Atrial Periodic Source Spectrum from Preoperative Body Surface Potentials Predicts Long-term Recurrence of Atrial Fibrillation.

Abstract

About half of patients experience recurrence of atrial fibrillation (AF) within three to five years after a single catheter ablation procedure. The suboptimality of the long-term outcomes likely results from the inter-patient variability of AF mechanisms, which can be remedied by improved patient screening. We aim to improve the interpretation of body surface potentials (BSPs), such as 12-lead electrocardiograms and 252-lead BSP maps, to aid preoperative patient screening. We developed the Atrial Periodic Source Spectrum (APSS), a novel patient-specific representation based on atrial periodic content, computed on the f-wave segments of patient BSPs, using a second-order blind source separation and a Gaussian Process for regression. With follow-up data, Cox's proportional hazard model was used to select the most relevant feature from preoperative APSSs responsible for AF recurrence. Over 138 persistent AF patients, the presence of highly periodic content with cycle lengths between 220-230 ms or 350-400 ms indicates higher risks of 4-year post-ablation AF recurrence (log-rank test, p-value ). Preoperative BSPs demonstrate effective prediction in the long-term outcomes, highlighting their potential for patient screening in AF ablation therapy.