In-silico study of the cardiac arrhythmogenic potential of biomaterial injection therapy

Abstract

Biomaterial injection is a novel therapy to treat ischemic heart failure (HF) that has shown to reduce remodeling and restore cardiac function in recent preclinical studies. While the effect of biomaterial injection in reducing mechanical wall stress has been recently demonstrated, the influence of biomaterials on the electrical behavior of treated hearts has not been elucidated. In this work, we developed computational models of swine hearts to study the electrophysiological vulnerability associated with biomaterial injection therapy. The propagation of action potentials on realistic biventricular geometries was simulated by numerically solving the monodomain electrophysiology equations on anatomically-detailed models of normal, HF untreated, and HF treated hearts. Heart geometries were constructed from high-resolution magnetic resonance images (MRI) where the healthy, peri-infarcted, infarcted and gel regions were identified, and the orientation of cardiac fibers was informed from diffusion-tensor MRI. Regional restitution properties in each case were evaluated by constructing a probability density function of the action potential duration (APD) at different cycle lengths. A comparative analysis of the ventricular fibrillation (VF) dynamics for every heart was carried out by measuring the number of filaments formed after wave braking. Our results suggest that biomaterial injection therapy does not affect the regional dispersion of repolarization when comparing untreated and treated failing hearts. Further, we found that the treated failing heart is more prone to sustain VF than the normal heart, and is at least as susceptible to sustained VF as the untreated failing heart. Moreover, we show that the main features of VF dynamics in a treated failing heart are not affected by the level of electrical conductivity of the biogel injectates. This work represents a novel proof-of-concept study demonstrating the feasibility of computer simulations of the heart in understanding the arrhythmic behavior in novel therapies for HF.

On the Role of Ionic Modeling on the Signature of Cardiac Arrhythmias for Healthy and Diseased Hearts

“…Second, comparing linear, nonlinear, and fractional diffusion formulations would significantly help to identify the best computational approach to apply in subject-specific cardiac studies [10,[73][74][75]. Third, characterization of the border zone of the scar and gray zones in the infarcted myocardium is related to small-scale components [9,76] that are accurately modeled by detailed biophysical constitutive models reproducing modified ion channel dynamics (electrical remodeling). However, reduced-order models have been shown to provide a viable alternative also in this context [77].…”

“…Layers from Endo to Epi showed in the figure refer to the parametrization used in the TP06 model. The geometry and structural information of each heart is taken from our previous publication [9]. Structural differences due to pathological remodeling processes appear in fibers orientation and ventricular wall thickness, though the overall organs are volumetrically and morphology similar [54].…”

“…These advances are the result of the significant progress in cardiac cell modeling, corroborated with experimentation and clinical practice. Moreover, continuous increases in computational power have led to whole-heart electrical models that have shown promising translational outcomes, improving the general understanding of heart function, its pathologies, and therapies [4][5][6][7][8][9]. Still, critical modeling challenges arise when local heterogeneities at different spatio-temporal scales are taken into account [10][11][12][13][14][15][16].…”

“…Estimates of membrane potential and ionic currents distributions in the core region of a sinoatrial node reentry was obtained through detailed computer simulations [45]. Subject-specific whole-heart computational models explored arrhythmia risk-stratification in patients with myocardial infarction (MI) [9,46], and complex VF dynamics have also been characterized in terms of scroll wave filaments through detailed ventricular models [42]. Likewise, the study of AP vortex dynamics has been conducted via phenomenological descriptions in both simplified [47][48][49] and whole-heart simulations [50][51][52][53].…”

Precision medicine in human heart modeling

“…For electrophysiological simulations, where we are interested in extracting electrocardiograms under physiological and pathological conditions, we usually have to simulate both ventricles using anatomic biventricular models (Sahli Costabal et al 2016). Anatomic bi-ventricular models are also frequently used to simulate pressure-volume loops (Krishnamurthy et al 2013) or to predict realistic excitation patterns in response to different treatment scenarios (Ramírez et al 2020). The most complex models of the heart are undoubtedly anatomic whole heart models from real personalized geometries (Zygote 2014) that become unavoidable when studying the interaction between the atria and the ventricles, for example in all medical conditions that involve the valves.…”