ORIGINAL RESEARCH article
Front. Cardiovasc. Med.
Sec. Cardiovascular Imaging
Predicting Major Adverse Cardiovascular Events in Diabetic and Non-Diabetic Patients with Coronary Artery Disease: Visual Models Integrating Multi-Parametric Coronary Computed Tomography Angiography and Pericoronary Adipose Tissue Radiomics
Ming Chen 1
Xiyi Huang 2
Lizhu Ouyang 1
Xinjie Chen 1
Jialing Pan 1
Li-Wen Wang 1
Zhou Lanni 1
Fusheng Ouyang 1
Qiugen Hu 1
BaoLiang Guo 1
1. The Eighth Affiliated Hospital of Southern Medical University, Foshan, China
2. The Affiliated Shunde Hospital of Guangzhou Medical University, Foshan, China
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Abstract
Objective: To compare the application value differences of PCAT radiomic features, clinical risk features and computed tomography (CT)-derived parameters in predicting Major adverse cardiovascular events (MACE) in patients with/without diabetes. Methods: Retrospective analysis included 1000 coronary atherosclerosis patients undergoing Coronary CT angiography (CCTA) (with/without diabetes: 274/726) from the Eighth Affiliated Hospital of Southern Medical University. Clinical/CT data were collected, extracting 285 PCAT radiomic features from three major coronaries. Least absolute shrinkage and selection operator regression identified MACE-associated radiomic features. Patients underwent random 6:4 training/testing cohort split. Four predictive models were constructed: Model 1 (clinical factors), Model 2 (imaging factors), Model 3 (imaging-radiomic features), Model 4 (all factors). Results: In the training set, Model 4 showed the best performance: The area under the curves (AUC) of 0.803 [95% confidence interval (CI): 0.756-0.850] and 0.854 (95% CI: 0.779-0.929) for groups with/without diabetes, respectively. Model 3 outperformed Model 2 in patients without diabetes (p<0.05), but not significantly in diabetic patients (p>0.05). Conclusion PCAT radiomics, CT-derived parameters, and plaque features demonstrate differential predictive value for MACE in patients with/without diabetes. Combining these with clinical risk factors provides most effective model for both.
Summary
Keywords
Coronary arteriosclerosis, Coronary CT angiography, diabetes, Major adverse cardiovascular events, Pericoronary adipose tissue
Received
18 July 2025
Accepted
11 February 2026
Copyright
© 2026 Chen, Huang, Ouyang, Chen, Pan, Wang, Lanni, Ouyang, Hu and Guo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Qiugen Hu; BaoLiang Guo
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