Computer Simulations of Composite Maps for Detection of Atrial Fibrillation Mechanisms

Localized AF drivers with repetitive activity are candidate ablation targets for patients with persistent atrial fibrillation (AF). High-density mapping electrodes cover only a fraction of the atria but combining sequential recordings could provide a more comprehensive picture of common repetitive atrial conduction characteristics and enable AF driver localization. We developed a novel algorithm to merge overlapping local activation maps into larger composite maps by linking repetitive patterns detected in neighboring locations with similar conduction directions and cycle lengths. Regions exhibiting high curl, divergence and heterogeneity in composite maps were marked as candidate reentry locations and were compared to those estimated through phase singularities and cycle length coverage maps from the individual recordings. The proposed algorithm led to better estimates of the underlying source density (sensitivity: 0.88/0.87/0.79, specificity: 0.85/0.85/0.68 for stable reentry, meandering reentry, and collision, respectively), compared to the maps from individual recordings (sensitivities 0.85/0.70/0.65 and 0.84/0.86/0.51, specificities 0.86/0.70/0.64 and 0.85/0.87/0.50 for phase singularity and CL coverage, respectively).