Europace. 2023 Jul 21:euad211. doi: 10.1093/europace/euad211. Online ahead of print.
ABSTRACT
BACKGROUND AND AIMS: Intracardiac echocardiography (ICE) is a useful but operator-dependent tool for left atrial (LA) anatomical rendering during atrial fibrillation (AF) ablation. The CARTOSOUND FAM Module, a new deep learning (DL) imaging algorithm, has the potential to overcome this limitation. This study aims to evaluate feasibility of the algorithm compared to cardiac computed tomography (CT) in patients undergoing AF ablation.
METHODS: In 28 patients undergoing AF ablation, baseline patient information were recorded and 3D shells of LA body and anatomical structures (LAA/LSPV/LIPV/RSPV/RIPV) were reconstructed using the DL algorithm. The selected ultrasound frames were gated to end-expiration and max LA volume. Ostial diameters of these structures and carina-to-carina distance between left and right pulmonary veins were measured and compared with CT measurements. Anatomical accuracy of the DL algorithm was evaluated by three independent electrophysiologists using a 3-anchor scale for LA anatomical structures and a 5-anchor scale for LA body. Ablation related characteristics were summarized.
RESULTS: The algorithm generated 3D reconstruction of LA anatomies and 2D contours overlaid on ultrasound input frames. Average calculation time for LA reconstruction was 65s. Mean ostial diameters and carina-to-carina distance were all comparable to CT without statistical significance. Ostial diameters and carina-to-carina distance also showed moderate to high correlation (r=0.52-0.75) except for RIPV (r=0.20). Qualitative ratings showed good agreement without between-rater differences. Average procedure time was 143.7±43.7min, with average RF time 31.6±10.2min. All patients achieved ablation success and no immediate complications were observed.
CONCLUSION: DL algorithm integration with ICE demonstrated considerable accuracy compared to CT and qualitative physician assessment. The feasibility of ICE with this algorithm can potentially further streamline AF ablation workflow.
PMID:37477946 | DOI:10.1093/europace/euad211
