Abstract
Fibrosis in atrial tissue can act as a substrate for persistent atrial fibrillation, and can be focal or diffuse. Regions of fibrosis are associated with slowed or blocked conduction, and several approaches have been used to model these effects. In this study a computational model of 2D atrial tissue was used to investigate how the spatial scale of regions of simulated fibrosis influenced the dispersion of action potential duration (APD) and vulnerability to re-entry in simulated normal human atrial tissue, and human tissue that has undergone remodeling as a result of persistent atrial fibrillation. Electrical activity was simulated in a 10 × 10 cm square 2D domain, with a spatially varying diffusion coefficient as described below. Cellular electrophysiology was represented by the Courtemanche model for human atrial cells, with the model parameters set for normal and remodeled cells. The effect of fibrosis was modeled with a smoothly varying diffusion coefficient, obtained from sampling a Gaussian random field (GRF) with length scales of between 1.25 and 10.0 mm. Twenty samples were drawn from each field, and used to allocate a value of diffusion coefficient between 0.05 and 0.2 mm2/ms. Dispersion of APD was assessed in each sample by pacing at a cycle length of 1,000 ms, followed by a premature beat with a coupling interval of 400 ms. Vulnerability to re-entry was assessed with an aggressive pacing protocol with pacing cycle lengths decreasing from 450 to 250 ms in 25 ms intervals for normal tissue and 300–150 ms for remodeled tissue. Simulated fibrosis at smaller spatial scales tended to lengthen APD, increase APD dispersion, and increase vulnerability to sustained re-entry relative to fibrosis at larger spatial scales. This study shows that when fibrosis is represented by smoothly varying tissue diffusion, the spatial scale of fibrosis has important effects on both dispersion of recovery and vulnerability to re-entry.
Highlights
Atrial fibrillation (AF) is a common cardiac arrhythmia, the mechanisms that initiate and sustain it are complex and remain incompletely understood
Fibrosis is hard to study in experimental preparations because it is difficult to control the extent of fibrosis and the size of individual lesions, and so computational models of cardiac cell and tissue electrophysiology have been used to examine how regions of simulated fibrosis affect activation and recovery in cardiac tissue, as well as vulnerability to arrhythmias (Trayanova et al, 2014)
The effect of spatial scale of fibrosis has been investigated in simulations where fibrosis was represented as regions of uncoupled and inexcitable ventricular tissue; this study found that an increasing amount of fibrosis and increasing spatial scale both acted to increase vulnerability to arrhythmia (Kazbanov et al, 2016)
Summary
Atrial fibrillation (AF) is a common cardiac arrhythmia, the mechanisms that initiate and sustain it are complex and remain incompletely understood. When regions of fibrosis are represented as inexcitable obstacles, diffuse fibrosis can act to slow activation and to destabilize re-entry in simulated ventricular tissue (Ten Tusscher and Panfilov, 2007). This approach was extended by representing fibroblasts as coupled elements with a fixed resting potential instead of inexcitable regions, and similar effects were found (Majumder et al, 2012). The electrotonic effect of regions of fibrosis was studied using a coupled and detailed fibroblast model to demonstrate that the effect of fibroblasts could underlie the complex fractionated electrograms often seen in persistent atrial fibrillation (Ashihara et al, 2012)
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