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Atrial fibrillation ablation using three-dimensional artificial intelligence module integration with intracardiac echocardiography

Year: 2026
Type: article
Abstract: AIMS: Intracardiac echocardiography-based electroanatomical mapping (EAM) improves procedural efficiency and safety in atrial fibrillation (AF) ablation and remains the standard of care. The CARTOSOUND FAM (AI FAM) module uses a deep-learning algorithm that automates left atrial reconstruction without manual contouring. This study aims to evaluate the 1-year outcomes of AI FAM compared to standard-of-care EAM in AF ablation. METHODS AND RESULTS: This study included 298 patients undergoing radiofrequency AF ablation between January 2021 and December 2023. Patients treated before January 2023 underwent standard-of-care EAM, while those in 2023 utilized AI FAM-based reconstruction. Baseline demographics, comorbidities, AF type, and medication use were recorded. Procedural characteristics, acute success, complications, and AF recurrence at 1-year follow-up were analysed. Of the 298 patients, 115 underwent mapping with AI FAM and 183 with EAM. Baseline characteristics were comparable. AI FAM reduced mean total procedure time (122.5 ± 23.5 vs. 129.0 ± 30.4 min, P = 0.040) and left atrial (LA) dwell time (78.3 ± 21.45 vs. 87.5 ± 28.2 min, P = 0.001). Acute procedural success was 98.3% in AI FAM vs. 98.9% in EAM with fewer complications observed in the AI FAM group (1 vs. 4). At 1 year, freedom from AF recurrence was comparable (80.0% AI FAM vs. 81.4% EAM at 1 year, LogRank P = 0.610). CONCLUSION: AI FAM was associated with incremental but significant procedural advantages over conventional contouring via reduced total procedure time and LA dwell time, without compromising acute and long-term safety and rhythm control efficacy. AI FAM integration with pulsed field ablation will mark another step towards making AF ablation more streamlined and accessible.
Source: EP Europace
Language: English
Field: Medicine
Open Access status: hybrid
Estimated APC paid: $4,909
OpenAlex ID: W7124525522
FWCI: 13.89
Cites: 19
Cited by: 3
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