A Pericoronary Adipose Tissue Radiomics Signature Predicts Coronary Heart Disease Risk in Patients with Type 2 Diabetes

Medical (Radiology)

Background Patients with type 2 diabetes mellitus (T2DM) are extremely vulnerable to cardiovascular disease, with coronary artery disease (CAD) is being the leading cause of mortality among them. Our objective was to evaluate whether imaging parameters obtained from computed tomography (CT) and radiomic features of pericoronary adipose tissue (PCAT) can enhance the diagnostic accuracy in identifying CAD in T2DM patients. Objective To determine Radiomics of pericoronary adipose tissue on CT angiography predicts coronary heart disease in patients with type 2 diabetes mellitus. Methods A cross-sectional study was conducted at the first affiliated hospital of Xinjiang Medical University, Xinjiang, China, which was performed between April 2023 to September 2025, The total number of patients in our study were 100. The number of female patients in our study were 33 and males were 67. For all patients, we did a diagnostic test (CT) angiogram who have coronary heart disease with type 2 diabetes mellitus. We took detailed data for all enrolled patients. We excluded pregnant women in our study. Data was tabulated and analyzed by software MATLAB and R. Result In a current study total 100 patients were enrolled. In a current study total 100 patients were enrolled. The mean of survival Time were 17.1 (M), the Median were 18, SD were 4.42, the Minimum were 1 and the maximum of survival time were 18 (M). P-Value were of survival time 0.088126. The mean of age were 53.3 Years, the Median were 53, SD were 12.24, the Minimum were 31 and the maximum of survival time were 85 Years. P-Value of age were 0.062998. The mean of BMI were 27.2 (Kg/m2), the Median were 26.5, SD were 4.56, the Minimum were 20 and the maximum of BMI were 39 (Kg/m2). In the above table 4, Correlation between selected variables, Variable MACE and Age correlation coefficient were 0.25. Variable MACE and BMI correlation coefficient were 0.15. Variable MACE and TG correlation coefficient were 0.30. Variable MACE and TCcorrelation coefficient were 0.20. Variable MACE and LDL correlation coefficient were 0.35. Variable MACE and HDL correlation coefficient were -0.20. Variable MACE and CRP correlation coefficient were 0.40. Variable MACE and IL-6 correlation coefficient were 0.45. In our study P-Value were less than (< 0.05). Conclusion We concluded in our study that the diagnosis of Coronary heart disease (CHD) in individuals with type 2 diabetes can be made more accurately with a complete diagnostic model that combines clinical risk factors and CT-angiogram. This provides information for the early detection of coronary heart disease (CHD) in patients with diabetes and allows for timely intervention and treatment.

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