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

Computational Medicine: What Electrophysiologists Should Know to Stay Ahead of the Curve

PURPOSE OF REVIEW

Technology drives the field of cardiac electrophysiology. Recent computational advances will bring exciting changes. To stay ahead of the curve, we recommend electrophysiologists develop a robust appreciation for novel computational techniques, including deterministic, statistical, and hybrid models.

RECENT FINDINGS

In clinical applications, deterministic models use biophysically detailed simulations to offer patient-specific insights. Statistical techniques like machine learning and artificial intelligence recognize patterns in data. Emerging clinical tools are exploring avenues to combine all the above methodologies. We review three ways that computational medicine will aid electrophysiologists by: (1) improving personalized risk assessments, (2) weighing treatment options, and (3) guiding ablation procedures. Leveraging clinical data that are often readily available, computational models will offer valuable insights to improve arrhythmia patient care. As emerging tools promote personalized medicine, physicians must continue to critically evaluate technology-driven tools they consider using to ensure their appropriate implementation.

Understanding the Utility of Endocardial Electrocardiographic Imaging in Epi-Endocardial Mapping of 3D Reentrant Circuits

Background

Studies of VT mechanisms are largely based on a 2D portrait of reentrant circuits on one surface of the heart. This oversimplifies the 3D circuit that involves the depth of the myocardium. Simultaneous epicardial and endocardial (epi-endo) mapping was shown to facilitate a 3D delineation of VT circuits, which is however difficult via invasive mapping.

Objective

This study investigates the capability of noninvasive epicardial-endocardial electrocardiographic imaging (ECGI) to elucidate the 3D construct of VT circuits, emphasizing the differentiation of epicardial, endocardial, and intramural circuits and to determine the proximity of mid-wall exits to the epicardial or endocardial surfaces.

Methods

120-lead ECGs of VT in combination with subject-specific heart-torso geometry are used to compute unipolar electrograms (CEGM) on ventricular epicardium and endocardia. Activation isochrones are constructed, and the percentage of activation within VT cycle length is calculated on each surface. This classifies VT circuits into 2D (surface only), uniform transmural, nonuniform transmural, and mid-myocardial (focal on surfaces). Furthermore, the endocardial breakthrough time was accurately measured using Laplacian eigenmaps, and by correlating the delay time of the epi-endo breakthroughs, the relative distance of a mid-wall exit to the epicardium or the endocardium surfaces was identified.

Results

We analyzed 23 simulated and in-vivo VT circuits on post-infarction porcine hearts. In simulated circuits, ECGI classified 21% as 2D and 78% as 3D: 82.6% of these were correctly classified. The relative timing between epicardial and endocardial breakthroughs was correctly captured across all cases. In in-vivo circuits, ECGI classified 25% as 2D and 75% as 3D: in all cases, circuit exits and entrances were consistent with potential critical isthmus delineated from combined LGE-MRI and catheter mapping data.

Conclusions

ECGI epi-endo mapping has the potential for fast delineation of 3D VT circuits, which may augment detailed catheter mapping for VT ablation.

Predicting postinfarct ventricular tachycardia by integrating cardiac MRI and advanced computational reentrant pathway analysis

BACKGROUND

Implantable cardiac defibrillator (ICD) implantation can protect against sudden cardiac death after myocardial infarction. However, improved risk stratification for device requirement is still needed.

OBJECTIVE

The purpose of this study was to improve assessment of postinfarct ventricular electropathology and prediction of appropriate ICD therapy by combining late gadolinium enhancement (LGE) and advanced computational modeling.

METHODS

ADAS 3D LV (ADAS LV Medical, Barcelona, Spain) and custom-made software were used to generate 3-dimensional patient-specific ventricular models in a prospective cohort of patients with a myocardial infarction (N = 40) having undergone LGE imaging before ICD implantation. Corridor metrics and 3-dimensional surface features were computed from LGE images. The Virtual Induction and Treatment of Arrhythmias (VITA) framework was applied to patient-specific models to comprehensively probe the vulnerability of the scar substrate to sustaining reentrant circuits. Imaging and VITA metrics, related to the numbers of induced ventricular tachycardias and their corresponding round trip times (RTTs), were compared with ICD therapy during follow-up.

RESULTS

Patients with an event (n = 17) had a larger interface between healthy myocardium and scar and higher VITA metrics. Cox regression analysis demonstrated a significant independent association with an event: interface (hazard ratio [HR] 2.79; 95% confidence interval [CI] 1.44-5.44; P < .01), unique ventricular tachycardias (HR 1.67; 95% CI 1.04-2.68; P = .03), mean RTT (HR 2.14; 95% CI 1.11-4.12; P = .02), and maximum RTT (HR 2.13; 95% CI 1.19-3.81; P = .01).

CONCLUSION

A detailed quantitative analysis of LGE-based scar maps, combined with advanced computational modeling, can accurately predict ICD therapy and could facilitate the early identification of high-risk patients in addition to left ventricular ejection fraction.

Optimizing ventricular tachycardia ablation through imaging-based assessment of arrhythmic substrate: A comprehensive review and roadmap for the future

Ventricular tachycardia (VT) is a life-threatening heart rhythm and has long posed a complex challenge in the field of cardiology. Recent developments in advanced imaging modalities have aimed to improve comprehension of underlying arrhythmic substrate for VT. To this extent, high-resolution cardiac magnetic resonance (CMR) and cardiac computed tomography (CCT) have emerged as tools for accurately visualizing and characterizing scar tissue, fibrosis, and other critical structural abnormalities within the heart, providing novel insights into VT triggers and substrate. However, clinical implementation of knowledge derived from these advanced imaging techniques in improving VT treatment and guiding invasive therapeutic strategies continues to pose significant challenges. A pivotal concern lies in the absence of standardized imaging protocols and analysis methodologies, resulting in a large variance in data quality and consistency. Furthermore, the clinical significance and outcomes associated with VT substrate characterization through CMR and CCT remain dynamic and subject to ongoing evolution. This highlights the need for refinement of these techniques before their reliable integration into routine patient care can be realized. The primary objectives of this study are twofold: firstly, to provide a comprehensive overview of the studies conducted over the last 15 years, summarizing the current available literature on imaging-based assessment of VT substrate. Secondly, to critically analyze and evaluate the selected studies, with the aim of providing valuable insights that can inform current clinical practice and future research.

Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales, makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias, from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed, and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook toward potential future advances, including the combination of mechanistic modeling and machine learning/artificial intelligence, is provided. As the field of cardiology is embarking on a journey toward precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

Re-entry in models of cardiac ventricular tissue with scar represented as a Gaussian random field

Introduction: Fibrotic scar in the heart is known to act as a substrate for arrhythmias. Regions of fibrotic scar are associated with slowed or blocked conduction of the action potential, but the detailed mechanisms of arrhythmia formation are not well characterised and this can limit the effective diagnosis and treatment of scar in patients. The aim of this computational study was to evaluate different representations of fibrotic scar in models of 2D 10 × 10 cm ventricular tissue, where the region of scar was defined by sampling a Gaussian random field with an adjustable length scale of between 1.25 and 10.0 mm. Methods: Cellular electrophysiology was represented by the Ten Tusscher 2006 model for human ventricular cells. Fibrotic scar was represented as a spatially varying diffusion, with different models of the boundary between normal and fibrotic tissue. Dispersion of activation time and action potential duration (APD) dispersion was assessed in each sample by pacing at an S1 cycle length of 400 ms followed by a premature S2 beat with a coupling interval of 323 ms. Vulnerability to reentry was assessed with an aggressive pacing protocol. In all models, simulated fibrosis acted to delay activation, to increase the dispersion of APD, and to generate re-entry. Results: A higher incidence of re-entry was observed in models with simulated fibrotic scar at shorter length scale, but the type of model used to represent fibrotic scar had a much bigger influence on the incidence of reentry. Discussion: This study shows that in computational models of fibrotic scar the effects that lead to either block or propagation of the action potential are strongly influenced by the way that fibrotic scar is represented in the model, and so the results of computational studies involving fibrotic scar should be interpreted carefully.

Signal-averaged electrocardiography as a noninvasive tool for evaluating the ventricular substrate in patients with nonischemic cardiomyopathy: reassessment of an old tool

Introduction

Signal-averaged electrocardiography (SAECG) provides diagnostic and prognostic information regarding cardiac diseases. However, its value in other nonischemic cardiomyopathies (NICMs) remains unclear. This study aimed to investigate the role of SAECG in patients with NICM.

Methods and results

This retrospective study included consecutive patients with NICM who underwent SAECG, biventricular substrate mapping, and ablation for ventricular arrhythmia (VA). Patients with baseline ventricular conduction disturbances were excluded. Patients who fulfilled at least one SAECG criterion were categorized into Group 1, and the other patients were categorized into Group 2. Baseline and ventricular substrate characteristics were compared between the two groups. The study included 58 patients (39 men, mean age 50.4 ± 15.5 years), with 34 and 24 patients in Groups 1 and 2, respectively. Epicardial mapping was performed in eight (23.5%) and six patients (25.0%) in Groups 1 and 2 (p = 0.897), respectively. Patients in Group 1 had a more extensive right ventricular (RV) low-voltage zone (LVZ) and scar area than those in Group 2. Group 1 had a larger epicardial LVZ than Group 2. Epicardial late potentials were more frequent in Group 1 than in Group 2. There were more arrhythmogenic foci within the RV outflow tract in Group 1 than in Group 2. There was no significant difference in long-term VA recurrence.

Conclusion

In our NICM population, a positive SAECG was associated with a larger RV endocardial scar, epicardial scar/late potentials, and a higher incidence of arrhythmogenic foci in the RV outflow tract.

A Semi-automatic Pipeline for Generation of Large Cohorts of Four-Chamber Heart Meshes

Computational models for cardiac electro-mechanics have been increasingly used to further understand heart function. Small cohort and single patient computational studies provide useful insight into cardiac pathophysiology and response to therapy. However, these smaller studies have limited capability to capture the high level of anatomical variability seen in cardiology patients. Larger cohort studies are, on the other hand, more representative of the study population, but building several patient-specific anatomical meshes can be time-consuming and requires access to larger datasets of imaging data, image processing software to label anatomical structures and tools to create high fidelity anatomical meshes. Limited access to these tools and data might limit advances in this area of research. In this chapter, we present our semi-automatic pipeline to build patient-specific four-chamber heart meshes from CT imaging datasets, including ventricular myofibers and a set of universal ventricular and atrial coordinates. This pipeline was applied to CT images from both heart failure patients and healthy controls to generate cohorts of tetrahedral meshes suitable for electro-mechanics simulations. Both cohorts were made publicly available in order to promote computational studies employing large virtual cohorts.

Heterogeneity of Repolarization and Cell-Cell Variability of Cardiomyocyte Remodeling Within the Myocardial Infarction Border Zone Contribute to Arrhythmia Susceptibility

BACKGROUND

After myocardial infarction, the infarct border zone (BZ) is the dominant source of life-threatening arrhythmias, where fibrosis and abnormal repolarization create a substrate for reentry. We examined whether repolarization abnormalities are heterogeneous within the BZ in vivo and could be related to heterogeneous cardiomyocyte remodeling.

METHODS

Myocardial infarction was induced in domestic pigs by 120-minute ischemia followed by reperfusion. After 1 month, remodeling was assessed by magnetic resonance imaging, and electroanatomical mapping was performed to determine the spatial distribution of activation-recovery intervals. Cardiomyocytes were isolated and tissue samples collected from the BZ and remote regions. Optical recording allowed assessment of action potential duration (di-8-ANEPPS, stimulation at 1 Hz, 37 °C) of large cardiomyocyte populations while gene expression in cardiomyocytes was determined by single nuclear RNA sequencing.

RESULTS

In vivo, activation-recovery intervals in the BZ tended to be longer than in remote with increased spatial heterogeneity evidenced by a greater local SD (3.5±1.3 ms versus remote: 2.0±0.5 ms, P=0.036, npigs=5). Increased activation-recovery interval heterogeneity correlated with enhanced arrhythmia susceptibility. Cellular population studies (ncells=635-862 cells per region) demonstrated greater heterogeneity of action potential duration in the BZ (SD, 105.9±17.0 ms versus remote: 73.9±8.6 ms; P=0.001; npigs=6), which correlated with heterogeneity of activation-recovery interval in vivo. Cell-cell gene expression heterogeneity in the BZ was evidenced by increased Euclidean distances between nuclei of the BZ (12.1 [9.2-15.0] versus 10.6 [7.5-11.6] in remote; P<0.0001). Differentially expressed genes characterizing BZ cardiomyocyte remodeling included hypertrophy-related and ion channel-related genes with high cell-cell variability of expression. These gene expression changes were driven by stress-responsive TFs (transcription factors). In addition, heterogeneity of left ventricular wall thickness was greater in the BZ than in remote.

CONCLUSIONS

Heterogeneous cardiomyocyte remodeling in the BZ is driven by uniquely altered gene expression, related to heterogeneity in the local microenvironment, and translates to heterogeneous repolarization and arrhythmia vulnerability in vivo.

Artificial Intelligence as a Diagnostic Tool in Non-Invasive Imaging in the Assessment of Coronary Artery Disease

Coronary artery disease (CAD) remains a leading cause of mortality and morbidity worldwide, and it is associated with considerable economic burden. In an ageing, multimorbid population, it has become increasingly important to develop reliable, consistent, low-risk, non-invasive means of diagnosing CAD. The evolution of multiple cardiac modalities in this field has addressed this dilemma to a large extent, not only in providing information regarding anatomical disease, as is the case with coronary computed tomography angiography (CCTA), but also in contributing critical details about functional assessment, for instance, using stress cardiac magnetic resonance (S-CMR). The field of artificial intelligence (AI) is developing at an astounding pace, especially in healthcare. In healthcare, key milestones have been achieved using AI and machine learning (ML) in various clinical settings, from smartwatches detecting arrhythmias to retinal image analysis and skin cancer prediction. In recent times, we have seen an emerging interest in developing AI-based technology in the field of cardiovascular imaging, as it is felt that ML methods have potential to overcome some limitations of current risk models by applying computer algorithms to large databases with multidimensional variables, thus enabling the inclusion of complex relationships to predict outcomes. In this paper, we review the current literature on the various applications of AI in the assessment of CAD, with a focus on multimodality imaging, followed by a discussion on future perspectives and critical challenges that this field is likely to encounter as it continues to evolve in cardiology.

Intracardiac Electrogram Targets for Ventricular Tachycardia Ablation

The pathogenesis of ventricular tachycardia (VT) in most patients with a prior myocardial scarring is reentry involving compartmentalized muscle fibers protected within the scar. Often the 12-lead ECG morphology of the VT itself is not available when treated with a defibrillator. Consequently, VT ablation takes on an interesting challenge of finding critical targets in sinus rhythm. High-density recordings are essential to evaluate a substrate based on whole electrogram voltage and activation delay, supplemented with substrate perturbation through alternate site pacing or introducing an extra stimulation. In this article, we discuss contemporary intracardiac electrogram targets for VT ablation, with explanation on each of their specific fundamental physiology.

[Simulators and simulator training in interventional electrophysiology]

Simulators and simulator training are commonly used in many areas of industry and medicine. Simulators offer excellent training modalities for interventional cardiology to practice certain procedures and the handling of associated complications. In the field of electrophysiology, there are currently initial approaches to using simulators specifically for training purposes. A realistic simulator system does not yet exist in electrophysiology.

An automated near-real time computational method for induction and treatment of scar-related ventricular tachycardias

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.

Assessment of arrhythmia mechanism and burden of the infarcted ventricles following remuscularization with pluripotent stem cell-derived cardiomyocyte patches using patient-derived models

AIMS

Direct remuscularization with pluripotent stem cell-derived cardiomyocytes (PSC-CMs) seeks to address the onset of heart failure post-myocardial infarction (MI) by treating the persistent muscle deficiency that underlies it. However, direct remuscularization with PSC-CMs could potentially be arrhythmogenic. We investigated two possible mechanisms of arrhythmogenesis-focal vs. re-entrant-arising from direct remuscularization with PSC-CM patches in two personalized, human ventricular computer models of post-MI. Moreover, we developed a principled approach for evaluating arrhythmogenicity of direct remuscularization that factors in the VT propensity of the patient-specific post-MI fibrotic substrate and use it to investigate different conditions of patch remuscularization.

METHODS AND RESULTS

Two personalized, human ventricular models of post-MI (P1 and P2) were constructed from late gadolinium enhanced (LGE)-magnetic resonance images (MRIs). In each model, remuscularization with PSC-CM patches was simulated under different treatment conditions that included patch engraftment, patch myofibril orientation, remuscularization site, patch size (thickness and diameter), and patch maturation. To determine arrhythmogenicity of treatment conditions, VT burden of heart models was quantified prior to and after simulated remuscularization and compared. VT burden was quantified based on inducibility (i.e. weighted sum of pacing sites that induced) and severity (i.e. the number of distinct VT morphologies induced). Prior to remuscularization, VT burden was significant in P1 (0.275) and not in P2 (0.0, not VT inducible). We highlight that re-entrant VT mechanisms would dominate over focal mechanisms; spontaneous beats emerging from PSC-CM grafts were always a fraction of resting sinus rate. Moreover, incomplete patch engraftment can be particularly arrhythmogenic, giving rise to particularly aberrant electrical activation and conduction slowing across the PSC-CM patches along with elevated VT burden when compared with complete engraftment. Under conditions of complete patch engraftment, remuscularization was almost always arrhythmogenic in P2 but certain treatment conditions could be anti-arrhythmogenic in P1. Moreover, the remuscularization site was the most important factor affecting VT burden in both P1 and P2. Complete maturation of PSC-CM patches, both ionically and electrotonically, at the appropriate site could completely alleviate VT burden.

CONCLUSION

We identified that re-entrant VT would be the primary VT mechanism in patch remuscularization. To evaluate the arrhythmogenicity of remuscularization, we developed a principled approach that factors in the propensity of the patient-specific fibrotic substrate for VT. We showed that arrhythmogenicity is sensitive to the patient-specific fibrotic substrate and remuscularization site. We demonstrate that targeted remuscularization can be safe in the appropriate individual and holds the potential to non-destructively eliminate VT post-MI in addition to addressing muscle deficiency underlying heart failure progression.

Atrial fibrillation driver identification through regional mutual information networks: a modeling perspective

Purpose

Effective identification of electrical drivers within remodeled tissue is a key for improving ablation treatment for atrial fibrillation. We have developed a mutual information, graph-based approach to identify and propose fault tolerance metric of local efficiency as a distinguishing feature of rotational activation and remodeled atrial tissue.

Methods

Voltage data were extracted from atrial tissue simulations (2D Karma, 3D physiological, and the Multiscale Cardiac Simulation Framework (MSCSF)) using multi-spline open and parallel regional mapping catheter geometries. Graphs were generated based on varied mutual information thresholds between electrode pairs and the local efficiency for each graph was calculated.

Results

High-resolution mapping catheter geometries can distinguish between rotational and irregular activation patterns using the derivative of local efficiency as a function of increasing mutual information threshold. The derivative is decreased for rotational activation patterns comparing to irregular activations in both a simplified 2D model (0.0017 ± 1 × 10⁻⁴ vs. 0.0032 ± 1 × 10⁻⁴, p < 0.01) and a more realistic 3D model (0.00092 ± 5 × 10⁻⁵ vs. 0.0014 ± 4 × 10⁻⁵, p < 0.01). Average local efficiency derivative can also distinguish between degrees of remodeling. Simulations using the MSCSF model, with 10 vs. 90% remodeling, display distinct derivatives in the grid design parallel spline catheter configuration (0.0015 ± 5 × 10⁻⁵ vs. 0.0019 ± 6 × 10⁻⁵, p < 0.01) and the flower shaped open spline configuration (0.0011 ± 5 × 10⁻⁵ vs. 0.0016 ± 4 × 10⁻⁵, p < 0.01).

Conclusion

A decreased derivative of local efficiency characterizes rotational activation and varies with atrial remodeling. This suggests a distinct communication pattern in cardiac rotational activation detectable via high-resolution regional mapping and could enable identification of electrical drivers for targeted ablation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10840-021-01101-z.

Structure and function of the ventricular tachycardia isthmus

Catheter ablation of postinfarction reentrant ventricular tachycardia (VT) has received renewed interest owing to the increased availability of high-resolution electroanatomic mapping systems that can describe the VT circuits in greater detail, and the emergence and need to target noninvasive external beam radioablation. These recent advancements provide optimism for improving the clinical outcome of VT ablation in patients with postinfarction and potentially other scar-related VTs. The combination of analyses gleaned from studies in swine and canine models of postinfarction reentrant VT, and in human studies, suggests the existence of common electroanatomic properties for reentrant VT circuits. Characterizing these properties may be useful for increasing the specificity of substrate mapping techniques and for noninvasive identification to guide ablation. Herein, we describe properties of reentrant VT circuits that may assist in elucidating the mechanisms of onset and maintenance, as well as a means to localize and delineate optimal catheter ablation targets.

Ventricular Arrhythmias in Ischemic Cardiomyopathy-New Avenues for Mechanism-Guided Treatment

Ischemic heart disease is the most common cause of lethal ventricular arrhythmias and sudden cardiac death (SCD). In patients who are at high risk after myocardial infarction, implantable cardioverter defibrillators are the most effective treatment to reduce incidence of SCD and ablation therapy can be effective for ventricular arrhythmias with identifiable culprit lesions. Yet, these approaches are not always successful and come with a considerable cost, while pharmacological management is often poor and ineffective, and occasionally proarrhythmic. Advances in mechanistic insights of arrhythmias and technological innovation have led to improved interventional approaches that are being evaluated clinically, yet pharmacological advancement has remained behind. We review the mechanistic basis for current management and provide a perspective for gaining new insights that centre on the complex tissue architecture of the arrhythmogenic infarct and border zone with surviving cardiac myocytes as the source of triggers and central players in re-entry circuits. Identification of the arrhythmia critical sites and characterisation of the molecular signature unique to these sites can open avenues for targeted therapy and reduce off-target effects that have hampered systemic pharmacotherapy. Such advances are in line with precision medicine and a patient-tailored therapy.

Whole-heart ventricular arrhythmia modeling moving forward: Mechanistic insights and translational applications

Ventricular arrhythmias are the primary cause of sudden cardiac death and one of the leading causes of mortality worldwide. Whole-heart computational modeling offers a unique approach for studying ventricular arrhythmias, offering vast potential for developing both a mechanistic understanding of ventricular arrhythmias and clinical applications for treatment. In this review, the fundamentals of whole-heart ventricular modeling and current methods of personalizing models using clinical data are presented. From this foundation, the authors summarize recent advances in whole-heart ventricular arrhythmia modeling. Efforts in gaining mechanistic insights into ventricular arrhythmias are discussed, in addition to other applications of models such as the assessment of novel therapeutics. The review emphasizes the unique benefits of computational modeling that allow for insights that are not obtainable by contemporary experimental or clinical means. Additionally, the clinical impact of modeling is explored, demonstrating how patient care is influenced by the information gained from ventricular arrhythmia models. The authors conclude with future perspectives about the direction of whole-heart ventricular arrhythmia modeling, outlining how advances in neural network methodologies hold the potential to reduce computational expense and permit for efficient whole-heart modeling.

Modulating the Infarcted Ventricle's Refractoriness with an Epicardial Biomaterial

Patients diagnosed with heart failure with reduced ejection fraction (HFrEF) are at increased risk of monomorphic ventricular tachycardia (VT) and ventricular fibrillation. The presence of myocardial fibrosis provides both anatomical and functional barriers that promote arrhythmias in these patients. Propagation of VT in a reentrant circuit depends on the presence of excitable myocardium and the refractoriness of the circuit. We hypothesize that myocardial refractoriness can be modulated surgically in a model of HFrEF, leading to decreased susceptibility to VT.Male Sprague-Dawley rats were infarcted via permanent left coronary artery ligation. At 3 weeks post-infarction, engineered grafts composed of human dermal fibroblasts cultured into a polyglactin-910 biomaterial were implanted onto the epicardium to cover the area of infarction. Three weeks post-graft treatment, all rats underwent a terminal electrophysiologic study to compare monophasic action potential electroanatomic maps and susceptibility to inducible monomorphic VT.HFrEF rats (n=29) demonstrated a longer (p=0.0191) ventricular effective refractory period (ERP) and a greater (p=0.0394) VT inducibility compared with sham (n=7). HFrEF rats treated with the graft (n=12) exhibited no change in capture threshold (p=0.3220), but had a longer ventricular ERP (p=0.0029) compared with HFrEF. No statistically significant change in VT incidence was found between HFrEF rats treated with the graft and untreated HFrEF rats (p=0.0834).Surgical deployment of a fibroblast-containing biomaterial in a rodent ischemic cardiomyopathy model prolonged ventricular ERP as measured by programmed electrical stimulation. This hypothesis-generating study warrants additional studies to further characterize the antiarrhythmic or proarrhythmic effects of this novel surgical therapy.

In-silico pace-mapping using a detailed whole torso model and implanted electronic device electrograms for more efficient ablation planning

BACKGROUND

Pace-mapping is a commonly used electrophysiological (EP) procedure which aims to identify exit sites of ventricular tachycardia (VT) by matching ventricular activation patterns (assessed by QRS morphology) at specific pacing locations with activation during VT. However, long procedure durations and the need for VT induction render this technique non-optimal. To demonstrate the potential of in-silico pace-mapping, using stored electrogram (EGM) recordings of clinical VT from implanted devices to guide pre-procedural ablation planning.

METHOD

Six scar-related VT episodes were simulated in a 3D torso model reconstructed from computed tomography (CT) imaging data, including three different infarct anatomies mapped from infarcted porcine imaging data. In-silico pace-mapping was performed to localise VT exit sites and isthmuses by using 12-lead electrocardiogram (ECG) signals and different combinations of EGM sensing vectors from implanted devices, through the creation of conventional correlation maps and reference-less maps.

RESULTS

Our in-silico platform was successful in identifying VT exit sites for a variety of different VT morphologies from both ECG correlation maps and corresponding EGM maps, with the latter dependent upon the number of sensing vectors used. We also showed the added utility of both ECG and EGM reference-less pace-mapping for the identification of slow-conducting isthmuses, uncovering the optimal algorithm parameters. Finally, EGM-based pace-mapping was shown to be more dependent upon the mapped surface (epicardial/endocardial), relative to the VT origin.

CONCLUSIONS

In-silico pace-mapping can be used along with EGMs from implanted devices to localise VT ablation targets in pre-procedural planning.

Connexin43 expression in bone marrow derived cells contributes to the electrophysiological properties of cardiac scar tissue

Cardiac pathologies associated with arrhythmic activity are often accompanied by inflammation. The contribution of inflammatory cells to the electrophysiological properties of injured myocardium is unknown. Myocardial scar cell types and intercellular contacts were analyzed using a three-dimensional reconstruction from serial blockface scanning electron microscopy data. Three distinct cell populations were identified: inflammatory, fibroblastic and endocardial cells. While individual fibroblastic cells interface with a greater number of cells, inflammatory cells have the largest contact area suggesting a role in establishing intercellular electrical connections in scar tissue. Optical mapping was used to study the electrophysiological properties of scars in fetal liver chimeric mice generated using connexin43 knockout donors (bmpKO). Voltage changes were elicited in response to applied current pulses. Isopotential maps showed a steeper pattern of decay with distance from the electrode in scars compared with uninjured regions, suggesting reduced electrical coupling. The tissue decay constant, defined as the distance voltage reaches 37% of the amplitude at the edge of the scar, was 0.48 ± 0.04 mm (n = 11) in the scar of the bmpCTL group and decreased 37.5% in the bmpKO group (n = 10). Together these data demonstrate inflammatory cells significantly contribute to scar electrophysiology through coupling mediated at least partially by connexin43 expression.

Altered adrenergic response in myocytes bordering a chronic myocardial infarction underlies in vivo triggered activity and repolarization instability

Key points

Ventricular arrhythmias are a major complication after myocardial infarction (MI), associated with sympathetic activation. The structurally heterogeneous peri‐infarct zone is a known substrate, but the functional role of the myocytes is less well known.

Recordings of monophasic action potentials in vivo reveal that the peri‐infarct zone is a source of delayed afterdepolarizations (DADs) and has a high beat‐to‐beat variability of repolarization (BVR) during adrenergic stimulation (isoproterenol, ISO).

Myocytes isolated from the peri‐infarct region have more DADs and spontaneous action potentials, with spontaneous Ca²⁺ release, under ISO. These myocytes also have reduced repolarization reserve and increased BVR. Other properties of post‐MI remodelling are present in both peri‐infarct and remote myocytes.

These data highlight the importance of altered myocyte adrenergic responses in the peri‐infarct region as source and substrate of post‐MI arrhythmias.

Abstract

Ventricular arrhythmias are a major early complication after myocardial infarction (MI). The heterogeneous peri‐infarct zone forms a substrate for re‐entry while arrhythmia initiation is often associated with sympathetic activation. We studied the mechanisms triggering these post‐MI arrhythmias in vivo and their relation to regional myocyte remodelling. In pigs with chronic MI (6 weeks), in vivo monophasic action potentials were simultaneously recorded in the peri‐infarct and remote regions during adrenergic stimulation with isoproterenol (isoprenaline; ISO). Sham animals served as controls. During infusion of ISO in vivo, the incidence of delayed afterdepolarizations (DADs) and beat‐to‐beat variability of repolarization (BVR) was higher in the peri‐infarct than in the remote region. Myocytes isolated from the peri‐infarct region, in comparison to myocytes from the remote region, had more DADs, associated with spontaneous Ca²⁺ release, and a higher incidence of spontaneous action potentials (APs) when exposed to ISO (9.99 ± 4.2 vs. 0.16 ± 0.05 APs/min, p = 0.004); these were suppressed by CaMKII inhibition. Peri‐infarct myocytes also had reduced repolarization reserve and increased BVR (26 ± 10 ms vs. 9 ± 7 ms, P < 0.001), correlating with DAD activity. In contrast to these regional distinctions under ISO, alterations in Ca²⁺ handling at baseline and myocyte hypertrophy were present throughout the left ventricle (LV). Expression of some of the related genes was, however, different between the regions. In conclusion, altered myocyte adrenergic responses in the peri‐infarct but not the remote region provide a source of triggered activity in vivo and of repolarization instability amplifying the substrate for re‐entry. These findings stimulate further exploration of region‐specific therapies targeting myocytes and autonomic modulation.

Ventricular arrhythmias are a major complication after myocardial infarction (MI), associated with sympathetic activation. The structurally heterogeneous peri‐infarct zone is a known substrate, but the functional role of the myocytes is less well known.

Recordings of monophasic action potentials in vivo reveal that the peri‐infarct zone is a source of delayed afterdepolarizations (DADs) and has a high beat‐to‐beat variability of repolarization (BVR) during adrenergic stimulation (isoproterenol, ISO).

Myocytes isolated from the peri‐infarct region have more DADs and spontaneous action potentials, with spontaneous Ca²⁺ release, under ISO. These myocytes also have reduced repolarization reserve and increased BVR. Other properties of post‐MI remodelling are present in both peri‐infarct and remote myocytes.

These data highlight the importance of altered myocyte adrenergic responses in the peri‐infarct region as source and substrate of post‐MI arrhythmias.

How personalized heart modeling can help treatment of lethal arrhythmias: A focus on ventricular tachycardia ablation strategies in post-infarction patients

Precision Cardiology is a targeted strategy for cardiovascular disease prevention and treatment that accounts for individual variability. Computational heart modeling is one of the novel approaches that have been developed under the umbrella of Precision Cardiology. Personalized computational modeling of patient hearts has made strides in the development of models that incorporate the individual geometry and structure of the heart as well as other patient-specific information. Of these developments, one of the potentially most impactful is the research aimed at noninvasively predicting the targets of ablation of lethal arrhythmia, ventricular tachycardia (VT), using patient-specific models. The approach has been successfully applied to patients with ischemic cardiomyopathy in proof-of-concept studies. The goal of this paper is to review the strategies for computational VT ablation guidance in ischemic cardiomyopathy patients, from model developments to the intricacies of the actual clinical application. To provide context in describing the road these computational modeling applications have undertaken, we first review the state of the art in VT ablation in the clinic, emphasizing the benefits that personalized computational prediction of ablation targets could bring to the clinical electrophysiology practice. This article is characterized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Translational, Genomic, and Systems Medicine > Translational Medicine.

Improved co-registration of ex-vivo and in-vivo cardiovascular magnetic resonance images using heart-specific flexible 3D printed acrylic scaffold combined with non-rigid registration

BACKGROUND

Ex-vivo cardiovascular magnetic resonance (CMR) imaging has played an important role in the validation of in-vivo CMR characterization of pathological processes. However, comparison between in-vivo and ex-vivo imaging remains challenging due to shape changes occurring between the two states, which may be non-uniform across the diseased heart. A novel two-step process to facilitate registration between ex-vivo and in-vivo CMR was developed and evaluated in a porcine model of chronic myocardial infarction (MI).

METHODS

Seven weeks after ischemia-reperfusion MI, 12 swine underwent in-vivo CMR imaging with late gadolinium enhancement followed by ex-vivo CMR 1 week later. Five animals comprised the control group, in which ex-vivo imaging was undertaken without any support in the LV cavity, 7 animals comprised the experimental group, in which a two-step registration optimization process was undertaken. The first step involved a heart specific flexible 3D printed scaffold generated from in-vivo CMR, which was used to maintain left ventricular (LV) shape during ex-vivo imaging. In the second step, a non-rigid co-registration algorithm was applied to align in-vivo and ex-vivo data. Tissue dimension changes between in-vivo and ex-vivo imaging were compared between the experimental and control group. In the experimental group, tissue compartment volumes and thickness were compared between in-vivo and ex-vivo data before and after non-rigid registration. The effectiveness of the alignment was assessed quantitatively using the DICE similarity coefficient.

RESULTS

LV cavity volume changed more in the control group (ratio of cavity volume between ex-vivo and in-vivo imaging in control and experimental group 0.14 vs 0.56, p < 0.0001) and there was a significantly greater change in the short axis dimensions in the control group (ratio of short axis dimensions in control and experimental group 0.38 vs 0.79, p < 0.001). In the experimental group, prior to non-rigid co-registration the LV cavity contracted isotropically in the ex-vivo condition by less than 20% in each dimension. There was a significant proportional change in tissue thickness in the healthy myocardium (change = 29 ± 21%), but not in dense scar (change = - 2 ± 2%, p = 0.034). Following the non-rigid co-registration step of the process, the DICE similarity coefficients for the myocardium, LV cavity and scar were 0.93 (±0.02), 0.89 (±0.01) and 0.77 (±0.07) respectively and the myocardial tissue and LV cavity volumes had a ratio of 1.03 and 1.00 respectively.

CONCLUSIONS

The pattern of the morphological changes seen between the in-vivo and the ex-vivo LV differs between scar and healthy myocardium. A 3D printed flexible scaffold based on the in-vivo shape of the LV cavity is an effective strategy to minimize morphological changes in the ex-vivo LV. The subsequent non-rigid registration step further improved the co-registration and local comparison between in-vivo and ex-vivo data.

Factors Promoting Conduction Slowing as Substrates for Block and Reentry in Infarcted Hearts

The development of effective and safe therapies for scar-related ventricular tachycardias requires a detailed understanding of the mechanisms underlying the conduction block that initiates electrical re-entries associated with these arrhythmias. Conduction block has been often associated with electrophysiological changes that prolong action potential duration (APD) within the border zone (BZ) of chronically infarcted hearts. However, experimental evidence suggests that remodeling processes promoting conduction slowing as opposed to APD prolongation mark the chronic phase. In this context, the substrate for the initial block at the mouth of an isthmus/diastolic channel leading to ventricular tachycardia is unclear. The goal of this study was to determine whether electrophysiological parameters associated with conduction slowing can cause block and re-entry in the BZ. In silico experiments were conducted on two-dimensional idealized infarct tissue as well as on a cohort of postinfarction porcine left ventricular models constructed from ex vivo magnetic resonance imaging scans. Functional conduction slowing in the BZ was modeled by reducing sodium current density, whereas structural conduction slowing was represented by decreasing tissue conductivity and including fibrosis. The arrhythmogenic potential of APD prolongation was also tested as a basis for comparison. Within all models, the combination of reduced sodium current with structural remodeling more often degenerated into re-entry and, if so, was more likely to be sustained for more cycles. Although re-entries were also detected in experiments with prolonged APD, they were often not sustained because of the subsequent block caused by long-lasting repolarization. Functional and structural conditions associated with slow conduction rather than APD prolongation form a potent substrate for arrhythmogenesis at the isthmus/BZ of chronically infarcted hearts. Reduced excitability led to block while slow conduction shortened the wavelength of propagation, facilitating the sustenance of re-entries. These findings provide important insights for models of patient-specific risk stratification and therapy planning.

Characterizing Conduction Channels in Postinfarction Patients Using a Personalized Virtual Heart

Patients with myocardial infarction have an abundance of conduction channels (CC); however, only a small subset of these CCs sustain ventricular tachycardia (VT). Identifying these critical CCs (CCCs) in the clinic so that they can be targeted by ablation remains a significant challenge. The objective of this study is to use a personalized virtual-heart approach to conduct a three-dimensional (3D) assessment of CCCs sustaining VTs of different morphologies in these patients, to investigate their 3D structural features, and to determine the optimal ablation strategy for each VT. To achieve these goals, ventricular models were constructed from contrast enhanced magnetic resonance imagings of six postinfarction patients. Rapid pacing induced VTs in each model. CCCs that sustained different VT morphologies were identified. CCCs' 3D structure and type and the resulting rotational electrical activity were examined. Ablation was performed at the optimal part of each CCC, aiming to terminate each VT with a minimal lesion size. Predicted ablation locations were compared to clinical. Analyzing the simulation results, we found that the observed VTs in each patient model were sustained by a limited number (2.7 ± 1.2) of CCCs. Further, we identified three types of CCCs sustaining VTs: I-type and T-type channels, with all channel branches bounded by scar, and functional reentry channels, which were fully or partially bounded by conduction block surfaces. The different types of CCCs accounted for 43.8, 18.8, and 37.4% of all CCCs, respectively. The mean narrowest width of CCCs or a branch of CCC was 9.7 ± 3.6 mm. Ablation of the narrowest part of each CCC was sufficient to terminate VT. Our results demonstrate that a personalized virtual-heart approach can determine the possible VT morphologies in each patient and identify the CCCs that sustain reentry. The approach can aid clinicians in identifying accurately the optimal VT ablation targets in postinfarction patients.

The Role of Cardiac MRI in the Management of Ventricular Arrhythmias in Ischaemic and Non-ischaemic Dilated Cardiomyopathy

Ventricular tachycardia (VT) and VF account for the majority of sudden cardiac deaths worldwide. Treatments for VT/VF include anti-arrhythmic drugs, ICDs and catheter ablation, but these treatments vary in effectiveness and carry substantial risks and/or expense. Current methods of selecting patients for ICD implantation are imprecise and fail to identify some at-risk patients, while leading to others being overtreated. In this article, the authors discuss the current role and future direction of cardiac MRI (CMRI) in refining diagnosis and personalising ventricular arrhythmia management. The capability of CMRI with gadolinium contrast delayed-enhancement patterns and, more recently, T1 mapping to determine the aetiology of patients presenting with heart failure is well established. Although CMRI imaging in patients with ICDs can be challenging, recent technical developments have started to overcome this. CMRI can contribute to risk stratification, with precise and reproducible assessment of ejection fraction, quantification of scar and 'border zone' volumes, and other indices. Detailed tissue characterisation has begun to enable creation of personalised computer models to predict an individual patient's arrhythmia risk. When patients require VT ablation, a substrate-based approach is frequently employed as haemodynamic instability may limit electrophysiological activation mapping. Beyond accurate localisation of substrate, CMRI could be used to predict the location of re-entrant circuits within the scar to guide ablation.

A comprehensive, multiscale framework for evaluation of arrhythmias arising from cell therapy in the whole post-myocardial infarcted heart

Direct remuscularization approaches to cell-based heart repair seek to restore ventricular contractility following myocardial infarction (MI) by introducing new cardiomyocytes (CMs) to replace lost or injured ones. However, despite promising improvements in cardiac function, high incidences of ventricular arrhythmias have been observed in animal models of MI injected with pluripotent stem cell-derived cardiomyocytes (PSC-CMs). The mechanisms of arrhythmogenesis remain unclear. Here, we present a comprehensive framework for computational modeling of direct remuscularization approaches to cell therapy. Our multiscale 3D whole-heart modeling framework integrates realistic representations of cell delivery and transdifferentiation therapy modalities as well as representation of spatial distributions of engrafted cells, enabling simulation of clinical therapy and the prediction of emergent electrophysiological behavior and arrhythmogenensis. We employ this framework to explore how varying parameters of cell delivery and transdifferentiation could result in three mechanisms of arrhythmogenesis: focal ectopy, heart block, and reentry.

Information theory to tachycardia therapy: electrogram entropy predicts diastolic microstructure of reentrant ventricular tachycardia

There is no known strategy to differentiate which multicomponent electrograms in sinus rhythm maintain reentrant ventricular tachycardia (VT). Low entropy in the voltage breakdown of a multicomponent electrogram can localize conditions suitable for reentry but has not been validated against the classic VT activation mapping. We examined whether low entropy in a late and diversely activated ventricular scar region characterizes and differentiates the diastolic path of VT and represents protected tissue channels devoid of side branches. Intraoperative bipolar electrogram (BiEGM) activation and entropy maps were obtained during sinus rhythm in 17 patients with ischemic cardiomyopathy and compared with diastolic activation paths of VT (total of 39 VTs). Mathematical modeling of a zigzag main channel with side branches was also used to further validate structural representation of low entropy in the ventricular scar. A median of one region per patient (range: 1–2 regions) was identified in sinus rhythm, in which BiEGMwith the latest mean activation time and adjacent minimum entropy were assembled together in a high-activation dispersion region. These regions accurately recognized diastolic paths of 34 VTs, often to multiple inducible VTs within a single individual arrhythmogenic region. In mathematical modeling, side branching from the main channel had a strong influence on the BiEGMcomposition along the main channel. The BiEGMobtained from a long unbranched channel had the lowest entropy compared with those with multiple side branches. In conclusion, among a population of multicomponent sinus electrograms, those that demonstrate low entropy and are delayed colocalize to critical long-protected channels of VT. This information is pertinent for planning VT ablation in sinus rhythm.

NEW & NOTEWORTHY Entropy is a measure to quantify breakdown in information. Electrograms from a protected tissue channel can only possess a few states in their voltage and thus less information. In contrast, current-load interactions from side branches in unprotected channels introduce a number of dissimilar voltage deflections and thus high information. We compare here a mapping approach based on entropy against a rigorous reference standard of activation mapping during VT and entropy was assessed in sinus rhythm.

Optimal contrast-enhanced MRI image thresholding for accurate prediction of ventricular tachycardia using ex-vivo high resolution models

Patient specific models created from contrast-enhanced (i.e. late-gadolinium, LGE) MRI images can be used for prediction of reentry location and clinical ablation planning. However, there is still a need for direct and systematic comparison between characteristics of ventricular tachycardia (VT) morphologies predicted in computational models and those acquired in clinical or experimental protocols. In this study, we aimed to: 1) assess the differences in VT morphologies predicted by modeling and recorded in experiments in terms of patterns and location of reentries, earliest and latest activation sites, and cycle lengths; and 2) define the optimal range of infarct tissue threshold values which provide best match between simulation and experimental results. To achieve these goals, we utilized LGE-MRI images from 4 swine hearts with inducible monomorphic VT. The images were segmented to identify non-infarcted myocardium, semi viable gray zone (GZ), and core scar based on pixel intensity. Several models were reconstructed from each LGE-MRI scan, with voxels of intensity between that of non-infarcted myocardium and 20-50% of the maximum intensity (in 10% increments) in the infarct region classified as GZ. VT induction was simulated in each model. Our simulation results showed that using GZ intensity thresholds of 20% or 30% resulted in the best match of simulated propagation patterns and reentry locations with those from the experiment. Overall, we matched 70% (7/10) morphologies for all the hearts. Our simulation shows that MRI-based computational models of hearts with myocardial infarction can accurately reproduce the majority of experimentally recorded post-infarction VTs.