Abstract

Background Despite the high success rate of radiofrequency catheter ablation (RFCA) in Wolff-Parkinson-White Syndrome (WPW), localizing the successful ablation site can be challenging and may require multiple radiofrequency (RF) applications. Objective This study aims to evaluate the efficacy of a novel workflow for the automatic and precise identification of accessory pathway ablation site, named Delta Wave Automatic Mapping. Methods Patients undergoing a first procedure for RF ablation of a manifest accessory pathway were included. Electro-Anatomical Mapping (EAM) was performed with the CARTO 3 system (Biosense Webster, Johnson & Johnson Medical S.p.a., Irvine, CA) leveraging auto-acquisition algorithms already present in the CARTO 3 software. Mapping and ablation were performed with an irrigated tip catheter with contact force sensor. Procedure success was defined as loss of pathway function after ablation. The number of RF applications required and time to effect were measured for each patient. Recurrences were evaluated during follow-up visits. Additionally, at the end of each procedure, historical predictors of ablation success were measured offline to evaluate their relationship with the successful ablation site found with the novel workflow. Results A total of 50 patients were analysed (62% APs right and 38% APs left). All 50 APs were successfully eliminated in each procedure with a median Time-to-effect (TTE) of 2.0 (IQR 1.2–3.5) seconds. No AP recurrences during a median follow-up of 10 (IQR 6–13) months were recorded. Offline analysis of successful ablation site revealed a pre-ablation delta/ventricular interval of ≤−10 msec in 52% of the patients and in 100% of the patients the signal related to the Kent bundle was identified. Conclusions The novel workflow efficiently localizes APs without requiring manual annotations. Historical endocardial parameters predicting success were measured offline for each case and they corresponded to the ablation target automatically annotated by the proposed workflow. This novel mapping workflow holds promise in enhancing the efficacy of RFCA in the presence of manifest APs.