Prediction of coronary atherosclerosis progression in type 2 diabetes mellitus based on AI-derived CCTA parameters and clinical factors: a follow-up study
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引用次数: 0
Abstract
Objective
To develop a predictive model for coronary atherosclerosis progression in patients with type 2 diabetes mellitus (T2DM) based on Artificial intelligence(AI)-derived coronary computed tomography angiography (CCTA) parameters combined with clinical indicators.
Methods
This retrospective study enrolled 114 patients with T2DM and non-obstructive coronary artery disease (1%–49% stenosis) who underwent CCTA at our hospital between September 2019 and September 2024. After follow-up of 1–5 years, patients were stratified into a progression group (n = 48) and a control group (n = 66). Progression was defined as the occurrence of acute myocardial infarction, revascularization, or stenosis progression to ≥ 50% on follow-up CCTA. Clinical data and AI-derived quantitative parameters of pericoronary adipose tissue(PCAT) and coronary plaques were compared. A predictive model was then developed using stepwise logistic regression and its performance evaluated.
Results
The progression group had significantly higher glycated hemoglobin (HbA1c) and troponin, and lower high-density lipoprotein cholesterol (HDL-C) (all P < 0.05).CCTA analysis revealed that the progression group had a significantly greater pericoronary fat attenuation index around the left anterior descending (LAD-FAI) and left circumflex (LCX-FAI) arteries, as well as increased plaque length, total plaque volume, and specific plaque component volumes (all P < 0.05). Multivariate logistic regression analysis identified HbA1c, LAD-FAI, and plaque length as independent predictors of progression. A nomogram based on these predictors achieved an AUC of 0.8332.
Conclusion
LAD-FAI and plaque length and HbA1c are independent predictors for the progression of non-obstructive coronary lesions in T2DM patients. The proposed nomogram may provide a noninvasive and cost-effective tool for early risk stratification and preventive management.
期刊介绍：
Acta Diabetologica is a journal that publishes reports of experimental and clinical research on diabetes mellitus and related metabolic diseases. Original contributions on biochemical, physiological, pathophysiological and clinical aspects of research on diabetes and metabolic diseases are welcome. Reports are published in the form of original articles, short communications and letters to the editor. Invited reviews and editorials are also published. A Methodology forum, which publishes contributions on methodological aspects of diabetes in vivo and in vitro, is also available. The Editor-in-chief will be pleased to consider articles describing new techniques (e.g., new transplantation methods, metabolic models), of innovative importance in the field of diabetes/metabolism. Finally, workshop reports are also welcome in Acta Diabetologica.
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