Computational Representations of Myocardial Infarct Scars and Implications for Arrhythmogenesis

A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data

Computational models of cardiac electrophysiology have gradually matured during the past few decades and are now being personalised to provide patient-specific therapy guidance for improving suboptimal treatment outcomes. The predictive features of these personalised electrophysiology models hold the promise of providing optimal treatment planning, which is currently limited in the clinic owing to reliance on a population-based or average patient approach. The generation of a personalised electrophysiology model entails a sequence of steps for which a range of activation mapping, calibration methods and therapy simulation pipelines have been suggested. However, the optimal methods that can potentially constitute a clinically relevant in silico treatment are still being investigated and face limitations, such as uncertainty of electroanatomical data recordings, generation and calibration of models within clinical timelines and requirements to validate or benchmark the recovered tissue parameters. This paper is aimed at reporting techniques on the personalisation of cardiac computational models, with a focus on calibrating cardiac tissue conductivity based on electroanatomical mapping data.

Current progress toward isogeometric modeling of the heart biophysics

In this paper, we review a powerful methodology to solve complex numerical simulations, known as isogeometric analysis, with a focus on applications to the biophysical modeling of the heart. We focus on the hemodynamics, modeling of the valves, cardiac tissue mechanics, and on the simulation of medical devices and treatments. For every topic, we provide an overview of the methods employed to solve the specific numerical issue entailed by the simulation. We try to cover the complete process, starting from the creation of the geometrical model up to the analysis and post-processing, highlighting the advantages and disadvantages of the methodology.

Combination of personalized computational modeling and machine learning for optimization of left ventricular pacing site in cardiac resynchronization therapy

Introduction: The 30-50% non-response rate to cardiac resynchronization therapy (CRT) calls for improved patient selection and optimized pacing lead placement. The study aimed to develop a novel technique using patient-specific cardiac models and machine learning (ML) to predict an optimal left ventricular (LV) pacing site (ML-PS) that maximizes the likelihood of LV ejection fraction (LVEF) improvement in a given CRT candidate. To validate the approach, we evaluated whether the distance D_PS between the clinical LV pacing site (ref-PS) and ML-PS is associated with improved response rate and magnitude. Materials and methods: We reviewed retrospective data for 57 CRT recipients. A positive response was defined as a more than 10% LVEF improvement. Personalized models of ventricular activation and ECG were created from MRI and CT images. The characteristics of ventricular activation during intrinsic rhythm and biventricular (BiV) pacing with ref-PS were derived from the models and used in combination with clinical data to train supervised ML classifiers. The best logistic regression model classified CRT responders with a high accuracy of 0.77 (ROC AUC = 0.84). The LR classifier, model simulations and Bayesian optimization with Gaussian process regression were combined to identify an optimal ML-PS that maximizes the ML-score of CRT response over the LV surface in each patient. Results: The optimal ML-PS improved the ML-score by 17 ± 14% over the ref-PS. Twenty percent of the non-responders were reclassified as positive at ML-PS. Selection of positive patients with a max ML-score >0.5 demonstrated an improved clinical response rate. The distance D_PS was shorter in the responders. The max ML-score and D_PS were found to be strong predictors of CRT response (ROC AUC = 0.85). In the group with max ML-score > 0.5 and D_PS< 30 mm, the response rate was 83% compared to 14% in the rest of the cohort. LVEF improvement in this group was higher than in the other patients (16 ± 8% vs. 7 ± 8%). Conclusion: A new technique combining clinical data, personalized heart modelling and supervised ML demonstrates the potential for use in clinical practice to assist in optimizing patient selection and predicting optimal LV pacing lead position in HF candidates for CRT.

Graft-host coupling changes can lead to engraftment arrhythmia: a computational study

After myocardial infarction (MI), a significant portion of heart muscle is replaced with scar tissue, progressively leading to heart failure. Human pluripotent stem cell-derived cardiomyocytes (hPSC-CM) offer a promising option for improving cardiac function after MI. However, hPSC-CM transplantation can lead to engraftment arrhythmia (EA). EA is a transient phenomenon arising shortly after transplantation then spontaneously resolving after a few weeks. The underlying mechanism of EA is unknown. We hypothesize that EA may be explained partially by time-varying, spatially heterogeneous, graft-host electrical coupling. Here, we created computational slice models derived from histological images that reflect different configuration of grafts in the infarcted ventricle. We ran simulations with varying degrees of connection imposed upon the graft-host perimeter to assess how heterogeneous electrical coupling affected EA with non-conductive scar, slow-conducting scar and scar replaced by host myocardium. We also quantified the effect of variation in intrinsic graft conductivity. Susceptibility to EA initially increased and subsequently decreased with increasing graft-host coupling, suggesting the waxing and waning of EA is regulated by progressive increases in graft-host coupling. Different spatial distributions of graft, host and scar yielded markedly different susceptibility curves. Computationally replacing non-conductive scar with host myocardium or slow-conducting scar, and increasing intrinsic graft conductivity both demonstrated potential means to blunt EA vulnerability. These data show how graft location, especially relative to scar, along with its dynamic electrical coupling to host, can influence EA burden; moreover, they offer a rational base for further studies aimed to define the optimal delivery of hPSC-CM injection. KEY POINTS: Human pluripotent stem cell-derived cardiomyocytes (hPSC-CM) hold great cardiac regenerative potential but can also cause engraftment arrhythmias (EA). Spatiotemporal evolution in the pattern of electrical coupling between injected hPSC-CMs and surrounding host myocardium may explain the dynamics of EA observed in large animal models. We conducted simulations in histology-derived 2D slice computational models to assess the effects of heterogeneous graft-host electrical coupling on EA propensity, with or without scar tissue. Our findings suggest spatiotemporally heterogeneous graft-host coupling can create an electrophysiological milieu that favours graft-initiated host excitation, a surrogate metric of EA susceptibility. Removing scar from our models reduced but did not abolish the propensity for this phenomenon. Conversely, reduced intra-graft electrical connectedness increased the incidence of graft-initiated host excitation. The computational framework created for this study can be used to generate new hypotheses, targeted delivery of hPSC-CMs.

Mechanisms of ventricular arrhythmias elicited by coexistence of multiple electrophysiological remodeling in ischemia: A simulation study

Myocardial ischemia, injury and infarction (MI) are the three stages of acute coronary syndrome (ACS). In the past two decades, a great number of studies focused on myocardial ischemia and MI individually, and showed that the occurrence of reentrant arrhythmias is often associated with myocardial ischemia or MI. However, arrhythmogenic mechanisms in the tissue with various degrees of remodeling in the ischemic heart have not been fully understood. In this study, biophysical detailed single-cell models of ischemia 1a, 1b, and MI were developed to mimic the electrophysiological remodeling at different stages of ACS. 2D tissue models with different distributions of ischemia and MI areas were constructed to investigate the mechanisms of the initiation of reentrant waves during the progression of ischemia. Simulation results in 2D tissues showed that the vulnerable windows (VWs) in simultaneous presence of multiple ischemic conditions were associated with the dynamics of wave propagation in the tissues with each single pathological condition. In the tissue with multiple pathological conditions, reentrant waves were mainly induced by two different mechanisms: one is the heterogeneity along the excitation wavefront, especially the abrupt variation in conduction velocity (CV) across the border of ischemia 1b and MI, and the other is the decreased safe factor (SF) for conduction at the edge of the tissue in MI region which is attributed to the increased excitation threshold of MI region. Finally, the reentrant wave was observed in a 3D model with a scar reconstructed from MRI images of a MI patient. These comprehensive findings provide novel insights for understanding the arrhythmic risk during the progression of myocardial ischemia and highlight the importance of the multiple pathological stages in designing medical therapies for arrhythmias in ischemia.

Role of Scar and Border Zone Geometry on the Genesis and Maintenance of Re-Entrant Ventricular Tachycardia in Patients With Previous Myocardial Infarction

In patients with healed myocardial infarction, the left ventricular ejection fraction is characterized by low sensitivity and specificity in the prediction of future malignant arrhythmias. Thus, there is the need for new parameters in daily practice to perform arrhythmic risk stratification. The aim of this study is to identify some features of proarrhythmic geometric configurations of scars and border zones (BZ), by means of numerical simulations based on left ventricular models derived from post myocardial infarction patients. Two patients with similar clinical characteristics were included in this study. Both patients exhibited left ventricular scars characterized by subendo- and subepicardial BZ and a transmural BZ isthmus. The scar of patient #1 was significantly larger than that of patient #2, whereas the transmural BZ isthmus and the subdendo- and subepicardial BZs of patient #2 were thicker than those of patient #1. Patient #1 was positive at electrophysiologic testing, whereas patient #2 was negative. Based on the cardiac magnetic resonance (CMR) data, we developed a geometric model of the left ventricles of the two patients, taking into account the position, extent, and topological features of scars and BZ. The numerical simulations were based on the anisotropic monodomain model of electrocardiology. In the model of patient #1, sustained ventricular tachycardia (VT) was inducible by an S2 stimulus delivered at any of the six stimulation sites considered, while in the model of patient #2 we were not able to induce sustained VT. In the model of patient #1, making the subendo- and subepicardial BZs as thick as those of patient #2 did not affect the inducibility and maintenance of VT. On the other hand, in the model of patient #2, making the subendo- and subepicardial BZs as thin as those of patient #1 yielded sustained VT. In conclusion, the results show that the numerical simulations have an effective predictive capability in discriminating patients at high arrhythmic risk. The extent of the infarct scar and the presence of transmural BZ isthmuses and thin subendo- and subepicardial BZs promote sustained VT.

An in-silico assessment of efficacy of two novel intra-cardiac electrode configurations versus traditional anti-tachycardia pacing therapy for terminating sustained ventricular tachycardia

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.

Cardiac Mechano-Electric Coupling: Acute Effects of Mechanical Stimulation on Heart Rate and Rhythm

The heart is vital for biological function in almost all chordates, including humans. It beats continually throughout our life, supplying the body with oxygen and nutrients while removing waste products. If it stops, so does life. The heartbeat involves precise coordination of the activity of billions of individual cells, as well as their swift and well-coordinated adaption to changes in physiological demand. Much of the vital control of cardiac function occurs at the level of individual cardiac muscle cells, including acute beat-by-beat feedback from the local mechanical environment to electrical activity (as opposed to longer term changes in gene expression and functional or structural remodeling). This process is known as mechano-electric coupling (MEC). In the current review, we present evidence for, and implications of, MEC in health and disease in human; summarize our understanding of MEC effects gained from whole animal, organ, tissue, and cell studies; identify potential molecular mediators of MEC responses; and demonstrate the power of computational modeling in developing a more comprehensive understanding of ‟what makes the heart tick.ˮ.

Influence of the distribution of fibrosis within an area of myocardial infarction on wave propagation in ventricular tissue

The presence of fibrosis in heart tissue is strongly correlated with an incidence of arrhythmia, which is a leading cause of sudden cardiac death (SCD). However, it remains incompletely understood how different distributions, sizes and positions of fibrotic tissues contribute to arrhythmogenesis. In this study, we designed 4 different ventricular models mimicking wave propagation in cardiac tissues under normal, myocardial infarction (MI), MI with random fibrosis and MI with gradient fibrosis conditions. Simulation results of ideal square tissues indicate that vulnerable windows (VWs) of random and gradient fibrosis distributions are similar with low levels of fibrosis. However, with a high level of fibrosis, the VWs significantly increase in random fibrosis tissue but not in gradient fibrosis tissue. In addition, we systematically analyzed the effects of the size and position of fibrosis tissues on VWs. Simulation results show that it is more likely for a reentry wave to appear when the length of the infarcted area is greater than 25% of the perimeter of the ventricle, when the width is approximately half that of the ventricular wall, or when the infarcted area is attached to the inside or outside of the ventricular wall.

Role of 3-Dimensional Architecture of Scar and Surviving Tissue in Ventricular Tachycardia: Insights From High-Resolution Ex Vivo Porcine Models

BACKGROUND

An improved knowledge of the spatial organization of infarct structure and its contribution to ventricular tachycardia (VT) is important for designing optimal treatments. This study explores the relationship between the 3-dimensional structure of the healed infarct and the VT reentrant pathways in high-resolution models of infarcted porcine hearts.

METHODS

Structurally detailed models of infarcted ventricles were reconstructed from ex vivo late gadolinium enhancement and diffusion tensor magnetic resonance imaging data of 8 chronically infarcted porcine hearts at submillimeter resolution (0.25×0.25×0.5 mm³). To characterize the 3-dimensional structure of surviving tissue in the zone of infarct, a novel scar-mapped thickness metric was introduced. Further, using the ventricular models, electrophysiological simulations were conducted to determine and analyze the 3-dimensional VT pathways that were established in each of the complex infarct morphologies.

RESULTS

The scar-mapped thickness metric revealed the heterogeneous organization of infarct and enabled us to systematically characterize the distribution of surviving tissue thickness in 8 hearts. Simulation results demonstrated the involvement of a subendocardial tissue layer of varying thickness in the majority of VT pathways. Importantly, they revealed that VT pathways are most frequently established within thin surviving tissue structures of thickness ≤2.2 mm (90th percentile) surrounding the scar.

CONCLUSIONS

The combination of high-resolution imaging data and ventricular simulations revealed the 3-dimensional distribution of surviving tissue surrounding the scar and demonstrated its involvement in VT pathways. The new knowledge obtained in this study contributes toward a better understanding of infarct-related VT.

Personalized Cardiac Computational Models: From Clinical Data to Simulation of Infarct-Related Ventricular Tachycardia

In the chronic stage of myocardial infarction, a significant number of patients develop life-threatening ventricular tachycardias (VT) due to the arrhythmogenic nature of the remodeled myocardium. Radiofrequency ablation (RFA) is a common procedure to isolate reentry pathways across the infarct scar that are responsible for VT. Unfortunately, this strategy show relatively low success rates; up to 50% of patients experience recurrent VT after the procedure. In the last decade, intensive research in the field of computational cardiac electrophysiology (EP) has demonstrated the ability of three-dimensional (3D) cardiac computational models to perform in-silico EP studies. However, the personalization and modeling of certain key components remain challenging, particularly in the case of the infarct border zone (BZ). In this study, we used a clinical dataset from a patient with a history of infarct-related VT to build an image-based 3D ventricular model aimed at computational simulation of cardiac EP, including detailed patient-specific cardiac anatomy and infarct scar geometry. We modeled the BZ in eight different ways by combining the presence or absence of electrical remodeling with four different levels of image-based patchy fibrosis (0, 10, 20, and 30%). A 3D torso model was also constructed to compute the ECG. Patient-specific sinus activation patterns were simulated and validated against the patient's ECG. Subsequently, the pacing protocol used to induce reentrant VTs in the EP laboratory was reproduced in-silico. The clinical VT was induced with different versions of the model and from different pacing points, thus identifying the slow conducting channel responsible for such VT. Finally, the real patient's ECG recorded during VT episodes was used to validate our simulation results and to assess different strategies to model the BZ. Our study showed that reduced conduction velocities and heterogeneity in action potential duration in the BZ are the main factors in promoting reentrant activity. Either electrical remodeling or fibrosis in a degree of at least 30% in the BZ were required to initiate VT. Moreover, this proof-of-concept study confirms the feasibility of developing 3D computational models for cardiac EP able to reproduce cardiac activation in sinus rhythm and during VT, using exclusively non-invasive clinical data.

A Multi-Domain Continuum Model of Electrical Stimulation of Healthy and Degenerate Retina

A continuum multi-domain model of electrical stimulation of the retina is presented and validated against retinal ganglion cell (RGC) excitation thresholds reported in a recently published in vitro experimental study. We applied our model to investigate the response of the RGC layer to electrical stimulation during mid-to-late stage retinal degeneration for both epiretinal and suprachoroidal configurations. Interestingly, our model predicted that suprachoroidal stimulation of the degenerate retina required increased current thresholds, mainly because of the presence of the glial scar layer. In contrast, epiretinal stimulation thresholds were almost similar for both healthy and degenerate models. The latter finding implies that there is no influence of the glial scar layer on epiretinal stimulation current thresholds.

Modeling the Electrophysiological Properties of the Infarct Border Zone

Ventricular arrhythmias (VA) in patients with myocardial infarction (MI) are thought to be associated with structural and electrophysiological remodeling within the infarct border zone (BZ). Personalized computational models have been used to investigate the potential role of the infarct BZ in arrhythmogenesis, which still remains incompletely understood. Most recent models have relied on experimental data to assign BZ properties. However, experimental measurements vary significantly resulting in different computational representations of this region. Here, we review experimental data available in the literature to determine the most prominent properties of the infarct BZ. Computational models are then used to investigate the effect of different representations of the BZ on activation and repolarization properties, which may be associated with VA. Experimental data obtained from several animal species and patients with infarct show that BZ properties vary significantly depending on disease's stage, with the early disease stage dominated by ionic remodeling and the chronic stage by structural remodeling. In addition, our simulations show that ionic remodeling in the BZ leads to large repolarization gradients in the vicinity of the scar, which may have a significant impact on arrhythmia simulations, while structural remodeling plays a secondary role. We conclude that it is imperative to faithfully represent the properties of regions of infarction within computational models specific to the disease stage under investigation in order to conduct in silico mechanistic investigations.

Calcium Dynamics and Cardiac Arrhythmia

This Special Collection will gather all studies highlighting recent advances in theoretical and experimental studies of arrhythmia, with a specific focus on research seeking to elucidate links between calcium homeostasis in cardiac cells and organ-scale disruption of heart rhythm.

Electrophysiological alterations in a murine model of chronic coxsackievirus B3 myocarditis

INTRODUCTION

Coxsackievirus B3 (CVB3) is known to induce acute and chronic myocarditis. Most infections are clinically unapparent but some patients suffer from ventricular arrhythmias (VA) and sudden cardiac death (SCD). Studies showed that acute CVB3 infection may cause impaired function of cardiac ion channels, creating a proarrhythmic substrate. However, it is unknown whether low level CVB3+ expression in myocytes may cause altered cardiac electrophysiology leading to VA.

METHODS

Cellular electrophysiology was used to analyze cellular action potentials (APs) and occurrence of afterdepolarizations from isolated cardiomyocytes of wildtype (WT) and transgenic CVB3ΔVP0 (CVB3+) mice. Further, we studied surface ECGs, monophasic APs, ventricular effective refractory period (VERP) and inducibility of VAs in Langendorff-perfused whole hearts. All used cardiomyocytes and whole hearts originated from male mice.

RESULTS

Cellular action potential duration (APD) in WT and CVB3+ myocytes was unchanged. No difference in mean occurrence or amplitude of afterdepolarizations in WT and CVB3+ myocytes was found. Interestingly, resting membrane potential in CVB3+ myocytes was significantly hyperpolarized (WT: -90.0±2.2 mV, n = 7; CVB3+: -114.1±3.0 mV, n = 14; p<0.005). Consistently, in Langendorff-perfused hearts, APDs were also not different between WT and CVB3+ whole hearts. Within both groups, we found a heart rate dependent shortening of ADP90 with increasing heart rate in Langendorff-perfused hearts. VERP was significantly prolonged in CVB3+ hearts compared to WT (WT: 36.0±2.7 ms, n = 5; CVB3+: 47.0±2.0 ms, n = 7; p = 0.018). Resting heart rate (HR) in Langendorff-perfused hearts was not significantly different between both genotypes. Electrical pacing protocols induced no VA in WT and CVB3+ hearts.

CONCLUSION

In CVB3+ mice, prolonged ventricular refractoriness and hyperpolarized resting membrane potentials in presence of unchanged APD were observed, suggesting that low level CVB3 expression does not promote VA by altered cardiac electrophysiology in this type of chronic myocarditis. These findings may suggest that other mechanisms such as chronic myocardial inflammation or fibrosis may account for arrhythmias observed in patients with chronic enteroviral myocarditis.