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J Interv Card Electrophysiol ; 64(1): 39-47, 2022 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-34382153

RESUMEN

PURPOSE: Atrial fibrillation (AF) ablation requires a precise reconstruction of the left atrium (LA) and pulmonary veins (PV). Model-based FAM (m-FAM) is a novel module recently developed for the CARTO system which applies machine learning techniques to LA reconstruction. We aimed to evaluate the feasibility and safety of a m-FAM-guided AF ablation as well as the accuracy of LA reconstruction using the cardiac computed tomography angiography (CTA) of the same patient LA as the gold standard, in 32 patients referred for AF ablation. METHODS: Consecutive patients undergoing AF ablation. The m-FAM reconstruction was performed with the ablation catheter (group 1) or a Pentaray and ablation catheters (group 2). The reconstruction accuracy was confirmed prior to the ablation by verification of pre-specified landmarks of the LA and PVs by an intracardiac echocardiogram (ICE) visualization and fluoroscopy. A cardiac CTA performed before the ablation was used as the gold standard of LA anatomy. For each patient, the m-FAM reconstruction was compared to his/her cardiac CTA. RESULTS: The m-FAM reconstruction was accurate in all patients regardless of the catheter used for mapping. Twelve percent re-acquisition of the LA landmarks was necessary to improve the accuracy. m-FAM time was shorter in group 2 while the M-Fam fluoroscopy time was similar. Pulmonary vein isolation was achieved in 100% of patients without major complications. The m-FAM reconstructions accurately resemble the cardiac CTA of the same patients. CONCLUSIONS: The m-FAM module allows for rapid and precise reconstruction of the LA and PV anatomy, which can be safely used to guide AF ablation.


Asunto(s)
Fibrilación Atrial , Ablación por Catéter , Venas Pulmonares , Fibrilación Atrial/diagnóstico por imagen , Fibrilación Atrial/cirugía , Ablación por Catéter/métodos , Femenino , Atrios Cardíacos/diagnóstico por imagen , Atrios Cardíacos/cirugía , Humanos , Aprendizaje Automático , Masculino , Venas Pulmonares/diagnóstico por imagen , Venas Pulmonares/cirugía , Programas Informáticos , Resultado del Tratamiento
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