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).