Sensitivity analysis of cardiac alternans in electrophysiology cell models: A Monte Carlo filtering approach

Cardiac arrhythmias, and disruptions in normal heart rhythm, pose significant risks such as heart failure, ventricular fibrillation, and sudden cardiac death. A key marker of arrhythmias is electrical alternans, characterized by beat-to-beat variations in cardiac action potential duration or amplitude, detectable on electrocardiograms as T-wave alternations. Since these alternans often precede severe ventricular arrhythmias, their detection and understanding are critical for improving clinical outcomes. Recent studies focus on modeling electrical alternans to identify parameters influencing their occurrence. Ion channels, particularly the plateau calcium current, have been implicated in action potential duration (APD) alternations. Sensitivity analysis methods like Sobol indices and Monte Carlo Filtering (MCF) have been employed to assess parameter impacts, though their application in alternans studies remains limited. Computational challenges in complex models have prompted the use of Polynomial Chaos Expansion (PCE)-based emulators, which enhance analysis efficiency without sacrificing accuracy. This research investigates APD alternations in two cardiac models: the simplified modified Mitchell–Schaeffer model and the detailed ten Tusscher–Panfilov model. The proposed technique, which combines MCF and PCE emulators for sensitivity analysis, can effectively identify influential parameters driving alternans and enhance the understanding of cardiac electrophysiology, thereby contributing to the development of arrhythmia prevention strategies.