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Background Patients with type 2 diabetes mellitus (T2DM) are highly susceptible to cardiovascular disease, and coronary artery disease (CAD) is their leading cause of death. We aimed to assess whether computed tomography (CT) based imaging parameters and radiomic features of pericoronary adipose tissue (PCAT) can improve the diagnostic efficacy of whether patients with T2DM have developed CAD. Methods We retrospectively recruited 229 patients with T2DM but no CAD history (146 were diagnosed with CAD at this visit and 83 were not). We collected clinical information and extracted imaging manifestations from CT images and 93 radiomic features of PCAT from all patients. All patients were randomly divided into training and test groups at a ratio of 7:3. Four models were constructed, encapsulating clinical factors (Model 1), clinical factors and imaging indices (Model 2), clinical factors and Radscore (Model 3), and all together (Model 4), to identify patients with CAD. Receiver operating characteristic curves and decision curve analysis were plotted to evaluate the model performance and pairwise model comparisons were performed via the DeLong test to demonstrate the additive value of different factors. Results In the test set, the areas under the curve (AUCs) of Model 2 and Model 4 were 0.930 and 0.929, respectively, with higher recognition effectiveness compared to the other two models (each p < 0.001). Of these models, Model 2 had higher diagnostic efficacy for CAD than Model 1 (p < 0.001, 95% CI [0.129–0.350]). However, Model 4 did not improve the effectiveness of the identification of CAD compared to Model 2 (p = 0.776); similarly, the AUC did not significantly differ between Model 3 (AUC = 0.693) and Model 1 (AUC = 0.691, p = 0.382). Overall, Model 2 was rated better for the diagnosis of CAD in patients with T2DM. Conclusions A comprehensive diagnostic model combining patient clinical risk factors with CT-based imaging parameters has superior efficacy in diagnosing the occurrence of CAD in patients with T2DM.

Background: Pericoronary adipose tissue (PCAT) around the proximal right coronary artery (RCA) is considered a marker of coronary inflammation. We aimed to explore the segments of PCAT that represent coronary inflammation in patients with acute coronary syndrome (ACS) and to identify patients with ACS and stable coronary artery disease (CAD) prior to intervention. Methods:We retrospectively enrolled consecutive patients with ACS and stable CAD who underwent invasive coronary angiography (ICA) after coronary computed tomography angiography (CCTA) from November 2020 to October 2021 at the Fourth Affiliated Hospital of Harbin Medical University. The fat attenuation index (FAI) was obtained using PCAT quantitative measurement software, and the coronary Gensini score was also calculated to indicate the severity of CAD. The differences and correlations between FAI within different radial distances of proximal coronary arteries were evaluated, and the recognition ability of FAI for patients with ACS and stable CAD was evaluated by establishing receiver operator characteristic (ROC) curves.Results: A total of 267 patients were included in the cross-sectional study, including 173 patients with ACS. With the increase of radial distance from the outer wall of proximal coronary vessels, the FAI decreased (P<0.001). The FAI around the proximal left anterior descending artery (LAD) within the reference diameter from the outer wall of the vessel (LAD_ref) had the highest correlation with the FAI around culprit lesions [r=0.587; 95% confidence interval (CI): 0.489-0.671; P<0.001]. The model based on clinical features, Gensini score, and LAD_ref had the highest recognition performance for patients with ACS and stable CAD [area under the curve (AUC): 0.663; 95% CI: 0.540-0.785].

Background The differences in fat deposition sites exhibit varying degrees of systemic inflammatory responses and organ damage, especially in obese individuals with excessive visceral fat. Visceral fat, which is closely related to an increase in mortality rates related to heart and liver diseases. However, few studies have analysed the differences in heart and liver indicators and their correlation among groups based on the abdominal visceral fat area (AVFA). Objective Clarifying the differences in and correlations of heart and liver indicators among groups with different severities of AVFA by magnetic resonance imaging (MRI). Methods Sixty-nine subjects with obesity were enrolled. The study group consisted of forty-one individuals (AVFA ≥ 150 cm2), and the control group consisted of twenty-eight individuals (100 cm2 ≤ AVFA < 150 cm2). The differences in and correlations between clinical, laboratory, and MRI indicators of the heart and liver between the two groups were analysed. Results In the study group, the incidences of type 2 diabetes mellitus (T2DM) and insulin resistance were higher, and liver function indicators were worse. The left ventricular eccentricity ratio (LVER), left ventricular mass (LVM) and global peak wall thickness (GPWT) were higher in the study group than in the control group (P = 0.002, P = 0.001, P = 0.03), and the left ventricle global longitudinal strain (LVGLS) was lower in the study group than in the control group (P = 0.016). The pericardiac adipose tissue volume (PATV) and myocardial proton density fat fraction (M-PDFF) were higher in the study group than in the control group (P = 0.001, P = 0.001). The hepatic proton density fat fraction (H-PDFF) and abdominal subcutaneous fat area (ASFA) were higher in the study group than in the control group (P < 0.001, P = 0.012). There was a moderate positive correlation (ρ = 0.39–0.59, P < 0.001) between the AVFA and LVER, LVM, GPWT, LVGLS, and H-PDFF. There was no difference in right ventricular and most left ventricular systolic and diastolic function between the two groups. Conclusion The high AVFA group had a larger LVM, GPWT and PATV, more obvious changes in LVER, impaired left ventricular diastolic function, an increased risk of heart disease, and more severe hepatic fat deposition and liver injury. Therefore, there is a correlation between the amount of visceral adipose tissue and subclinical cardiac changes and liver injury.

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