Abstract
OBJECTIVE: To establish a model based on intratumoral and peritumoral radiomics for preoperatively differentiating solitary intrahepatic mass-forming cholangiocarcinoma (IMCC) lesions from colorectal cancer liver metastases (CRLM). METHODS: Preoperative MRI scans from IMCC patients were retrospectively obtained from three academic medical centers. Radiomics features were extracted from the intratumoral and multiple peritumoral regions. After feature selection, the optimal peritumoral range was determined. The radiomics model was developed by integrating both single-sequence and multisequence models through probabilistic ensemble learning. Significant variables from clinical imaging features, radiomics, were integrated into a combined model, and its performance was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: A total of 170 patients (93 IMCC, 77 CRLM) comprised the training cohort, and 42 (23 IMCC, 19 CRLM) formed the external validation cohort. The Combined model achieved superior AUCs in training (0.978 [95% CI: 0.971-0.985]) and validation (0.940 [0.899-0.968]), outperforming radiomics (training: 0.947 [(95% CI: 0.932-0.961]); validation: 0.908 [(95% CI: 0.861-0.943)]) and Clin-Imag models (training: 0.858 [95% CI: 0.831-0.880]; validation: 0.842 [95% CI: 0.786-0.889]) (DeLong test, p = 0.001). SHAP analysis identified DWI-based 5-mm peritumoral features and clinical-imaging variables (e.g., lesion location and bile duct dilation) as key discriminators. CONCLUSIONS: The combined model integrating clinical-imaging variables and multiparametric MRI-derived intratumoral and 5-mm peritumoral radiomics features provides a non-invasive tool for distinguishing solitary IMCC from CRLM, offering potential clinical utility for guiding personalized treatment strategies and avoiding unnecessary invasive interventions.