Deep-Learning Segmentation of Epicardial Adipose Tissue Using Four-Chamber Cardiac Magnetic Resonance Imaging

In magnetic resonance imaging (MRI), epicardial adipose tissue (EAT) overload remains often overlooked due to tedious manual contouring in images. Automated four-chamber EAT area quantification was proposed, leveraging deep-learning segmentation using multi-frame fully convolutional networks (FCN). The investigation involved 100 subjects—comprising healthy, obese, and diabetic patients—who underwent 3T cardiac cine MRI, optimized U-Net and FCN (noted FCNB) were trained on three consecutive cine frames for segmentation of central frame using dice loss. Networks were trained using 4-fold cross-validation (n = 80) and evaluated on an independent dataset (n = 20). Segmentation performances were compared to inter-intra observer bias with dice (DSC) and relative surface error (RSE). Both systole and diastole four-chamber area were correlated with total EAT volume (r = 0.77 and 0.74 respectively). Networks’ performances were equivalent to inter-observers’ bias (EAT: DSCInter = 0.76, DSCU-Net = 0.77, DSCFCNB = 0.76). U-net outperformed (p < 0.0001) FCNB on all metrics. Eventually, proposed multi-frame U-Net provided automated EAT area quantification with a 14.2% precision for the clinically relevant upper three quarters of EAT area range, scaling patients’ risk of EAT overload with 70% accuracy. Exploiting multi-frame U-Net in standard cine provided automated EAT quantification over a wide range of EAT quantities. The method is made available to the community through a FSLeyes plugin.

Technique for detecting an electrical connection between the right atrium and right pulmonary venous carina

Introduction: There is increasing evidence of the epicardial connection between the right-sided pulmonary vein (PV) carina and right atrium interrupts right-sided PV isolation after circumferential PV ablation in patients with atrial fibrillation. In such cases, carina ablation is often required. This study aimed to assess the utility of the right atrial posterior wall (RAPW) pacing in the detection of the right-sided epicardial connection (EC), evaluate the requirement for additional carina ablation after circumferential pulmonary vein (PV) ablation depending on the presence of EC, and investigate the clinical characteristics including the amount of epicardial adipose tissue (EAT) in patients with ECs. Methods and Results: Forty-one patients scheduled for PV isolation were enrolled. Before ablation, activation mapping of the LA was prospectively performed during pacing from the RAPW. EC was observed in 12 patients (EC group, 29%), whereas no EC was observed in the remaining 29 patients (non-EC group, 71%). For PV isolation, carina ablation was required in addition to circumferential ablation in 7 patients (58%) in the EC group, compared to 2 patients (7%) in the non-EC group (p < 0.003). Periatrial and intercaval EAT volumes were significantly lower (12.8 ± 6.2 vs. 23.1 ± 13.9 ml/m , p < 0.02, and 1.1 ± 0.8 vs. 2.2 ± 1.6 ml/m , p< 0.02, respectively) and the patients were younger (66.5 ± 6.6 vs. 72.4 ± 8.3 years, p < 0.03) in the EC group than in the non-EC group. Conclusions: RAPW pacing revealed EC between the RA and right PV carina in nearly a quarter of the patients.