ArticleQuantitative imaging in medicine and surgery2026
Plaque characteristics and parameters derived from coronary computed tomography angiography for predicting major adverse cardiovascular events in patients with and without diabetes.
Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Coronary atherosclerosis is the primary pathological basis of coronary heart disease, and patients with diabetes face an elevated risk of cardiovascular events. The value of plaque characteristics and derived parameters based on coronary computed tomography angiography (CCTA) in predicting major adverse cardiovascular events (MACEs) may differ between patients with and without diabetes. This study aimed to compare the predicative value of plaque features and computed tomography (CT)-derived parameters from CCTA in forecasting MACEs in between patients with and without diabetes, providing a more accurate reference for clinical management. Methods: A total of 472 patients with coronary artery disease were retrospectively enrolled, including 132 patients with diabetes and 340 patients without diabetes. Clinical and imaging data were collected, and follow-up was conducted. Multivariate Cox proportional hazards regression was used to identify risk factors, while receiver operating characteristic (ROC) curve analysis assessed the predictive value for MACEs. Results: In the diabetic group, the independent predictors of MACEs were coronary artery calcium score (CACS) ≥100 [hazard ratio (HR) =1.98; 95% confidence interval (CI): 1.06-3.72; P=0.033] and the presence of low-attenuation plaque (LAP) (HR =2.13; 95% CI: 1.00-4.53; P=0.049). The combination of CACS and LAP predicted 1-, 3-, and 5-year MACEs, with areas under the curve (AUCs) of 0.649, 0.603, and 0.668, respectively. In the nondiabetic group, positive remodeling (PR) was a strong predictor of MACEs (HR =45.00; 95% CI: 22.69-89.28; P<0.001), with AUCs of 0.792, 0.884, and 0.795 at 1, 3, and 5 years, respectively. Significant differences in baseline characteristics such as hypertension, CT-derived fractional flow reserve ≤0.8, and Coronary Artery Disease Reporting and Data System score ≥3 were observed between the two groups (P<0.05). Conclusions: The value of plaque characteristics and CT-derived parameters in predicting MACEs varies between patients with and without diabetes. The combination of CACS and LAP is effective in assessing MACE risk in patients with diabetes, whereas PR is a stronger predictor of MACEs in patients without diabetes.
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