Optimized Reconstruction Algorithm-Processed CT Image in the Diagnosis of Correlation between Epicardial Fat Volume and Coronary Heart Disease

This study was to analyze the application value of a reconstruction algorithm in CT images of patients with coronary heart disease and analyze the correlation between epicardial fat volume and coronary heart disease. An optimized reconstruction algorithm was constructed based on compressed sensing theory in this study. Then, the optimized algorithm was applied to the image reconstruction of multislice spiral CT image data after testing its sensitivity, accuracy, and specificity. 60 patients with suspected angina pectoris were divided into lesion group (40 cases) and normal group (20 cases) according to whether there were coronary atherosclerotic plaques in cardiac vessels. The results showed that the sensitivity, specificity, and accuracy of the optimized reconstruction algorithm were 91.78%, 84.27%, and 95.32%, and the running time was (12.18 ± 2.49) s. The CT value of the liver and the CT ratio of the liver and spleen in the lesion group were (53.81 ± 5.91) and (3.88 ± 0.67), respectively. There was no significant difference between the two groups ( P > 0.05 ). The body mass index and epicardial fat volume in the lesion group were (31.93 ± 4.54) kg/m2 and (120.09 ± 22.01) cm3, respectively. The body mass index and fat volume in the lesion group were significantly higher than those in the normal group ( P < 0.05 ). The epicardial fat constitution increased with the increase of the number of coronary arteries involved, and there was a positive correlation between them. Among patients with different coronary atherosclerotic plaques, the epicardial fat volume in patients with mixed plaques was the largest ( P < 0.05 ). In summary, optimizing CT images under compressed a sensing reconstruction algorithm could effectively improve the diagnostic accuracy of doctors. Epicardial fat volume was positively correlated with coronary heart disease. Epicardial fat volume could be used as one of the important indexes to predict coronary heart disease.

Epicardial fat volume is associated with preexisting atrioventricular conduction abnormalities and increased pacemaker implantation rate in patients undergoing transcatheter aortic valve implantation

Epicardial fat tissue (EFT) is a highly metabolically active fat depot surrounding the heart and coronary arteries that is related to early atherosclerosis and adverse cardiac events. We aimed to investigate the relationship between the amount of EFT and preexisting cardiac conduction abnormalities (CCAs) and the need for new postinterventional pacemaker in patients with severe aortic stenosis planned for transcatheter aortic valve implantation (TAVI). A total of 560 consecutive patients (54% female) scheduled for TAVI were included in this retrospective study. EFT volume was measured via a fully automated artificial intelligence software (QFAT) using computed tomography (CT) performed before TAVI. Baseline CCAs [first-degree atrioventricular (AV) block, right bundle branch block (RBBB), and left bundle branch block (LBBB)] were diagnosed according to 12-lead ECG before TAVI. Aortic valve calcification was determined by the Agatston score assessed in the pre-TAVI CT. The median EFT volume was 129.5 ml [IQR 94–170]. Baseline first-degree AV block was present in 17%, RBBB in 10.4%, and LBBB in 10.2% of the overall cohort. In adjusted logistic regression analysis, higher EFT volume was associated with first-degree AV block (OR 1.006 [95% CI 1.002–1.010]; p = 0.006) and the need for new pacemaker implantation after TAVI (OR 1.005 [95% CI 1.0–1.01]; p = 0.035) but not with the presence of RBBB or LBBB. EFT volume did not correlate with the Agatston score of the aortic valve. Greater EFT volume is associated independently with preexisting first-degree AV block and new pacemaker implantation in patients undergoing TAVI. It may play a causative role in degenerative processes and the susceptibility of the AV conduction system.

Predictors of Epicardial Fat Volume Decrease after Dapagliflozin Treatment in Patients with Type 2 Diabetes

Background and Objectives: Dapagliflozin treatment proved to reduce the epicardial fat volume (EFV) in patients with type 2 diabetes (T2D). Despite the reduction in EFV being associated with improved diastolic function in patients with T2D, EVF is not routinely evaluated in T2D because it is costly and involves radiation exposure. This study aims to identify biomarkers that predict EFV reduction after dapagliflozin treatment in patients with T2D. Materials and Methods: In a prospective, observational, consecutive-case enrollment scenario, 52 patients with T2D were initiated on dapagliflozin 10 mg q.d. as part of the standard of care. At enrollment and after six months of dapagliflozin treatment, patients were evaluated using cardiac ultrasonography, native computer tomography, transient liver elastography, and metabolic lab tests. In addition, the atherogenic index of plasma (AIP), atherogenic coefficient (AC), triglyceride glucose index (TyG), cardiac risk ratio (CRR), and visceral abdominal index (VAI) were calculated. Results: Higher AIP (r = 0.28; p = 0.04), CRR (r = 0.28; p = 0.04), and TyG (r = 0.32; p = 0.01) are associated with more important reductions in the EFV. A lower conicity index (β = −0.29; p = 0.03), visceral fat volume at the 4th vertebrae (L4VFV) (β = −0.32; p = 0.02), left atrium volume (β = −3.08; p = 0.003), and right ventricle diameter (β = −2.13; p = 0.04) are associated with higher reductions in the EFV after six months of dapagliflozin treatment. A valid performance for predicting clinically relevant decreases in EFV after dapagliflozin treatment was observed for AIP (AUROC = 0.903; Youden = 0.732; p < 0.001), CRR (AUROC = 0.772; Youden = 0.595; p = 0.004), TyG (AUROC = 0.957; Youden = 0.904; p < 0.001), and VAI (AUROC = 0.898; Youden = 0.712; p < 0.001). Conclusion: Higher initial EFV values are associated with more important reductions in EFV in patients with T2D treated for six months with dapagliflozin. TyG values have the best prediction performances for EFV reduction, having the highest sum of sensitivity and specificity at the 0.904 threshold level. AIP, CRR, VAI, conicity index, L4VF, left atrium volume, and right ventricle volume are valid biomarkers for a decrease in EFV after dapagliflozin treatment in diabetes patients.

A 3D deep learning approach to epicardial fat segmentation in non-contrast and post-contrast cardiac CT images

Epicardial fat (ECF) is localized fat surrounding the heart muscle or myocardium and enclosed by the thin-layer pericardium membrane. Segmenting the ECF is one of the most difficult medical image segmentation tasks. Since the epicardial fat is infiltrated into the groove between cardiac chambers and is contiguous with cardiac muscle, segmentation requires location and voxel intensity. Recently, deep learning methods have been effectively used to solve medical image segmentation problems in several domains with state-of-the-art performance. This paper presents a novel approach to 3D segmentation of ECF by integrating attention gates and deep supervision into the 3D U-Net deep learning architecture. The proposed method shows significant improvement of the segmentation performance, when compared with standard 3D U-Net. The experiments show excellent performance on non-contrast CT datasets with average Dice scores of 90.06%. Transfer learning from a pre-trained model of a non-contrast CT to contrast-enhanced CT dataset was also performed. The segmentation accuracy on the contrast-enhanced CT dataset achieved a Dice score of 88.16%.

May hepatic steatosis be associated with gynecomastia and epicardial fat? A retrospective study of 599 male patients

Objective There is no study in the literature investigating the association of hepatic steatosis with both gynecomastia and epicardial fat thickness together. We aimed to determine the correlations between hepatic steatosis through liver density, gynecomastia and epicardial fat thickness in patients undergoing CT scans due to suspected COVID-19 symptoms. Methods A total of 599 male patients who underwent chest CT scans due to a presumed diagnosis of COVID-19 in our radiology clinic were included in the study. Patients’ age, diameters of the subareolar glandular tissues of the right and left breasts, the right retroareolar fatty tissue, liver and spleen density, epicardial fat thickness and biochemical parameters were recorded and analyzed. The laboratory analyses were performed according to the standard methods. Results The mean age of the patients was 47.21±15.00 years. The left subareolar tissue thickness and the right retroareolar fatty tissue thickness that are used to indicate the presence of gynecomastia were found to be significantly correlated with liver density in negative direction (r=-.137, p<0.001; r=-.172, p<0.001; respectively). Epicardial fat thickness was statistically significantly correlated with right subareolar tissue thickness (r=.085, p=0.037), left subareolar tissue thickness (r=.101, p=0.014) and right retroareolar fatty tissue thickness (r=.148, p<0.001). Conclusion The results of this study showed that gynecomastia was significantly correlated with both age and hepatic steatosis. Epicardial fat thickness was also associated with liver steatosis. We demonstrated the significant correlations between epicardial fat thickness and gynecomastia for the first time. Nevertheless, our results need to be confirmed by further comprehensive studies.