Atrial fibrillation driver identification through regional mutual information networks: a modeling perspective.

ABSTRACT:

Purpose

Effective identification of electrical drivers within remodeled tissue is a key for improving ablation treatment for atrial fibrillation. We have developed a mutual information, graph-based approach to identify and propose fault tolerance metric of local efficiency as a distinguishing feature of rotational activation and remodeled atrial tissue.

Methods

Voltage data were extracted from atrial tissue simulations (2D Karma, 3D physiological, and the Multiscale Cardiac Simulation Framework (MSCSF)) using multi-spline open and parallel regional mapping catheter geometries. Graphs were generated based on varied mutual information thresholds between electrode pairs and the local efficiency for each graph was calculated.

Results

High-resolution mapping catheter geome

SUBMITTER: Sha Q 

PROVIDER: S-EPMC9470649 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature