Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation

Abstract

The complexity of cardiac electrophysiology, involving dynamic changes in numerous components across multiple spatial (from ion channel to organ) and temporal (from milliseconds to days) scales makes an intuitive or empirical analysis of cardiac arrhythmogenesis challenging. Multiscale mechanistic computational models of cardiac electrophysiology provide precise control over individual parameters, and their reproducibility enables a thorough assessment of arrhythmia mechanisms. This review provides a comprehensive analysis of models of cardiac electrophysiology and arrhythmias. from the single cell to the organ level, and how they can be leveraged to better understand rhythm disorders in cardiac disease and to improve heart patient care. Key issues related to model development based on experimental data are discussed and major families of human cardiomyocyte models and their applications are highlighted. An overview of organ-level computational modeling of cardiac electrophysiology and its clinical applications in personalized arrhythmia risk assessment and patient-specific therapy of atrial and ventricular arrhythmias is provided. The advancements presented here highlight how patient-specific computational models of the heart reconstructed from patient clinical data have achieved success in predicting risk of sudden cardiac death and guiding optimal treatments of heart rhythm disorders. Finally, an outlook towards potential future advances, including the combination of mechanistic modeling and machine learning / artificial intelligence, is provided. As the field of cardiology is embarking on a journey towards precision medicine, personalized modeling of the heart is expected to become a key technology to guide pharmaceutical therapy, deployment of devices, and surgical interventions.

Digital twins for cardiac electrophysiology: state of the art and future challenges

“…Computer models of cardiac electrophysiology have been around for many decades and have grown increasingly sophisticated [15,28]. Several different types of computer models exist.…”

“…For example, computer models play a central role in modern safety assessment of new pharmacological agents through the comprehensive in vitro proarrhythmia assay (CiPA) initiative [14], thereby potentially influencing commercial decisions on compound selection. In recent years, several cardiomyocyte models based on data from non-diseased human hearts, as well as models representing specific pathologies such as hypertrophic cardiomyopathy, heart failure, or atrial fibrillation have been developed [28]. Since cardiac arrhythmias are intrinsically multi-cellular phenomena, these models have been employed in multi-scale organ-level simulations to study the determinants of arrhythmia initiation and stability [28].…”

“…In recent years, several cardiomyocyte models based on data from non-diseased human hearts, as well as models representing specific pathologies such as hypertrophic cardiomyopathy, heart failure, or atrial fibrillation have been developed [28]. Since cardiac arrhythmias are intrinsically multi-cellular phenomena, these models have been employed in multi-scale organ-level simulations to study the determinants of arrhythmia initiation and stability [28]. Since the early 2000s, organ-level models based on patient-specific anatomies have been developed [24] and have subsequently been further personalized with structural remodeling derived from non-invasive imaging data [2].…”

“…Previous studies have shown how patient-specific anatomies and structural remodeling (fibrosis) can be obtained from non-invasive imaging [2]. Here, personalization typically entails creating a 3D mesh of a patient's heart from imaging, including regions of scar and border zone, and using a computational electrophysiology model that includes pre-defined parameters for scar tissue, border zone tissue, and healthy tissue [28].…”

“…Naturally, if one can predict the occurrence of arrhythmias, one can also evaluate how electrophysiological changes would modulate this inducibility, providing patient-specific treatment guidance. This has been done in retrospective studies for catheter ablation of infarct-related ventricular tachycardia [4,22] and persistent AF [17], as well as inherited arrhythmia syndromes [28,29] and resynchronization therapy [20].…”