To investigate the predictive value of peri-coronary adipose tissue (PCAT) attenuation for microvascular complications in diabetic patients without significant stenosis and to develop a prediction model for early risk stratification.
This study retrospectively included patients clinically identified for coronary computed tomography angiography (CCTA) and type 2 diabetes between January 2017 and December 2020. All patients were followed up for at least 1 year. The clinical data and CCTA-based imaging characteristics (including PCAT of major epicardial vessels, high-risk plaque features) were recorded. In the training cohort comprising of 579 patients, two models were developed: model 1 with the inclusion of clinical factors and model 2 incorporating clinical factors + RCAPCAT using multivariable logistic regression analysis. An internal validation cohort comprising 249 patients and an independent external validation cohort of 269 patients were used to validate the proposed models.
Microvascular complications occurred in 69.1% (758/1097) of the current cohort during follow-up. In the training cohort, model 2 exhibited improved predictive power over model 1 based on clinical factors (AUC = 0.820 versus 0.781, p = 0.003) with lower prediction error (Brier score = 0.146 versus 0.164) compared to model 1. Model 2 accurately categorized 78.58% of patients with diabetic microvascular complications. Similar performance of model 2 in the internal validation cohort and the external validation cohort was further confirmed.
The model incorporating clinical factors and RCAPCAT predicts the development of microvascular complications in diabetic patients without significant coronary stenosis.
• Hypertension, HbA1c, duration of diabetes, and RCAPCAT were independent risk factors for microvascular complications.
• The prediction model integrating RCAPCAT exhibited improved predictive power over the model only based on clinical factors (AUC = 0.820 versus 0.781, p = 0.003) and showed lower prediction error (Brier score=0.146 versus 0.164).
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Area under the curve
Body mass index
Coronary Artery Calcium Scoring
Coronary artery disease
Coronary Artery Disease - Reporting and Data System
Coronary computed tomography angiography
Diabetic kidney disease
Intraclass correlation coefficients
Left anterior descending artery
Left circumflex artery
Negative predictive value
Net reclassification index
Peri-coronary adipose tissue
Proliferative diabetic retinopathy
Positive predictive value
Right coronary artery
Receiver operating characteristic
Type 2 diabetes
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This study is supported by The National Key Research and Development Program of China (Grant No.: 2021YFF0501402), Shanghai Committee of Science and Technology (Grant No.: 21ZR1452200) and Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (Grant No.: 20161428).
The scientific guarantor of this publication is Dr. Jiayin Zhang.
Conflict of interest
The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
Statistics and biometry
No complex statistical methods were necessary for this paper.
Written informed consent was waived by the hospital Institutional Review Board.
Institutional Review Board approval was obtained.
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Yu, Y., Ding, X., Yu, L. et al. Prediction of microvascular complications in diabetic patients without obstructive coronary stenosis based on peri-coronary adipose tissue attenuation model. Eur Radiol 33, 2015–2026 (2023). https://doi.org/10.1007/s00330-022-09176-6