Incremental Value of Pericoronary Adipose Tissue Radiomics Models in Identifying Vulnerable Plaques.

Objective: Inflammatory characteristics in pericoronary adipose tissue (PCAT) may enhance the diagnostic capability of radiomics techniques for identifying vulnerable plaques. This study aimed to evaluate the incremental value of PCAT radiomics scores in identifying vulnerable plaques defined by intravascular ultrasound imaging (IVUS).

Methods: In this retrospective study, a PCAT radiomics model was established and validated using IVUS as the reference standard. The dataset consisted of patients with coronary artery disease who underwent both coronary computed tomography angiography and IVUS examinations at a tertiary hospital between March 2023 and January 2024. The dataset was randomly assigned to the training and validation sets in a 7:3 ratio. The diagnostic performance of various models was evaluated on both sets using the area under the curve (AUC).

Results: From 88 lesions in 79 patients, we selected 9 radiomics features (5 texture features, 1 shape feature, 1 gray matrix feature, and 2 first-order features) from the training cohort (n = 61) to build the PCAT model. The PCAT radiomics model demonstrated moderate to high AUCs (0.847 and 0.819) in both the training and test cohorts. Furthermore, the AUC of the PCAT radiomics model was significantly higher than that of the fat attenuation index model (0.847 vs 0.659, P < 0.05). The combined model had a higher AUC than the clinical model (0.925 vs 0.714, P < 0.01).

Conclusions: The PCAT radiomics signature of coronary CT angiography enabled the detection of vulnerable plaques defined by IVUS.