Computational models of the atria incorporating clinical imaging data and remodeling could serve as a first-line screening tool for new atrial fibrillation therapies, diagnostics, and prevention.
Computational models of the atria incorporating clinical imaging data hold promise as a screening tool for new atrial fibrillation therapies and diagnostic methods.
Atrial fibrillation (AF) is the most common sustained arrhythmia in humans. The mechanisms that govern AF initiation and persistence are highly complex, of dynamic nature, and involve interactions across multiple temporal and spatial scales in the atria. This article aims to review the mathematical modeling and computer simulation approaches to understanding AF mechanisms and aiding in its management. Various atrial modeling approaches are presented, with descriptions of the methodological basis and advancements in both lower-dimensional and realistic geometry models. A review of the most significant mechanistic insights made by atrial simulations is provided. The article showcases the contributions that atrial modeling and simulation have made not only to our understanding of the pathophysiology of atrial arrhythmias, but also to the development of AF management approaches. A summary of the future developments envisioned for the field of atrial simulation and modeling is also presented. The review contends that computational models of the atria assembled with data from clinical imaging modalities that incorporate electrophysiological and structural remodeling could become a first line of screening for new AF therapies and approaches, new diagnostic developments, and new methods for arrhythmia prevention.
Natalia A. Trayanova (Thu,) conducted a review in Atrial fibrillation. Mathematical modeling and computer simulation was evaluated. Computational models of the atria incorporating clinical imaging data and remodeling could serve as a first-line screening tool for new atrial fibrillation therapies, diagnostics, and prevention.