Artificial intelligence-guided pulsed field ablation for persistent atrial fibrillation: automated peak frequency mapping predicts termination sites and durable rhythm control
摘要
Ablation outcomes in long-standing persistent atrial fibrillation (AF) remain limited by diffuse substrate. Although AI-guided spatiotemporal dispersion (STD) mapping identifies complex electrograms, specificity declines with increasing AF duration. Peak frequency (PF) mapping, derived from high-resolution near-field signals, may better pinpoint functionally critical sites.
ObjectiveTo determine whether PF combined with conduction velocity (CV) mapping improves localisation of AF termination sites during pulsed field ablation (PFA).
MethodsIn 28 patients with long-standing persistent AF, high-density left atrial mapping (> 30 000 points) was performed using a paddle‑shaped multielectrode mapping catheter and a contemporary electroanatomic mapping system. STD was annotated with VX1 AI; PF and CV maps were generated offline using omnipolar near-field technology. PF, CV, and voltage at termination (T) sites were compared with control sites; ROC analysis identified predictors of termination.
ResultsAF terminated in 18/28 patients (64%). Termination sites clustered in four regions (anteroseptal LA, anterior LA, inferior LA–CS, RSPV ridge). PF was markedly higher at T sites (389 ± 81 vs. 202 ± 51 Hz; P < 0.001) and showed excellent discrimination (AUC 0.96; ≥340 Hz: sensitivity 88%, specificity 90%), outperforming voltage (AUC 0.59). PF maxima colocalised with CV deceleration zones. At 12 months, arrhythmia recurrence was 18% overall (40% without vs. 5% with acute termination).
ConclusionPF mapping during ongoing AF reliably identifies functional substrate and termination sites during PFA, outperforming voltage and complementing AI-STD mapping. Integration of automated PF/CV analysis may enhance outcomes in long-standing persistent AF. Multicentre validation is warranted.