Noninvasive detection of spatiotemporal activation-repolarization interactions that prime idiopathic ventricular fibrillation

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.

The Dutch Idiopathic Ventricular Fibrillation Registry: progress report on the quest to identify the unidentifiable

BACKGROUND

Idiopathic ventricular fibrillation (iVF) is a rare cause of sudden cardiac arrest and, by definition, a diagnosis of exclusion. Due to the rarity of the disease, previous and current studies are limited by their retrospective design and small patient numbers. Even though the incidence of iVF has declined owing to the identification of new disease entities, an important subgroup of patients remains.

AIM

To expand the existing Dutch iVF Registry into a large nationwide cohort of patients initially diagnosed with iVF, to reveal the underlying cause of iVF in these patients, and to improve arrhythmia management.

METHODS

The Dutch iVF Registry includes sudden cardiac arrest survivors with an initial diagnosis of iVF. Clinical data and outcomes are collected. Outcomes include subsequent detection of a diagnosis other than 'idiopathic', arrhythmia recurrence and death. Non-invasive electrocardiographic imaging is used to investigate electropathological substrates and triggers of VF.

RESULTS

To date, 432 patients have been included in the registry (median age at event 40 years (interquartile range 28-52)), 61% male. During a median follow-up of 6 (2-12) years, 38 patients (9%) received a diagnosis other than 'idiopathic'. Eleven iVF patients were characterised with electrocardiographic imaging.

CONCLUSION

The Dutch iVF Registry is currently the largest of its kind worldwide. In this heterogeneous population of index patients, we aim to identify common functional denominators associated with iVF. With the implementation of non-invasive electrocardiographic imaging and other diagnostic modalities (e.g. echocardiographic deformation, cardiac magnetic resonance), we advance the possibilities to reveal pro-fibrillatory substrates.

Digital twins for cardiac electrophysiology: state of the art and future challenges

Cardiac arrhythmias remain a major cause of death and disability. Current antiarrhythmic therapies are effective to only a limited extent, likely in large part due to their mechanism-independent approach. Precision cardiology aims to deliver targeted therapy for an individual patient to maximize efficacy and minimize adverse effects. In-silico digital twins have emerged as a promising strategy to realize the vision of precision cardiology. While there is no uniform definition of a digital twin, it typically employs digital tools, including simulations of mechanistic computer models, based on patient-specific clinical data to understand arrhythmia mechanisms and/or make clinically relevant predictions. Digital twins have become part of routine clinical practice in the setting of interventional cardiology, where commercially available services use digital twins to non-invasively determine the severity of stenosis (computed tomography-based fractional flow reserve). Although routine clinical application has not been achieved for cardiac arrhythmia management, significant progress towards digital twins for cardiac electrophysiology has been made in recent years. At the same time, significant technical and clinical challenges remain. This article provides a short overview of the history of digital twins for cardiac electrophysiology, including recent applications for the prediction of sudden cardiac death risk and the tailoring of rhythm control in atrial fibrillation. The authors highlight the current challenges for routine clinical application and discuss how overcoming these challenges may allow digital twins to enable a significant precision medicine-based advancement in cardiac arrhythmia management.

Strain-controlled electrophysiological wave propagation alters in silico scar-based substrate for ventricular tachycardia

Introduction: Assessing a patient's risk of scar-based ventricular tachycardia (VT) after myocardial infarction is a challenging task. It can take months to years after infarction for VT to occur. Also, if selected for ablation therapy, success rates are low. Methods: Computational ventricular models have been presented previously to support VT risk assessment and to provide ablation guidance. In this study, an extension to such virtual-heart models is proposed to phenomenologically incorporate tissue remodeling driven by mechanical load. Strain amplitudes in the heart muscle are obtained from simulations of mechanics and are used to adjust the electrical conductivity. Results: The mechanics-driven adaptation of electrophysiology resulted in a more heterogeneous distribution of propagation velocities than that of standard models, which adapt electrophysiology in the structural substrate from medical images only. Moreover, conduction slowing was not only present in such a structural substrate, but extended in the adjacent functional border zone with impaired mechanics. This enlarged the volumes with high repolarization time gradients (≥10 ms/mm). However, maximum gradient values were not significantly affected. The enlarged volumes were localized along the structural substrate border, which lengthened the line of conduction block. The prolonged reentry pathways together with conduction slowing in functional regions increased VT cycle time, such that VT was easier to induce, and the number of recommended ablation sites increased from 3 to 5 locations. Discussion: Sensitivity testing showed an accurate model of strain-dependency to be critical for low ranges of conductivity. The model extension with mechanics-driven tissue remodeling is a potential approach to capture the evolution of the functional substrate and may offer insight into the progression of VT risk over time.

Electrophysiological Characterization of Subclinical and Overt Hypertrophic Cardiomyopathy by Magnetic Resonance Imaging-Guided Electrocardiography

BACKGROUND

Ventricular arrhythmia in hypertrophic cardiomyopathy (HCM) relates to adverse structural change and genetic status. Cardiovascular magnetic resonance (CMR)-guided electrocardiographic imaging (ECGI) noninvasively maps cardiac structural and electrophysiological (EP) properties.

OBJECTIVES

The purpose of this study was to establish whether in subclinical HCM (genotype [G]+ left ventricular hypertrophy [LVH]-), ECGI detects early EP abnormality, and in overt HCM, whether the EP substrate relates to genetic status (G+/G-LVH+) and structural phenotype.

METHODS

This was a prospective 211-participant CMR-ECGI multicenter study of 70 G+LVH-, 104 LVH+ (51 G+/53 G-), and 37 healthy volunteers (HVs). Local activation time (AT), corrected repolarization time, corrected activation-recovery interval, spatial gradients (GAT/GRTc), and signal fractionation were derived from 1,000 epicardial sites per participant. Maximal wall thickness and scar burden were derived from CMR. A support vector machine was built to discriminate G+LVH- from HV and low-risk HCM from those with intermediate/high-risk score or nonsustained ventricular tachycardia.

RESULTS

Compared with HV, subclinical HCM showed mean AT prolongation (P = 0.008) even with normal 12-lead electrocardiograms (ECGs) (P = 0.009), and repolarization was more spatially heterogenous (GRTc: P = 0.005) (23% had normal ECGs). Corrected activation-recovery interval was prolonged in overt vs subclinical HCM (P < 0.001). Mean AT was associated with maximal wall thickness; spatial conduction heterogeneity (GAT) and fractionation were associated with scar (all P < 0.05), and G+LVH+ had more fractionation than G-LVH+ (P = 0.002). The support vector machine discriminated subclinical HCM from HV (10-fold cross-validation accuracy 80% [95% CI: 73%-85%]) and identified patients at higher risk of sudden cardiac death (accuracy 82% [95% CI: 78%-86%]).

CONCLUSIONS

In the absence of LVH or 12-lead ECG abnormalities, HCM sarcomere gene mutation carriers express an aberrant EP phenotype detected by ECGI. In overt HCM, abnormalities occur more severely with adverse structural change and positive genetic status.

Optogenetic manipulation of cardiac repolarization gradients using sub-threshold illumination

Introduction: Mechanisms underlying cardiac arrhythmias are typically driven by abnormalities in cardiac conduction and/or heterogeneities in repolarization time (RT) across the heart. While conduction slowing can be caused by either electrophysiological defects or physical blockade in cardiac tissue, RT heterogeneities are mainly related to action potential (AP) prolongation or abbreviation in specific areas of the heart. Importantly, the size of the area with altered RT and the difference between the short RT and long RT (RT gradient) have been identified as critical determinators of arrhythmogenicity. However, current experimental methods for manipulating RT gradient rely on the use of ion channel inhibitors, which lack spatial and temporal specificity and are commonly only partially reversible. Therefore, the conditions facilitating sustained arrhythmia upon the presence of RT heterogeneities and/or defects in cardiac conduction remain to be elucidated. Methods: We here employ an approach based on optogenetic stimulation in a low-intensity fashion (sub-threshold illumination), to selectively manipulate cardiac electrical activity in defined areas of the heart. Results: As previously described, subthreshold illumination is a robust tool able to prolong action potentials (AP), decrease upstroke velocity as well as slow cardiac conduction, in a fully reversible manner. By applying a patterned sub-threshold illumination in intact mouse hearts constitutively expressing the light-gated ion channel channelrhodopsin-2 (ChR2), we optically manipulate RT gradients and cardiac conduction across the heart in a spatially selective manner. Moreover, in a proof-of-concept assessment we found that in the presence of patterned sub-threshold illumination, mouse hearts were more susceptible to arrhythmias. Hence, this optogenetic-based approach may be able to mimic conduction slowing and RT heterogeneities present in pathophysiological conditions.

Idiopathic ventricular fibrillation associated with long-coupled Purkinje ectopy

INTRODUCTION

Idiopathic ventricular fibrillation (IVF) is mainly associated with and triggered by short-coupled (R-on-T) ventricular ectopics. However, little is known about the risk of VF associated with long-coupled premature ventricular complexes (LCPVCs).

OBJECTIVE

To examine the prevalence and characteristics of IVF patients presenting with LCPVCs.

METHODS

Consecutive patients with IVF and PVCs from five arrhythmia referral centers were reviewed. We included patients presenting LCPVCs, defined as PVCs falling after the end of the T wave, with a normal QTc interval. We evaluated demographics, medical history, and clinical circumstances associated with PVCs and VF episodes. The origin of PVCs was determined by invasive mapping.

RESULTS

Seventy-nine patients with IVF were reviewed. Among them, 12 (15.2%) met the inclusion criteria (8 women, age 36 ± 14 years). Eleven patients had documented LCPVCs initiating repetitive PVCs or sustained VF, whereas 1 had only documented isolated PVCs. In 10 of 12 patients, PVCs were recorded showing both long and short coupling intervals of 418 ± 46 and 304 ± 33 ms, respectively. Mapping showed that PVCs originated from the left Purkinje in 10 patients, from the right Purkinje in 1 patient, and both in 1 patient. Compared to other patients from the initial cohort, IVF with LCPVCs was associated with a left-sided origin of PVCs (92% in long-coupled IVF vs. 46% of left Purkinje PVCs in short-coupled IVF, p = .004).

CONCLUSION

Long-coupled fascicular PVCs, traditionally recognized as benign, can be associated with IVF in a subset of patients. They can induce IVF by themselves or in association with short-coupled PVCs.

Understanding repolarization in the intracardiac unipolar electrogram: A long-lasting controversy revisited

Background: The optimal way to determine repolarization time (RT) from the intracardiac unipolar electrogram (UEG) has been a topic of debate for decades. RT is typically determined by either the Wyatt method or the "alternative method," which both consider UEG T-wave slope, but differently. Objective: To determine the optimal method to measure RT on the UEG. Methods: Seven pig hearts surrounded by an epicardial sock with 100 electrodes were Langendorff-perfused with selective cannulation of the left anterior descending (LAD) coronary artery and submersed in a torso-shaped tank containing 256 electrodes on the torso surface. Repolarization was prolonged in the non-LAD-regions by infusing dofetilide and shortened in the LAD-region using pinacidil. RT was determined by the Wyatt (t_Wyatt) and alternative (t_Alt) methods, in both invasive (recorded with epicardial electrodes) and in non-invasive UEGs (reconstructed with electrocardiographic imaging). t_Wyatt and t_Alt were compared to local effective refractory period (ERP). Results: With contact mapping, mean absolute error (MAE) of t_Wyatt and t_Alt vs. ERP were 21 ms and 71 ms, respectively. Positive T-waves typically had an earlier ERP than negative T-waves, in line with theory. t_Wyatt -but not t_Alt-shortened by local infusion of pinacidil. Similar results were found for the non-invasive UEGs (MAE of t_Wyatt and t_Alt vs. ERP were 30 ms and 92 ms, respectively). Conclusion: The Wyatt method is the most accurate to determine RT from (non) invasive UEGs, based on novel and historical analyses. Using it to determine RT could unify and facilitate repolarization assessment and amplify its role in cardiac electrophysiology.

High-resolution structural-functional substrate-trigger characterization: Future roadmap for catheter ablation of ventricular tachycardia

Introduction

Patients with ventricular tachyarrhythmias (VT) are at high risk of sudden cardiac death. When appropriate, catheter ablation is modestly effective, with relatively high VT recurrence and complication rates. Personalized models that incorporate imaging and computational approaches have advanced VT management. However, 3D patient-specific functional electrical information is typically not considered. We hypothesize that incorporating non-invasive 3D electrical and structural characterization in a patient-specific model improves VT-substrate recognition and ablation targeting.

Materials and methods

In a 53-year-old male with ischemic cardiomyopathy and recurrent monomorphic VT, we built a structural-functional model based on high-resolution 3D late-gadolinium enhancement (LGE) cardiac magnetic resonance imaging (3D-LGE CMR), multi-detector computed tomography (CT), and electrocardiographic imaging (ECGI). Invasive data from high-density contact and pace mapping obtained during endocardial VT-substrate modification were also incorporated. The integrated 3D electro-anatomic model was analyzed off-line.

Results

Merging the invasive voltage maps and 3D-LGE CMR endocardial geometry led to a mean Euclidean node-to-node distance of 5 ± 2 mm. Inferolateral and apical areas of low bipolar voltage (<1.5 mV) were associated with high 3D-LGE CMR signal intensity (>0.4) and with higher transmurality of fibrosis. Areas of functional conduction delay or block (evoked delayed potentials, EDPs) were in close proximity to 3D-LGE CMR-derived heterogeneous tissue corridors. ECGI pinpointed the epicardial VT exit at ∼10 mm from the endocardial site of origin, both juxtaposed to the distal ends of two heterogeneous tissue corridors in the inferobasal left ventricle. Radiofrequency ablation at the entrances of these corridors, eliminating all EDPs, and at the VT site of origin rendered the patient non-inducible and arrhythmia-free until the present day (20 months follow-up). Off-line analysis in our model uncovered dynamic electrical instability of the LV inferolateral heterogeneous scar region which set the stage for an evolving VT circuit.

Discussion and conclusion

We developed a personalized 3D model that integrates high-resolution structural and electrical information and allows the investigation of their dynamic interaction during arrhythmia formation. This model enhances our mechanistic understanding of scar-related VT and provides an advanced, non-invasive roadmap for catheter ablation.

The circle of reentry: Characteristics of trigger-substrate interaction leading to sudden cardiac arrest

Sudden cardiac death is often caused by ventricular arrhythmias driven by reentry. Comprehensive characterization of the potential triggers and substrate in survivors of sudden cardiac arrest has provided insights into the trigger-substrate interaction leading to reentry. Previously, a "Triangle of Arrhythmogenesis", reflecting interactions between substrate, trigger and modulating factors, has been proposed to reason about arrhythmia initiation. Here, we expand upon this concept by separating the trigger and substrate characteristics in their spatial and temporal components. This yields four key elements that are required for the initiation of reentry: local dispersion of excitability (e.g., the presence of steep repolarization time gradients), a critical relative size of the region of excitability and the region of inexcitability (e.g., a sufficiently large region with early repolarization), a trigger that originates at a time when some tissue is excitable and other tissue is inexcitable (e.g., an early premature complex), and which occurs from an excitable region (e.g., from a region with early repolarization). We discuss how these findings yield a new mechanistic framework for reasoning about reentry initiation, the "Circle of Reentry." In a patient case of unexplained ventricular fibrillation, we then illustrate how a comprehensive clinical investigation of these trigger-substrate characteristics may help to understand the associated arrhythmia mechanism. We will also discuss how this reentry initiation concept may help to identify patients at risk, and how similar reasoning may apply to other reentrant arrhythmias.

From novel discovery tools and biomarkers to precision medicine-basic cardiovascular science highlights of 2021/22

Here, we review the highlights of cardiovascular basic science published in 2021 and early 2022 on behalf of the European Society of Cardiology Council for Basic Cardiovascular Science. We begin with non-coding RNAs which have emerged as central regulators cardiovascular biology, and then discuss how technological developments in single-cell 'omics are providing new insights into cardiovascular development, inflammation, and disease. We also review recent discoveries on the biology of extracellular vesicles in driving either protective or pathogenic responses. The Nobel Prize in Physiology or Medicine 2021 recognized the importance of the molecular basis of mechanosensing and here we review breakthroughs in cardiovascular sensing of mechanical force. We also summarize discoveries in the field of atherosclerosis including the role of clonal haematopoiesis of indeterminate potential, and new mechanisms of crosstalk between hyperglycaemia, lipid mediators, and inflammation. The past 12 months also witnessed major advances in the field of cardiac arrhythmia including new mechanisms of fibrillation. We also focus on inducible pluripotent stem cell technology which has demonstrated disease causality for several genetic polymorphisms in long-QT syndrome and aortic valve disease, paving the way for personalized medicine approaches. Finally, the cardiovascular community has continued to better understand COVID-19 with significant advancement in our knowledge of cardiovascular tropism, molecular markers, the mechanism of vaccine-induced thrombotic complications and new anti-viral therapies that protect the cardiovascular system.

State-of-the-Art Multimodality Imaging in Sudden Cardiac Arrest with Focus on Idiopathic Ventricular Fibrillation: A Review

Idiopathic ventricular fibrillation is a rare cause of sudden cardiac arrest and a diagnosis by exclusion. Unraveling the mechanism of ventricular fibrillation is important for targeted management, and potentially for initiating family screening. Sudden cardiac arrest survivors undergo extensive clinical testing, with a growing role for multimodality imaging, before diagnosing “idiopathic” ventricular fibrillation. Multimodality imaging, considered as using multiple imaging modalities as diagnostics, is important for revealing structural myocardial abnormalities in patients with cardiac arrest. This review focuses on combining imaging modalities (echocardiography, cardiac magnetic resonance and computed tomography) and the electrocardiographic characterization of sudden cardiac arrest survivors and discusses the surplus value of multimodality imaging in the diagnostic routing of these patients. We focus on novel insights obtained through electrostructural and/or electromechanical imaging in apparently idiopathic ventricular fibrillation patients, with special attention to non-invasive electrocardiographic imaging.

Mechanistic Insights Into Inflammation-Induced Arrhythmias: A Simulation Study

Cardiovascular diseases are the primary cause of death of humans, and among these, ventricular arrhythmias are the most common cause of death. There is plausible evidence implicating inflammation in the etiology of ventricular fibrillation (VF). In the case of systemic inflammation caused by an overactive immune response, the induced inflammatory cytokines directly affect the function of ion channels in cardiomyocytes, leading to a prolonged action potential duration (APD). However, the mechanistic links between inflammatory cytokine-induced molecular and cellular influences and inflammation-associated ventricular arrhythmias need to be elucidated. The present study aimed to determine the potential impact of systemic inflammation on ventricular electrophysiology by means of multiscale virtual heart models. The experimental data on the ionic current of three major cytokines [i.e., tumor necrosis factor-α (TNF-α), interleukin-1 (IL-1β), and interleukin-6 (IL-6)] were incorporated into the cell model, and the effects of each cytokine and their combined effect on the cell action potential (AP) were evaluated. Moreover, the integral effect of these cytokines on the conduction of excitation waves was also investigated in a tissue model. The simulation results suggested that inflammatory cytokines significantly prolonged APD, enhanced the transmural and regional repolarization heterogeneities that predispose to arrhythmias, and reduced the adaptability of ventricular tissue to fast heart rates. In addition, simulated pseudo-ECGs showed a prolonged QT interval—a manifestation consistent with clinical observations. In summary, the present study provides new insights into ventricular arrhythmias associated with inflammation.

Myocardial electrophysiological and mechanical changes caused by moderate hypothermia-A clinical study

Moderate hypothermia has been used to improve outcomes in comatose out-of-hospital cardiac arrest survivors during the past two decades, although the effects remain controversial. We have recently shown in an experimental study that myocardial electrophysiological and mechanical relationships were altered during moderate hypothermia. Electromechanical window positivity increased, and electrical dispersion of repolarization decreased, both of which are changes associated with decreased arrhythmogenicity in clinical conditions. Mechanical dispersion, a parameter also linked to arrhythmic risk, remained unaltered. Whether corresponding electrophysiological and mechanical changes occur in humans during moderate hypothermia, has not been previously explored. Twenty patients with normal left ventricular function were included. Measurements were obtained at 36 and 32°C prior to ascending aortic repair while on partial cardiopulmonary bypass and at 36°C after repair. Registrations were performed in the presence of both spontaneous and comparable paced heart rate during standardized loading conditions. The following electrical and mechanical parameters were explored: (1) Electromechanical window, measured as time difference between mechanical and electrical systole, (2) dispersion of repolarization from ECG T-wave, and (3) mechanical dispersion, measured as segmental variation in time to peak echocardiographic strain. At moderate hypothermia, mechanical systolic prolongation (425 ± 43-588 ± 67 ms, p < 0.001) exceeded electrical systolic prolongation (397 ± 49-497 ± 79 ms, p < 0.001), whereby, electromechanical window positivity increased (29 ± 30-86 ± 50 ms, p < 0.001). Dispersion of repolarization and mechanical dispersion remained unchanged. Corresponding electrophysiological and mechanical relationships were present at comparable paced heart rates. After rewarming, the increased electromechanical window was reversed in the presence of both spontaneous and paced heart rates. Moderate hypothermia increased electromechanical window positivity, while dispersion of repolarization and mechanical dispersion remained unchanged. This impact of hypothermia may be clinically relevant for selected groups of patients after cardiac arrest.

Spatiotemporal approximation of cardiac activation and recovery isochrones

BACKGROUND

The sequence of myocardial activation and recovery can be studied in detail by invasive catheter recordings of cardiac electrograms (EGMs), or noninvasive inverse reconstructions thereof with electrocardiographic imaging (ECGI). Local activation and recovery times are obtained from a unipolar EGM by the moment of maximum downslope of the QRS complex or maximum upslope of the T wave, respectively. However, both invasive and noninvasive recordings of intracardiac EGMs may suffer from noise and fractionation, making reliable detection of these deflections nontrivial.

METHODS

Here, we introduce a novel method that benefits from the spatial coupling of these processes, and incorporate not only the temporal EGM deflection, but also the spatial gradients. We validated this approach in computer simulations, in animal data with ECGI and invasive electrode recordings, and illustrated its use in a clinical case.

RESULTS

In the simulated data, the spatiotemporal approach was able to incorporate spatial information to better select the correct deflection in artificially fractionated EGMs and outperformed the traditional temporal-only method. In experimental data, the accuracy of time estimation from ECGI compared to invasive recordings significantly increased from R = 0.73 (activation) and R = 0.58 (recovery) with the temporal-only method to R = 0.79 (activation) and R = 0.72 (recovery) with the novel approach. Localization of the pacing origin of paced beats improved significantly from 36 mm mean error with the temporal-only approach to 23 mm with the spatiotemporal approach.

CONCLUSION

The spatiotemporal method to compute activation and recovery times from EGMs outperformed the traditional temporal-only approach in which spatial information was not taken into account.