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.

Aim: To assess the efficacy of the TriGUARD 3™, a novel cerebral embolic protection (CEP) device in reducing cerebral embolization by deflecting embolic debris away from the cerebral circulation using a quantitative in vitro model. Methods and Results: This in vitro study assessed the ability of a cerebral embolic protection device to deflect embolic debris, by measuring the percent of particles and air bubbles, 200 µm and 300 µm in size, from entering the cerebral circulation compared to unprotected controls. A 3D printed silicone model of the ascending aorta, the aortic arch with its three major cerebral arteries and the descending aorta was connected to a custom-made simulator that mimics physiological pulsatile flow patterns of the left ventricle. Comparative analyses were used to assess the efficacy of the cerebral embolic protection device to deflect particles and air bubbles away from the major cerebral arteries. The percent of particles and air bubbles entering the major cerebral arteries was significantly lower with cerebral embolic protection compared to unprotected controls (p<0.0001). Cerebral protection resulted in 97.4-100% reduction in air bubble counts, and 97.4-97.8% reduction in particle counts compared to unprotected controls. Conclusion: This in vitro study used simulated physiologic flow conditions in an aortic arch model to demonstrate >97% efficacy of the TriGUARD 3 CEP device, in reducing cerebral embolization of particulate and air bubbles of 200 µm to 300 µm in size.

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