Multiscale human-based computer modelling and simulation for investigations of arrhythmic risk in acute ischemia

Acute myocardial ischemia is a major cause of sudden arrhythmic death. Variability in ischemic extent and location hampers the understanding of arrhythmic mechanisms and challenges risk diagnosis, stratification and treatment. Moreover, co-existent alterations in ionic channels have been proven to affect ischemia-induced arrhythmogenesis. Ischemic patients with alterations in the sodium (Na+) current availability due to SCN5A mutations, such as Brugada syndrome, are particularly prone to develop cardiac events. Low Na+ current availability can also be acquired with the use of pharmacological treatments. For instance, flecainide is a Na+ channel blocker commonly used for treating atrial fibrillation, but its effects have been proven to increase mortality among ischemic patients, as observed in the CAST trials. Although electrophysiological abnormalities caused by ischemia have been extensively investigated, the mechanisms linking such changes to high arrhythmic risk remain poorly understood. The use of in silico trials provides an alternative and high-resolution method to investigate ischemia-induced arrhythmogenesis, which overcomes ethical and technological restrictions linked to experiments. Computer simulations also allow considering variability both in ionic conditions and ischemic regions, providing a comprehensive and controlled approach for the investigations on arrhythmogenesis in acute myocardial ischemia. Thereby, I aim to investigate variability in arrhythmic risk and ECG abnormalities using a modelling and simulation framework constructed using extensive clinical and experimental data. Firstly, I present the construction and validation process of the computational framework for simulating acute myocardial ischemia. Secondly, I analyse the effects of size, transmural extent and location of myocardial ischemia on arrhythmogenesis and ECG. Then, I investigate the effects of changes in Na+ current variability on ischemia-induced arrhythmic risk. In this thesis, I construct a computational framework for simulating acute myocardial ischemia. The simulation pipeline is used for providing mechanistic evidence on ischemia-induced arrhythmogenesis in the context of clinical findings reported in the literature. A thorough analysis of the pro-arrhythmic mechanisms induced by ischemia is expected to provide new insights for formulating effective new anti-arrhythmic therapies.