Estimating the probabilities of rare arrhythmic events in multiscale computational models of cardiac cells and tissue

Ectopic heartbeats can trigger reentrant arrhythmias, leading to ventricular fibrillation and sudden cardiac death. Such events have been attributed to perturbed Ca2+ handling in cardiac myocytes leading to spontaneous Ca2+ release and delayed afterdepolarizations (DADs). However, the ways in which perturbation of specific molecular mechanisms alters the probability of ectopic beats is not understood. We present a multiscale model of cardiac tissue incorporating a biophysically detailed three-dimensional model of the ventricular myocyte. This model reproduces realistic Ca2+ waves and DADs driven by stochastic Ca2+ release channel (RyR) gating and is used to study mechanisms of DAD variability. In agreement with previous experimental and modeling studies, key factors influencing the distribution of DAD amplitude and timing include cytosolic and sarcoplasmic reticulum Ca2+ concentrations, inwardly rectifying potassium current (IK1) density, and gap junction conductance. The cardiac tissue model is used to investigate how random RyR gating gives rise to probabilistic triggered activity in a one-dimensional myocyte tissue model. A novel spatial-average filtering method for estimating the probability of extreme (i.e. rare, high-amplitude) stochastic events from a limited set of spontaneous Ca2+ release profiles is presented. These events occur when randomly organized clusters of cells exhibit synchronized, high amplitude Ca2+ release flux. It is shown how reduced IK1 density and gap junction coupling, as observed in heart failure, increase the probability of extreme DADs by multiple orders of magnitude. This method enables prediction of arrhythmia likelihood and its modulation by alterations of other cellular mechanisms.Author summary: Arrhythmias are electrical abnormalities of the heart that can degenerate into fibrillation, thus preventing normal heartbeats and leading to sudden cardiac death. The mechanisms leading to ventricular arrhythmias and the unexpected nature of sudden cardiac death are not fully understood. One hypothesis is that a group of cardiac myocytes, which generate contraction, spontaneously depolarize at precisely the same moment to excite the surrounding tissue. In individual myocytes, such misfires, known as delayed afterdepolarizations, are driven by random ion channel gating and thus stochastic in nature. While incidental afterdepolarizations in a large number of myocytes is highly improbable on any given beat, it may be feasible over a long time frame, thus explaining the unpredictability of arrhythmias. We developed a detailed model spanning the molecular, cellular, and tissue scales that realistically reproduces the mechanisms underlying this hypothesis. An efficient method is presented for estimating the probability of extremely rare delayed afterdepolarizations in tissue from a limited set of simulations. Furthermore, we demonstrate how altered tissue and ion channel properties in heart disease increase the risk of arrhythmia. This approach can be used generally to probe the effects of specific molecular mechanisms on the likelihood of rare delayed afterdepolarizations.