Patient-Directed Computational Analysis of Atrial Fibrillation

University Of California, San Diego, La Jolla CA

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Linked publications & trials

Abstract

Patient-Directed Computational Analysis of Atrial Fibrillation Project Summary Atrial fibrillation (AF) poses a significant and rapidly escalating health challenge, impacting over 5 million Americans and contributing to heightened risks of stroke, heart failure, and mortality. Despite extensive research efforts spanning decades, the precise mechanisms underlying AF remain incompletely understood, leading to suboptimal therapeutic interventions. Recent investigations, however, have shed light on the role of rotational or focal activity in driving AF, with targeted ablation of these sources showing promise for long-term outcomes. Yet, due to the complexity of AF and limitations in visualization, targeted ablation approaches do not consistently yield successful results. This project aims to advance our understanding of AF mechanisms and enhance therapeutic strategies for AF management. A key focus will be the development of a novel analysis technique capable of generating easily interpretable visual maps depicting the electrical activation patterns in AF patients. Leveraging a large and unique database of AF patient data, this technique will retrospectively analyze AF activity to elucidate how it is organized in these individuals. Additionally, extensive simulations will be conducted using patient-specific anatomical models to explore how atrial anatomy influences AF dynamics. The significance of this project lies in its potential to increase our understanding of AF and uncover novel mechanisms underlying AF maintenance. The insights gained can directly inform clinical practice and facilitate the development of more effective treatment options, ultimately improving outcomes for individuals with AF.