Patient-Tailored in Silico 3D Simulations and Models from Electroanatomical Maps of the Left Atrium

Abstract

The mechanisms underlying atrial fibrillation (AF) are still under debate, making treatments for this arrhythmia remain suboptimal, with most treatments applied in a standard fashion with no patient personalization. Recent technological advances in electroanatomical mapping (EAM) using multi-electrode catheter allow the physicians to better characterize the substrate, thanks to a better spatial resolution and higher density of acquisition points. Taking advantage of this technology, we describe a workflow to build personalized electrophysiological atrial models for AF patients. We seek to better predict the outcome of a treatment and study the AF problem in a more specific scenario. We generated physiological 3D models from the EAM data using hexahedral meshing of element size 300μm, and added fiber orientation based on a generic model. We used the local activation time (LAT) maps performed in sinus rhythm (SR) to estimate the conduction velocity (CV) of the regions in the atrium with a new method that combines the LATs of neighboring tissue as the average CV of triplets of points. We also characterized the cellular model by Maleckar et al. in terms of longitudinal conductivity and CV to personalize the atrial models. We were able to simulate SR and AF scenarios on the personalized models, and we generated a database of atrial models for future analysis.