Investigating the Role of the Coronary Vasculature in the Mechanisms of Defibrillation

Abstract

Background The direct role of coronary vessels in defibrillation, although hypothesized to be important, remains to be elucidated. We investigate how vessel-induced virtual-electrode polarizations assist reentry termination. Methods and Results A highly anatomically-detailed rabbit ventricular slice bidomain computer model was constructed from 25μm MR data, faithfully representing both structural and electrical properties of blood vessels. For comparison, an equivalent simplified model with intramural cavities filled-in was also built. Following fibrillation induction, 6 initial states were selected and biphasic shocks (5–70V) applied using a realistic Implanted Cardioverter Defibrillator electrode configuration. A fundamental mechanism of biphasic defibrillation was uncovered in both models, involving successive break excitations (after each shock phase) emanating from opposing myocardial surfaces (in septum/LV), which rapidly closed-down excitable gaps. The presence of vessels accelerated this process, achieving more rapid and successful defibrillation: defibrillation failed in 5 cases (all due to initiation of new activity), compared to 8 with the simplified model (5/8 failures due to surviving activity). At stronger shocks, virtual-electrodes formed around vessels, rapidly activating intramural tissue due to break excitations, assisting the main defibrillation mechanism and eliminating all activity <15ms of shock-end in 60% of successful shocks (36% in simplified model). Subsequent analysis identified only vessels approximately >200um diameter participated via this mechanism. Consequently, wavefronts could survive intramurally in the simplified model, leading to reentry and shock-failure. Conclusions We provide new insight into defibrillation mechanisms by showing how intramural blood vessels facilitate more effective elimination of existing wavefronts, rapid closing-down of excitable gaps and successful defibrillation, and give guidance towards the required resolution of cardiac imaging and model generation endeavors for mechanistic defibrillation analysis.

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

“…The investigators found that applied shock resulted in the formation of VEPs at the boundaries between blood vessels and myocardium. The VEPs elicited the formation of wavefronts that propagated through excitable gaps and led to successful defibrillation (Bishop et al, 2012). …”

Biophotonic Modelling of Cardiac Optical Imaging

“…Application of similar techniques, suitably adapted for specific optical mapping setups, will allow the simulation of optical signals over the latest computational anatomical models, intramural cavities and all. An interesting first line of application of such models will be during defibrillation shocks due to the recent suggestion of the importance of 'virtual-electrode' formation around large subepicardial vessels (Bishop et al 2012;Luther et al 2012). It is thought that the interaction of photon scattering Fig.…”

Cardiac Arrhythmias: Mechanistic Knowledge and Innovation from Computer Models

“…For example, Bishop et al applied shocks to a very high-resolution (∼ 25 μm voxel size) image-based rabbit ventricular model; VEPs formed at the boundaries between blood vessels and myocardium [19], which gave rise to secondary sources that eliminated excitable gaps and led to successful defibrillation [23]. Simulations have also contributed to understanding of the process of defibrillation in hearts with myocardial ischemia and infarction [96,105,106], uncovering the role of electrophysiological and structural remodeling in the failure or success of the shock.…”

“…Simulations that require application of the bidomain formulation (e.g., defibrillation studies [23,44,96,97,116]) are more time-consuming than those in which the monodomain formulation is adequate. Mesh size varies dramatically depending on the size of the model and the resolution necessary to capture details relevant to phenomena of interest; this review discusses studies involving models with degrees of freedom (i.e., mesh nodes) ranging from hundreds of thousands [32,33,44,45,[104][105][106][107] to millions [19,[21][22][23][96][97][98] and even tens of millions [95]. At the cell level, ionic models that aim to represent different levels of detail vary considerably in terms of the size of the associated ODE system; for example, the Courtemanche human atrial model has 19 equations [43], the O'Hara human ventricular model has 43 [91], and the Sampson human Purkinje fiber model has 83 [108].…”