High Coverage and High-Resolution Mapping of Repetitive Patterns During Atrial Fibrillation

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 using recurrence plots. The proposed algorithm was applied to atrial recordings in a goat model of AF (249-electrode mapping array, 2.4 mm inter-electrode distance, $n=16$). Sequential, overlapping recordings were generated by segmenting the mapping region into four spatially overlapping regions. Repetitive activation patterns were detected from recurrence plots generated from the recorded electrograms, and reconstructed with the proposed algorithm. Reconstruction quality was measured as the Pearson correlation between original and reconstructed activation patterns. The average correlation was 0.86. Among pattern properties, such as duration, area, complexity and cycle length, only duration was significantly correlated with the composite map quality ($r=0.126, p < 0.05$). The percentage of the cases where a composite map could be generated was 75.30% which was significantly higher for larger patterns ($p < 0.01$).