Abstract
OBJECTIVES: Differentiating chronic total occlusion (CTO) from subtotal occlusion (SO) is often difficult to make from coronary computed tomography angiography (CCTA). We developed a CCTA-based radiomics model to differentiate CTO and SO. METHODS: A total of 66 patients with SO underwent CCTA before invasive angiography and were matched to 66 patients with CTO. Comprehensive imaging analysis was conducted for all lesioned vessels, involving the automatic identification of the lumen within the occluded segment and extraction of 1,904 radiomics features. Radiomics models were then constructed to assess the discriminative value of these features in distinguishing CTO from SO. External validation of the model was performed using data from another medical center. RESULTS: Compared to SO patients, CTO patients had more blunt stumps (internal: 53/66 (80.3%) vs. 39/66 (59.1%); external: 36/50 (72.0%) vs. 20/50 (40.0%), both p < 0.01), longer lesion length (internal: median length 15.4 mm[IQR: 10.4-22.3 mm] vs. 8.7 mm[IQR: 4.9-12.6 mm]; external:11.8 mm[IQR: 6.1-23.4 mm] vs. 6.2 mm[IQR: 3.5-9.1 mm]; both p < 0.001). Sixteen unique radiomics features were identified after the least absolute shrinkage and selection operator regression. When added to the combined model including imaging features, radiomics features provided increased value for distinguishing CTO from SO (AUC, internal: 0.772 vs. 0.846; p = 0.023; external: 0.718 vs. 0.781, p = 0.146). CONCLUSIONS: The occluded segment vessels of CTO and SO have different radiomics signatures. The combined application of radiomics features and imaging features based on CCTA extraction can enhance diagnostic confidence.