The role of transmural ventricular heterogeneities in cardiac vulnerability to electric shocks

Abstract

Transmural electrophysiological heterogeneities have been shown to contribute to arrhythmia induction in the heart; however, their role in defibrillation failure has never been examined. The goal of this study is to investigate how transmural heterogeneities in ionic currents and gap-junctional coupling contribute to arrhythmia generation following defibrillation strength shocks. This study used a 3D anatomically realistic bidomain model of the rabbit ventricles. Transmural heterogeneity in ionic currents and reduced sub-epicardial intercellular coupling were incorporated based on experimental data. The ventricles were paced apically, and truncated-exponential monophasic shocks of varying strength and timing were applied via large external electrodes. Simulations demonstrate that inclusion of transmural heterogeneity in ionic currents results in an increase in vulnerability to shocks, reflected in the increased upper limit of vulnerability, ULV, and the enlarged vulnerable window, VW. These changes in vulnerability stem from increased post-shock dispersion in repolarisation as it increases the likelihood of establishment of re-entrant circuits. In contrast, reduced sub-epicardial coupling results in decrease in both ULV and VW. This decrease is caused by altered virtual electrode polarisation around the region of sub-epicardal uncoupling, and specifically, by the increase in (1) the amount of positively polarised myocardium at shock-end and (2) the spatial extent of post-shock wavefronts.

The functional role of electrophysiological heterogeneity in the rabbit ventricle during rapid pacing and arrhythmias

“…Intrinsic electrophysiological heterogeneity was represented by modifying individual ionic currents based on both previous modeling studies (33, 43) and experimental data (23, 35, 36, 52). Specifically, maximum conductivities of the transient-outward current ( g tos and g tof ), the sodium current ( g Na ), and the rapid ( g Kr ) and slow ( g Ks ) delayed-rectifier potassium currents within the Mahajan-Shiferaw model were varied to define distinct endocardial, midmyocardial, and epicardial regions.…”

“…Specifically, maximum conductivities of the transient-outward current ( g tos and g tof ), the sodium current ( g Na ), and the rapid ( g Kr ) and slow ( g Ks ) delayed-rectifier potassium currents within the Mahajan-Shiferaw model were varied to define distinct endocardial, midmyocardial, and epicardial regions. The spatial distribution of intrinsic transmural heterogeneity in ionic currents for these specific regions was assigned relative thicknesses of 3:3:2, respectively, across the myocardial wall (33, 43). The septum was defined as part of the left ventricle (LV) with the right ventricle (RV) side of the septum defined as “epicardial” tissue (26).…”

Unstable QT Interval Dynamics Precedes Ventricular Tachycardia Onset in Patients With Acute Myocardial Infarction

“…24 In order to obtain an ECG consistent with the clinical signal, we included transmural heterogeneities in cellular properties 24 in the model ventricles. The spatial distribution of endo-, epicardial, and M-cells across the ventricular walls (Fig.2B) was implemented as in a previous study, 25 based on data by Drouin et al 26 …”

“…25 We refer to the simulated ECGs as pseudo-ECGs since the model ventricles were not surrounded by torso 25 (Fig.2A), as well as to distinguish them from the clinical minECGs. The model ECG leads were configured to simulate Lead II of the standard 12-lead ECG (Fig.2A).…”

Computational rabbit models to investigate the initiation, perpetuation, and termination of ventricular arrhythmia

“…Over the years, rabbit ventricular models of defibrillation have made significant contributions to understanding how defibrillation shocks interact with cardiac tissue (Aguel et al, 2003; Arevalo et al, 2007; Ashihara and Trayanova, 2004; Bourn et al, 2006; Hillebrenner et al, 2004; Maharaj et al, 2008; Maleckar et al, 2008; Meunier et al, 2002; Plank et al, 2008; Rodriguez et al, 2006; Rodriguez et al, 2005; Tandri et al, 2011; Trayanova et al, 1998). In particular, these models have been instrumental in the development of the virtual electrode polarization (VEP) theory for defibrillation (Efimov et al, 2000; Efimov et al, 1998; Trayanova et al, 1998).…”