To investigate the value of radiomics nomogram based on coronary CT angiography (CCTA) in differential diagnosis of vulnerable plaques in patients with coronary artery disease (CAD).

From January 2018 to December 2022, 93 CAD patients who had undergone CCTA scans at the Affiliated Cardiovascular Hospital of Shanxi Medical University with complete data were enrolled. There were 95 non-calcified plaques, including 43 vulnerable plaques and 52 stable plaques. In an 8: 2 ratio, the lesions were randomly separated into a training set (n=76) and a testing set (n=19). To choose radiomics features appropriate for a CCTA-image-based radiomics signature, the Mann-Whitney U test, the correlation coefficient approach, and least absolute shrinkage and selection operator (LASSO) were used, and a radiomics score (Radscore) was created. Using clinical data and CCTA findings, a clinical model was constructed. Subsequently, the separate clinical parameters and Radscore were integrated to create a radiomics nomogram. The receiver operating characteristics (ROC) curve, calibration curve, and decision curve analysis were used to evaluate the performance of the radiomics signature, clinical model, and nomogram.

Finally, 13 best features with non-zero coefficients were selected. In the training and test sets, the AUC of the nomogram model combined with Radscore and clinical variables were 1.000 and 0.922, sensitivity were 1.000 and 1.000, specificity were 1.000 and 0.800, and accuracy were 1.000 and 0.895, respectively. The calibration curve demonstrated good agreement between expected and actual results. The decision curve analysis revealed that the nomogram had greater clinical application value compared to the clinical model.

Combined with clinical factors and imaging features, the radiomics nomogram can accurately and objectively identify vulnerable plaques, and has good diagnostic performance, which can be used to guide clinical decision-making.