetic resonance imaging and T1 mapping data to construct digital replicas of HCM patient hearts that represent the patient-specific distribution of focal and diffuse fibrosis and evaluate the substrate propensity to VA. Our analysis indicates that the presence of diffuse fibrosis, which is rarely assessed in these patients, increases arrhythmogenic propensity. In forecasting future VA events in HCM patients, the imaging-based computational heart approach achieved 84.6%, 76.9%, and 80.1% sensitivity, specificity, and accuracy, respectively, and significantly outperformed current clinical risk predictors. This novel VA risk assessment may have the potential to prevent SCD and help deploy primary prevention appropriately in HCM patients., Competing Interests: RO, EB, AP, SZ, MC, MA, DL, PB, NT No competing interests declared, (© 2022, O'Hara et al.)

Background: Adults with repaired tetralogy of Fallot (rTOF) are at increased risk for ventricular tachycardia (VT) due to fibrotic remodeling of the myocardium. However, the current clinical guidelines for VT risk stratification and subsequent implantable cardioverter-defibrillator deployment for primary prevention of sudden cardiac death in rTOF remain inadequate., Objective: The purpose of this study was to determine the feasibility of using an rTOF-specific virtual-heart approach to identify patients stratified incorrectly as being at low VT risk by current clinical criteria., Methods: This multicenter retrospective pilot study included 7 adult rTOF patients who were considered low risk for VT based on clinical criteria. Patient-specific computational heart models were generated from late gadolinium enhanced magnetic resonance imaging (LGE-MRI), incorporating the individual distribution of rTOF fibrotic remodeling in both ventricles. Simulations of rapid pacing determined VT inducibility. Model creation and simulations were performed by operators blinded to clinical outcome., Results: Two patients in the study experienced clinical VT. The virtual hearts constructed from LGE-MRI scans of 7 rTOF patients correctly predicted reentrant VT in the models from VT-positive patients and no arrhythmia in those from VT-negative patients. There were no statistically significant differences in clinical criteria commonly used to assess VT risk, including QRS duration and age, between patients who did and those who did not experience clinical VT., Conclusion: This study demonstrates the feasibility of image-based virtual-heart modeling in patients with congenital heart disease and structurally abnormal hearts. It highlights the potential of the methodology to improve VT risk stratification in patients with rTOF., (Copyright © 2019 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Atrial fibrillation is the most common arrhythmia in humans and is associated with high morbidity, mortality and health-related expenses. Computational approaches have been increasingly utilized in atrial electrophysiology. In this review we summarize the recent advancements in atrial fibrillation modeling at the organ scale. Multi-scale atrial models now incorporate high level detail of atrial anatomy, tissue ultrastructure and fibrosis distribution. We provide the state-of-the art methodologies in developing personalized atrial fibrillation models with realistic geometry and tissue properties. We then focus on the use of multi-scale atrial models to gain mechanistic insights in AF. Simulations using atrial models have provided important insight in the mechanisms underlying AF, showing the importance of the atrial fibrotic substrate and altered atrial electrophysiology in initiation and maintenance of AF. Last, we summarize the translational evidence that supports incorporation of computational modeling in clinical practice for development of personalized treatment strategies for patients with AF. In early-stages clinical studies, AF models successfully identify patients where pulmonary vein isolation alone is not adequate for treatment of AF and suggest novel targets for ablation. We conclude with a summary of the future developments envisioned for the field of atrial computational electrophysiology., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Aims: Efforts to improve ablation success rates in persistent atrial fibrillation (AF) patients by targeting re-entrant driver (RD) sites have been hindered by weak mechanistic understanding regarding emergent RDs localization following initial fibrotic substrate modification. This study aimed to systematically assess arrhythmia dynamics after virtual ablation of RD sites in computational models., Methods and Results: Simulations were conducted in 12 patient-specific atrial models reconstructed from pre-procedure late gadolinium-enhanced magnetic resonance imaging scans. In a previous study involving these same models, we comprehensively characterized pre-ablation RDs in simulations conducted with either 'average human AF'-based electrophysiology (i.e. EPavg) or ±10% action potential duration or conduction velocity (i.e. EPvar). Re-entrant drivers seen under the EPavg condition were virtually ablated and the AF initiation protocol was re-applied. Twenty-one emergent RDs were observed in 9/12 atrial models (1.75 ± 1.35 emergent RDs per model); these dynamically localized to boundary regions between fibrotic and non-fibrotic tissue. Most emergent RD locations (15/21, 71.4%) were within 0.1 cm of sites where RDs were seen pre-ablation in simulations under EPvar conditions. Importantly, this suggests that the level of uncertainty in our models' ability to predict patient-specific ablation targets can be substantially mitigated by running additional simulations that include virtual ablation of RDs. In 7/12 atrial models, at least one episode of macro-reentry around ablation lesion(s) was observed., Conclusion: Arrhythmia episodes after virtual RD ablation are perpetuated by both emergent RDs and by macro-reentrant circuits formed around lesions. Custom-tailoring of ablation procedures based on models should take steps to mitigate these sources of AF recurrence.

Intra-aortic balloon pump (IABP) is normally contraindicated in significant aortic regurgitation (AR). It causes and aggravates pre-existing AR while performing well in the event of mitral regurgitation (MR). Indirect parameters, such as the mean systolic pressure, product of heart rate and peak systolic pressure, and pressure-volume are used to quantify the effect of IABP on ventricular workload. However, to date, no studies have directly quantified the reduction in workload with IABP. The goal of this study is to examine the effect of IABP therapy on ventricular mechanics under valvular insufficiency by using a computational model of the heart. For this purpose, the 3D electromechanical model of the failing ventricles used in previous studies was coupled with a lumped parameter model of valvular regurgitation and the IABP-treated vascular system. The IABP therapy was disturbed in terms of reducing the myocardial tension generation and contractile ATP consumption by valvular regurgitation, particularly in the AR condition. The IABP worsened the problem of ventricular expansion induced as a result of the regurgitated blood volume during the diastole under the AR condition. The IABP reduced the LV stroke work in the AR, MR, and no regurgitation conditions. Therefore, the IABP helped the ventricle to pump blood and reduced the ventricular workload. In conclusion, the IABP partially performed its role in the MR condition. However, it was disturbed by the AR and worsened the cardiovascular responses that followed the AR. Therefore, this study computationally proved the reason for the clinical contraindication of IABP in AR patients.

This study hypothesized that a left ventricular assist device (LVAD) shortens the electromechanical delay (EMD) by mechanical unloading. The goal of this study is to examine, by computational modeling, the influence of LVAD on EMD for four heart failure (HF) cases ranging from mild HF to severe HF. We constructed an integrated model of an LVAD-implanted cardiovascular system, then we altered the Ca 2+ transient magnitude, with scaling factors 1, 0.9, 0.8, and 0.7 representing HF1, HF2, HF3, and HF4, respectively, in order of increasing HF severity. The four HF conditions are classified into two groups. Group one is the four HF conditions without LVAD, and group two is the conditions treated with continuous LVAD pump. The single-cell mechanical responses showed that EMD was prolonged with the higher load. The findings indicated that in group one, the HF-induced Ca2 + transient remodeling prolonged the mechanical activation time (MAT) and decreased the contractile tension, which reduced the left ventricle (LV) pressure, and increased the end-diastolic strain. In group two, LVAD shortened MAT of the ventricles. Furthermore, LVAD reduced the contractile tension, and end-diastolic strain, but increased the aortic pressure. The computational study demonstrated that LVAD shortens EMD by mechanical unloading of the ventricle.

Key Points: Optogenetics has emerged as a potential alternative to electrotherapy for treating heart rhythm disorders, but its applicability for terminating atrial arrhythmias remains largely unexplored. We used computational models reconstructed from clinical MRI scans of fibrotic patient atria to explore the feasibility of optogenetic termination of atrial tachycardia (AT), comparing two different illumination strategies: distributed vs. targeted. We show that targeted optogenetic stimulation based on automated, non-invasive flow-network analysis of patient-specific re-entry morphology may be a reliable approach for identifying the optimal illumination target in each individual (i.e. the critical AT isthmus). The above-described approach yields very high success rates (up to 100%) and requires dramatically less input power than distributed illumination We conclude that simulations in patient-specific models show that targeted light pulses lasting longer than the AT cycle length can efficiently and reliably terminate AT if the human atria can be successfully light-sensitized via gene delivery of ChR2., Abstract: Optogenetics has emerged as a potential alternative to electrotherapy for treating arrhythmia, but feasibility studies have been limited to ventricular defibrillation via epicardial light application. Here, we assess the efficacy of optogenetic atrial tachycardia (AT) termination in human hearts using a strategy that targets for illumination specific regions identified in an automated manner. In three patient-specific models reconstructed from late gadolinium-enhanced MRI scans, we simulated channelrhodopsin-2 (ChR2) expression via gene delivery. In all three models, we attempted to terminate re-entrant AT (induced via rapid pacing) via optogenetic stimulation. We compared two strategies: (1) distributed illumination of the endocardium by multi-optrode grids (number of optrodes, N opt  = 64, 128, 256) and (2) targeted illumination of the critical isthmus, which was identified via analysis of simulated activation patterns using an algorithm based on flow networks. The illuminated area and input power were smaller for the targeted approach (19-57.8 mm 2 ; 0.6-1.8 W) compared to the sparsest distributed arrays (N opt  = 64; 124.9 ± 6.3 mm 2 ; 3.9 ± 0.2 W). AT termination rates for distributed illumination were low, ranging from <5% for short pulses (1/10 ms long) to ∼20% for longer stimuli (100/1000 ms). When we attempted to terminate the same AT episodes with targeted illumination, outcomes were similar for short pulses (1/10 ms long: 0% success) but improved for longer stimuli (100 ms: 54% success; 1000 ms: 90% success). We conclude that simulations in patient-specific models show that light pulses lasting longer than the AT cycle length can efficiently and reliably terminate AT in atria light-sensitized via gene delivery. We show that targeted optogenetic stimulation based on analysis of AT morphology may be a reliable approach for defibrillation and requires less power than distributed illumination., (© 2017 The Authors. The Journal of Physiology © 2017 The Physiological Society.)

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, causing morbidity and mortality in millions worldwide. The atria of patients with persistent AF (PsAF) are characterized by the presence of extensive and distributed atrial fibrosis, which facilitates the formation of persistent reentrant drivers (RDs, i.e., spiral waves), which promote fibrillatory activity. Targeted catheter ablation of RD-harboring tissues has shown promise as a clinical treatment for PsAF, but the outcomes remain sub-par. Personalized computational modeling has been proposed as a means of non-invasively predicting optimal ablation targets in individual PsAF patients, but it remains unclear how RD localization dynamics are influenced by inter-patient variability in the spatial distribution of atrial fibrosis, action potential duration (APD), and conduction velocity (CV). Here, we conduct simulations in computational models of fibrotic atria derived from the clinical imaging of PsAF patients to characterize the sensitivity of RD locations to these three factors. We show that RDs consistently anchor to boundaries between fibrotic and non-fibrotic tissues, as delineated by late gadolinium-enhanced magnetic resonance imaging, but those changes in APD/CV can enhance or attenuate the likelihood that an RD will anchor to a specific site. These findings show that the level of uncertainty present in patient-specific atrial models reconstructed without any invasive measurements (i.e., incorporating each individual's unique distribution of fibrotic tissue from medical imaging alongside an average representation of AF-remodeled electrophysiology) is sufficiently high that a personalized ablation strategy based on targeting simulation-predicted RD trajectories alone may not produce the desired result.

Background: Left atrial flutter (LAFL) occurs in patients after atrial fibrillation ablation. Identification of optimal ablation targets to terminate LAFL remains challenging., Objective: The purpose of this study was to use patient-specific models to simulate LAFL and predict optimal ablation targets using a novel approach based on flow network theory., Methods: Late gadolinium-enhanced cardiac magnetic resonance scans from 10 patients with LAFL were used to construct atrial models incorporating fibrosis by investigators blinded to procedural findings. Rapid pacing was applied in silico to induce LAFL. In each LAFL, we represented reentrant wave propagation as an electric flow network and identified the "minimum cut" (MC), which was the smallest amount of tissue that separated the flow into 2 discontinuous components. In silico ablation was applied at MCs, and targets were compared to those that terminated LAFL during catheter ablation., Results: Patient-specific atrial models were successfully generated from patient scans. LAFL was induced in 7 of 10 models. Ablation of MCs terminated LAFL in 4 models and produced new, slower LAFL morphologies in the other 3. For the latter cases, flow analysis was repeated to identify MCs of emergent LAFLs. Ablation of these MCs terminated emergent LAFLs. The MC-based ablation lesions in simulations were similar in length and location to ablation targets that terminated LAFL during catheter ablation for these 7 patients., Conclusion: Personalized atrial simulations can predict ablation targets for LAFL. These simulations provide a powerful tool for planning ablation procedures and may reduce procedural times and complications., (Copyright © 2016 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Aims: The mechanisms underlying persistent atrial fibrillation (AF) in patients with atrial fibrosis are poorly understood. The goal of this study was to use patient-derived atrial models to test the hypothesis that AF re-entrant drivers (RDs) persist only in regions with specific fibrosis patterns., Methods and Results: Twenty patients with persistent AF (PsAF) underwent late gadolinium-enhanced MRI to detect the presence of atrial fibrosis. Segmented images were used to construct personalized 3D models of the fibrotic atria with biophysically realistic atrial electrophysiology. In each model, rapid pacing was applied to induce AF. AF dynamics were analysed and RDs were identified using phase mapping. Fibrosis patterns in RD regions were characterized by computing maps of fibrosis density (FD) and entropy (FE). AF was inducible in 13/20 models and perpetuated by few RDs (2.7 ± 1.5) that were spatially confined (trajectory of phase singularities: 7.6 ± 2.3 mm). Compared with the remaining atrial tissue, regions where RDs persisted had higher FE (IQR: 0.42-0.60 vs. 0.00-0.40, P < 0.05) and FD (IQR: 0.59-0.77 vs. 0.00-0.33, P < 0.05). Machine learning classified RD and non-RD regions based on FD and FE and identified a subset of fibrotic boundary zones present in 13.8 ± 4.9% of atrial tissue where 83.5 ± 2.4% of all RD phase singularities were located., Conclusion: Patient-derived models demonstrate that AF in fibrotic substrates is perpetuated by RDs persisting in fibrosis boundary zones characterized by specific regional fibrosis metrics (high FE and FD). These results provide new insights into the mechanisms that sustain PsAF and could pave the way for personalized, MRI-based management of PsAF., (Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For permissions please email: journals.permissions@oup.com.)

Cardiac optogenetics is emerging as an exciting new potential avenue to enable spatiotemporally precise control of excitable cells and tissue in the heart with low-energy optical stimuli. This approach involves the expression of exogenous light-sensitive proteins (opsins) in target heart tissue via viral gene or cell delivery. Preliminary experiments in optogenetically-modified cells, tissue, and organisms have made great strides towards demonstrating the feasibility of basic applications, including the use of light stimuli to pace or disrupt reentrant activity. However, it remains unknown whether techniques based on this intriguing technology could be scaled up and used in humans for novel clinical applications, such as pain-free optical defibrillation or dynamic modulation of action potential shape. A key step towards answering such questions is to explore potential optogenetics-based therapies using sophisticated computer simulation tools capable of realistically representing opsin delivery and light stimulation in biophysically detailed, patient-specific models of the human heart. This review provides (1) a detailed overview of the methodological developments necessary to represent optogenetics-based solutions in existing virtual heart platforms and (2) a survey of findings that have been derived from such simulations and a critical assessment of their significance with respect to the progress of the field., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Cardiac defibrillation, as accomplished nowadays by automatic, implantable devices, constitutes the most important means of combating sudden cardiac death. Advancing our understanding towards a full appreciation of the mechanisms by which a shock interacts with the heart, particularly under diseased conditions, is a promising approach to achieve an optimal therapy. The aim of this article is to assess the current state-of-the-art in whole-heart defibrillation modelling, focusing on major insights that have been obtained using defibrillation models, primarily those of realistic heart geometry and disease remodelling. The article showcases the contributions that modelling and simulation have made to our understanding of the defibrillation process. The review thus provides an example of biophysically based computational modelling of the heart (i.e. cardiac defibrillation) that has advanced the understanding of cardiac electrophysiological interaction at the organ level, and has the potential to contribute to the betterment of the clinical practice of defibrillation.

The purpose of this study was to investigate whether caveolin-3 (Cav3) regulates localization of β2-adrenergic receptor (β2AR) and its cAMP signaling in healthy or failing cardiomyocytes. We co-expressed wildtype Cav3 or its dominant-negative mutant (Cav3DN) together with the Förster resonance energy transfer (FRET)-based cAMP sensor Epac2-camps in adult rat ventricular myocytes (ARVMs). FRET and scanning ion conductance microscopy were used to locally stimulate β2AR and to measure cytosolic cAMP. Cav3 overexpression increased the number of caveolae and decreased the magnitude of β2AR-cAMP signal. Conversely, Cav3DN expression resulted in an increased β2AR-cAMP response without altering the whole-cell L-type calcium current. Following local stimulation of Cav3DN-expressing ARVMs, β2AR response could only be generated in T-tubules. However, the normally compartmentalized β2AR-cAMP signal became diffuse, similar to the situation observed in heart failure. Finally, overexpression of Cav3 in failing myocytes led to partial β2AR redistribution back into the T-tubules. In conclusion, Cav3 plays a crucial role for the localization of β2AR and compartmentation of β2AR-cAMP signaling to the T-tubules of healthy ARVMs, and overexpression of Cav3 in failing myocytes can partially restore the disrupted localization of these receptors., (Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Mechanisms of atrial fibrillation (AF) initiation are incompletely understood. We hypothesized that rate-dependent changes (restitution) in action potential duration (APD) and activation latency are central targets for clinical interventions that induce AF. We tested this hypothesis using clinical experiments and computer models., Methods and Results: In 50 patients (20 persistent, 23 paroxysmal AF, 7 controls), we used monophasic action potential catheters to define left atrial APD restitution, activation latency, and AF incidence from premature extrastimuli. Isoproterenol (n=14), adenosine (n=10), or rapid pacing (n=36) was then initiated to determine impact on these parameters. Compared with baseline in AF patients, isoproterenol and rapid pacing decreased activation latency (64±14 versus 31±13 versus 24±14 ms; P<0.05), steepened maximum APD restitution slope (0.8±0.7 versus 1.7±0.5 versus 1.1±0.5; P<0.05), and increased AF incidence (12% versus 64% versus 84%; P<0.05). Conversely, adenosine shortened APD (P<0.05), yet increased activation latency (86±27 ms; P=0.002) so that maximum APD restitution slope did not steepen (1.0±0.5; P=NS), and AF incidence was unchanged (10%; P=NS). In controls, no intervention steepened APD restitution or initiated AF. Computational modeling revealed that isoproterenol steepened APD restitution by increased L-type calcium current and decreased activation latency via enhanced rapid delayed potassium reactifier current inactivation, whereas rapid pacing steepened APD restitution via increased cardiac inward potassium rectifier current., Conclusions: Steep APD restitution is a common pathway for AF initiation by isoproterenol and tachycardia via reduced activation latency that enables engagement of steep APD restitution at rapid rates. Modeling suggests that AF initiation from each intervention uses distinct ionic mechanisms. This insight may help design interventions to prevent AF.

Cardiac resynchronization therapy (CRT) is an established clinical treatment modality that aims to recoordinate contraction of the heart in dyssynchrous heart failure (DHF) patients. Although CRT reduces morbidity and mortality, a significant percentage of CRT patients fail to respond to the therapy, reflecting an insufficient understanding of the electromechanical activity of the DHF heart. Computational models of ventricular electromechanics are now poised to fill this knowledge gap and provide a comprehensive characterization of the spatiotemporal electromechanical interactions in the normal and DHF heart. The objective of this paper is to demonstrate the powerful utility of computational models of ventricular electromechanics in characterizing the relationship between the electrical and mechanical activation in the DHF heart, and how this understanding can be utilized to devise better CRT strategies. The computational research presented here exploits knowledge regarding the three dimensional distribution of the electromechanical delay, defined as the time interval between myocyte depolarization and onset of myofiber shortening, in determining the optimal location of the LV pacing electrode for CRT. The simulation results shown here also suggest utilizing myocardial efficiency and regional energy consumption as a guide to optimize CRT., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Electrical waves traveling throughout the myocardium elicit muscle contractions responsible for pumping blood throughout the body. The shape and direction of these waves depend on the spatial arrangement of ventricular myocytes, termed fiber orientation. In computational studies simulating electrical wave propagation or mechanical contraction in the heart, accurately representing fiber orientation is critical so that model predictions corroborate with experimental data. Typically, fiber orientation is assigned to heart models based on Diffusion Tensor Imaging (DTI) data, yet few alternative methodologies exist if DTI data is noisy or absent. Here we present a novel Laplace-Dirichlet Rule-Based (LDRB) algorithm to perform this task with speed, precision, and high usability. We demonstrate the application of the LDRB algorithm in an image-based computational model of the canine ventricles. Simulations of electrical activation in this model are compared to those in the same geometrical model but with DTI-derived fiber orientation. The results demonstrate that activation patterns from simulations with LDRB and DTI-derived fiber orientations are nearly indistinguishable, with relative differences ≤6%, absolute mean differences in activation times ≤3.15 ms, and positive correlations ≥0.99. These results convincingly show that the LDRB algorithm is a robust alternative to DTI for assigning fiber orientation to computational heart models.

A long-sought, and thus far elusive, goal has been to develop drugs to manage diseases of excitability. One such disease that affects millions each year is cardiac arrhythmia, which occurs when electrical impulses in the heart become disordered, sometimes causing sudden death. Pharmacological management of cardiac arrhythmia has failed because it is not possible to predict how drugs that target cardiac ion channels, and have intrinsically complex dynamic interactions with ion channels, will alter the emergent electrical behavior generated in the heart. Here, we applied a computational model, which was informed and validated by experimental data, that defined key measurable parameters necessary to simulate the interaction kinetics of the anti-arrhythmic drugs flecainide and lidocaine with cardiac sodium channels. We then used the model to predict the effects of these drugs on normal human ventricular cellular and tissue electrical activity in the setting of a common arrhythmia trigger, spontaneous ventricular ectopy. The model forecasts the clinically relevant concentrations at which flecainide and lidocaine exacerbate, rather than ameliorate, arrhythmia. Experiments in rabbit hearts and simulations in human ventricles based on magnetic resonance images validated the model predictions. This computational framework initiates the first steps toward development of a virtual drug-screening system that models drug-channel interactions and predicts the effects of drugs on emergent electrical activity in the heart.

Computational modeling has traditionally played an important role in dissecting the mechanisms for cardiac dysfunction. Ventricular electromechanical models, likely the most sophisticated virtual organs to date, integrate detailed information across the spatial scales of cardiac electrophysiology and mechanics and are capable of capturing the emergent behavior and the interaction between electrical activation and mechanical contraction of the heart. The goal of this review is to provide an overview of the latest advancements in multiscale electromechanical modeling of the ventricles. We first detail the general framework of multiscale ventricular electromechanical modeling and describe the state of the art in computational techniques and experimental validation approaches. The powerful utility of ventricular electromechanical models in providing a better understanding of cardiac function is then demonstrated by reviewing the latest insights obtained by these models, focusing primarily on the mechanisms by which mechanoelectric coupling contributes to ventricular arrythmogenesis, the relationship between electrical activation and mechanical contraction in the normal heart, and the mechanisms of mechanical dyssynchrony and resynchronization in the failing heart. Computational modeling of cardiac electromechanics will continue to complement basic science research and clinical cardiology and holds promise to become an important clinical tool aiding the diagnosis and treatment of cardiac disease.

One of the most important components of mechanoelectric coupling is stretch-activated channels, sarcolemmal channels that open upon mechanical stimuli. Uncovering the mechanisms by which stretch-activated channels contribute to ventricular arrhythmogenesis under a variety of pathologic conditions is hampered by the lack of experimental methodologies that can record the 3-dimensional electromechanical activity simultaneously at high spatiotemporal resolution. Computer modeling provides such an opportunity. The goal of this review is to illustrate the utility of sophisticated, physiologically realistic, whole heart computer simulations in determining the role of mechanoelectric coupling in ventricular arrhythmogenesis. We first present the various ways by which stretch-activated channels have been modeled and demonstrate how these channels affect cardiac electrophysiologic properties. Next, we use an electrophysiologic model of the rabbit ventricles to understand how so-called commotio cordis, the mechanical impact to the precordial region of the heart, can initiate ventricular tachycardia via the recruitment of stretch-activated channels. Using the same model, we also provide mechanistic insight into the termination of arrhythmias by precordial thump under normal and globally ischemic conditions. Lastly, we use a novel anatomically realistic dynamic 3-dimensional coupled electromechanical model of the rabbit ventricles to gain insight into the role of electromechanical dysfunction in arrhythmogenesis during acute regional ischemia., (Copyright © 2010 Elsevier Inc. All rights reserved.)

Ongoing investigation of the electrophysiology and pathophysiology of the human atria requires an accurate representation of the membrane dynamics of the human atrial myocyte. However, existing models of the human atrial myocyte action potential do not accurately reproduce experimental observations with respect to the kinetics of key repolarizing currents or rate dependence of the action potential and fail to properly enforce charge conservation, an essential characteristic in any model of the cardiac membrane. In addition, recent advances in experimental methods have resulted in new data regarding the kinetics of repolarizing currents in the human atria. The goal of this study was to develop a new model of the human atrial action potential, based on the Nygren et al. model of the human atrial myocyte and newly available experimental data, that ensures an accurate representation of repolarization processes and reproduction of action potential rate dependence and enforces charge conservation. Specifically, the transient outward K(+) current (I(t)) and ultrarapid rectifier K(+) current (I(Kur)) were newly formulated. The inwardly recitifying K(+) current (I(K1)) was also reanalyzed and implemented appropriately. Simulations of the human atrial myocyte action potential with this new model demonstrated that early repolarization is dependent on the relative conductances of I(t) and I(Kur), whereas densities of both I(Kur) and I(K1) underlie later repolarization. In addition, this model reproduces experimental measurements of rate dependence of I(t), I(Kur), and action potential duration. This new model constitutes an improved representation of excitability and repolarization reserve in the human atrial myocyte and, therefore, provides a useful computational tool for future studies involving the human atrium in both health and disease.

While defibrillation is the only means for prevention of sudden cardiac death, key aspects of the process, such as the intramural virtual electrodes (VEs), remain controversial. Experimental studies had attempted to assess intramural VEs by using wedge preparations and recording activity from the cut surface; however, applicability of this approach remains unclear. These studies found, surprisingly, that for strong shocks, the entire cut surface was negatively polarized, regardless of boundary conditions. The goal of this study is to examine, by means of bidomain simulations, whether VEs on the cut surface represent a good approximation to VEs in depth of the intact wall. Furthermore, we aim to explore mechanisms that could give rise to negative polarization on the cut surface. A model of wedge preparation was used, in which fiber orientation could be changed, and where the cut surface was subjected to permeable and impermeable boundary conditions. Small-scale mechanisms for polarization were also considered. To determine whether any distortions in the recorded VEs arise from averaging during optical mapping, a model of fluorescent recording was employed. The results indicate that, when an applied field is spatially uniform and impermeable boundary conditions are enforced, regardless of the fiber orientation VEs on the cut surface faithfully represent those intramurally, provided tissue properties are not altered by dissection. Results also demonstrate that VEs are sensitive to the conductive layer thickness above the cut surface. Finally, averaging during fluorescent recordings results in large negative VEs on the cut surface, but these do not arise from small-scale heterogeneities.

Introduction: Recent experimental evidence demonstrates that a point stimulus generates a nonuniform distribution of transmembrane potential (virtual electrode pattern) consisting of large adjacent areas of depolarization and hyperpolarization. This simulation study focuses on the role of virtual electrodes in reentry induction., Methods and Results: We simulated the electrical behavior of a sheet of myocardium using a two-dimensional bidomain model with straight fibers. Membrane kinetics were represented by the Beeler-Reuter Drouhard-Roberge model. Simulations were conducted for equal and unequal anisotropy ratios. S1 wavefront was planar and propagated parallel or perpendicular to the fibers. S2 unipolar stimulus was cathodal or anodal. With regard to unequal anisotropy, for both cathodal and anodal stimuli, the S2 stimulus negatively polarizes some portion of membrane, deexciting it and opening an excitable pathway in a region of otherwise unexcitable tissue. Reentry is generated by break excitation of this tissue and subsequent propagation through deexcited and recovered areas of myocardium. Figure-of-eight and quatrefoil reentry are observed, with figure-of-eight most common. Figure-of-eight rotation is seen in the direction predicted by the critical point hypothesis. With regard to equal anisotropy, reentry was observed for cathodal stimuli only at strengths > -95 A/m., Conclusion: The key to reentry induction is the close proximity of S2-induced excited and deexcited areas, with adjacent nonexcited areas available for propagation.

This simulation study presents an inquiry into the mechanisms by which a strong electric shock halts life-threatening cardiac arrhythmias. It examines the "extension of refractoriness" hypothesis for defibrillation which postulates that the shock induces an extension of the refractory period of cardiac cells thus blocking propagating waves of arrhythmia and fibrillation. The present study uses a model of the defibrillation process that represents a sheet of myocardium as a biodomain with unequal anisotropy ratios. The tissue consists of curved fibers in which spiral wave reentry is initiated. The defibrillation shock is delivered via two line electrodes that occupy opposite tissue boundaries. Simulation results demonstrate that a large-scale region of depolarization is induced throughout most of the tissue. This depolarization extends the refractoriness of the cells in the region. In addition, new wavefronts are generated from the regions of induced hyperpolarization that further restrict the spiral wave pathway and cause its termination.

Optimizing lead placement in transvenous defibrillation remains central to the clinical aspects of the defibrillation procedure. Studies involving superior vena cava (SVC) return electrodes have found that left ventricular (LV) leads or septal positioning of the right ventricular (RV) lead minimizes the voltage defibrillation threshold (VDFT) in endocardial lead-->SVC defibrillation systems. However, similar studies have not been conducted for active-can configurations. The goal of this study was to determine the optimal lead position to minimize the VDFT for systems incorporating an active can. This study used a high resolution finite element model of a human torso that includes the fiber architecture of the ventricular myocardium to find the role of lead positioning in a transvenous LEAD-->can defibrillation electrode system. It was found that, among single lead systems, posterior positioning of leads in the right ventricle lowers VDFTs appreciably. Furthermore, a septal location of leads resulted in lower VDFTs than free-wall positioning. Increasing the number of leads, and thus the effective lead surface area in the right ventricle also resulted in lower VDFTs. However, the lead configuration that resulted in the lowest VDFTs is a combination of mid-cavity right ventricle lead and a mid-cavity left ventricle lead. The addition of a left ventricular lead resulted in a reduction in the size of the low gradient regions and a change of its location from the left ventricular free wall to the septal wall.