Spatiotemporal Behaviour of Human Persistent Atrial Fibrillation from Long-Duration Recordings

Identifying ablation targets in persistent atrial fibrillation (PersAF) remains challenging. This study aims to investigate the spatiotemporal stability of PersAF drivers within 5 min recordings of virtual atrial electrograms (VEGMs). 2048-channel VEGMs (EnSite Array, Abbott) were analysed for 5 patients undergoing substrate-guided ablation. Following QRST subtraction, dominant frequency (DF, 4–10 Hz) and organization index (OI) were identified using fast Fourier transform (4 s windows; 50% overlap). Areas with DF within 0.25 Hz below or equal the maximum out of the 2048 points were defined as the highest DF (HDF). Stable DFs (SDFs) were defined as DF patterns with the highest recurrence over consecutive time windows. Rotors were defined as phase singularities (PSs) with ≥100 ms. The 5 min VEGMs were divided into segments of 30, 60, 90, and 120 s. 2D correlation coefficients (CORR) was used to measure the similarity among maps (SDFs, DF selected by OI>0.3, HDF and Rotors) at different time segments. DF (OI>0.3) density maps were found to have the highest level of similarity over time, followed by Rotors, HDF, and SDFs. DF (OI>0.3) are the most spatially overlapped regions with the SDFs sites. Similarity and spatial overlapping of individual density maps increased with longer segments. There is spatial overlapping between PersAF drivers density maps, therefore investigate regions of overlapping might lead to better identification of substrate targets ablation for PersAF.