Automated generation of ablation lesion masks: a unison of electro and optic flow mapping for persistent AF virtual cohorts

Novel technologies and ablation techniques for identification of atrial fibrillation (AF) sources and personalized substrate modification may be required to improve outcomes for persistent AF. We hypothesize that a unison of electrophysiologic phase and optical flow mapping could be used to selectively prioritize ablation targets and optimize patient outcome while minimizing the tissue ablated. We aim to evaluate the efficacy of a novel electro-optic flow (EOF)-based ablation strategy for persistent AF patients using a virtual cohort of bi-atrial digital twins (DTs). A patient cohort (n=250) from a bi-atrial in silico population with different atrial fibrosis distributions was utilized to simulate five AF episodes per case. Phase singularity (PS) and average optical flow maps were computed for post-pulmonary vein isolation (PVI) sustained AF. Concordant regions, overlapping in at least three binarized PS maps were used to define regions to search for the highest optical curl cluster centroids as candidate EOF targets. Using optical curl as the weight, the centroid of five candidate EOF targets were computed and selected as an ablation target inside each concordant boundary. Six clinical ablation strategies were simulated. An inducibility-to-ablated tissue area metric was calculated to evaluate the efficacy of the tested ablation strategies. The pipeline automatically identified extra-PV targets and generated patient-specific EOF ablation plans. Electro-optic flow-guided ablations resulted in an average 32±2% AF inducibility, outperforming PVI (90±5%), and PVI+empiric (87±6%). Consensus-EOF further reduced inducibility to 20±5% while sparing 28±2% tissue as compared to PVI+PS ablation. Consensus mapping provides a novel method for assessing the dynamic nature of AF, while EOF offers a promising multimodal metric for identifying critical ablation targets outside of PVI. These findings underscore the potential of EOF-guided ablation planning in advancing the clinical translation of DT-based personalized therapy for PeAF patients.