High-density mapping of the average complex interval helps localizing atrial fibrillation drivers and predicts catheter ablation outcomes

Background: Persistent Atrial Fibrillation (PersAF) electrogram-based ablation is complex, and appropriate identification of atrial substrate is critical. Little is known regarding the value of the Average Complex Interval (ACI) feature for PersAF ablation.Objective: Using the evolution of AF complexity by sequentially computing AF dominant frequency (DF) along the ablation procedure, we sought to evaluate the value of ACI for discriminating active drivers (AD) from bystander zones (BZ), for predicting AF termination during ablation, and for predicting AF recurrence during follow-up.Methods: We included PersAF patients undergoing radiofrequency catheter ablation by pulmonary vein isolation and ablation of atrial substrate identified by Spatiotemporal Dispersion or Complex Fractionated Atrial Electrograms (>70% of recording). Operators were blinded to ACI measurement which was sought for each documented atrial substrate area. AF DF was measured by Independent Component Analysis on 1-minute 12-lead ECGs at baseline and after ablation of each atrial zone. AD were differentiated from BZ either by a significant decrease in DF (>10%), or by AF termination. Arrhythmia recurrence was monitored during follow-up.Results: We analyzed 159 atrial areas (129 treated by radiofrequency during AF) in 29 patients. ACI was shorter in AD than BZ (76.4 & PLUSMN; 13.6 vs. 86.6 & PLUSMN; 20.3 ms; p = 0.0055), and mean ACI of all substrate zones was shorter in patients for whom radiofrequency failed to terminate AF [71.3 (67.5-77.8) vs. 82.4 (74.4-98.5) ms; p = 0.0126]. ACI predicted AD [AUC 0.728 (0.629-0.826)]. An ACI < 70 ms was specific for predicting AD (Sp 0.831, Se 0.526), whereas areas with an ACI > 100 ms had almost no chances of being active in AF maintenance. AF recurrence was associated with more ACI zones with identical shortest value [3.5 (3-4) vs. 1 (0-1) zones; p = 0.021]. In multivariate analysis, ACI < 70 ms predicted AD [OR = 4.02 (1.49-10.84), p = 0.006] and mean ACI > 75 ms predicted AF termination [OR = 9.94 (1.14-86.7), p = 0.038].Conclusion: ACI helps in identifying AF drivers, and is correlated with AF termination and AF recurrence during follow-up. It can help in establishing an ablation plan, by prioritizing ablation from the shortest to the longest ACI zone.

Automated summary

By evaluating the value of ACI for discriminating AD from BZ and predicting AF termination and recurrence, this study found that ACI is helpful in identifying AF drivers and is correlated with AF termination and recurrence.