CAREER: Decoding Cardiac Arrhythmias: Integrating Multiphysics Simulations and Deep Learning Models to Uncover Multi-physical Contributions and Arrhythmia Initiation

Cardiovascular disease is a major health challenge in the US, affecting nearly half of the adult population. Cardiac arrhythmias are widespread threats, presenting a broad spectrum of conditions and life-threatening complications such as stroke and heart failure. In view of the health risks associated with cardiac arrhythmias, there is a strong need to develop more precise diagnostic tools and more effective therapeutic interventions.

This Faculty Early Career Development (CAREER) Program project aims to enhance the understanding of the mechanisms that drive cardiac arrhythmias, thereby improving both diagnosis and treatment effectiveness. The project integrates complex computational simulations of various physical phenomena with advanced deep-learning techniques to explore how multiple physiological factors within a human body can contribute to arrhythmias and their initiation mechanisms.

The research findings are seamlessly incorporated into educational activities, fostering a highly skilled healthcare workforce with an in-depth understanding of arrhythmia physiology and the cutting-edge methodologies developed in this study.

Current practices of understanding arrhythmia physiology primarily focus on electrical activity. For example, the diagnostic tool used to identify arrhythmias is the 12-lead electrocardiogram (ECG), which records the electrical signals of the heart projected onto the body surface. However, cardiac arrhythmias are complex conditions with multiple physical processes contributing to their initiation, maintenance, and progression.

For example, the malfunction of electrical impulses in arrhythmias initially disrupts the mechanical function of the heart muscles. Such mechanical dysfunction, in turn, impairs the heart’s ability to effectively maintain blood flow and pressure, thereby impacting fluid dynamics within the cardiovascular system. This research establishes a holistic research pathway to advance the understanding of arrhythmia physiology.

The first objective is to develop high-fidelity multiphysics simulations of cardiac arrhythmias, which simultaneously model the electrical, mechanical, and fluid dynamics, as well as their interdependencies. These simulations provide the foundation for the second objective, which investigates how these multi-physical processes contribute to arrhythmia conditions.

The third objective integrates insights from this project’s earlier phases and focuses on uncovering the mechanisms that initiate arrhythmias to advance knowledge of cardiac arrhythmias and support the development of more effective interventions for future research.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.