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.

Highly complex and irregular atrial activation patterns during atrial fibrillation (AF) can occasionally be interrupted by repetitive atrial activation patterns (RAAPs). These patterns are thought to be generated by mechanisms that initiate or maintain AF episodes are therefore, might be more diverse in patients with more complex forms of AF. We quantified RAAP diversity by the half decay time of the ratio of the unprecedented RAAPs to the total number of RAAPs in a goat model with different durations of sustained AF [3 weeks (3wkAF, n=8) and 22 weeks (22wkAF, n=8)]. 32 recordings from left and right atria (LA/RA) of each goat were analyzed. 24 out of 32 curves could be modeled as exponential decay functions with adjusted R-squared>0.75 while others presented more irregular decaying patterns (3wkAF LA:2 RA:3, 22wkAF LA:1 RA:2). Half decay rates were significantly shorter in LAs of 3wkAF goats (δ 3wkAF =23.67s vs. δ 22wkAF = 32.86s, p<0.05, Mann-Whitney U-test). There was no significant difference in RA.