MRI-Based Radiomics Nomogram for Preoperatively Differentiating Intrahepatic Mass-Forming Cholangiocarcinoma From Resectable Colorectal Liver Metastases

Abstract

To establish a radiomics nomogram based on multiparameter magnetic resonance(MR)images for preoperatively differentiating intrahepatic mass-forming cholangiocarcinoma (IMCC) from colorectal cancer liver metastasis (CRLM). A total of 133 patients in training cohort (64 IMCC and 69 CRLM), 57 patients in internal validation cohort (29 IMCC and 28 CRLM), and 51 patients (23 IMCC and 28 CRLM) in external validation cohort were included. Radiomics features were extracted from the multiparameter MR images and selected by the least absolute shrinkage and selection operator algorithm to establish the radiomics model. Clinical variables and magnetic resonance imaging (MRI) findings were selected by univariate and multivariate analyses to construct a clinical model. The radiomics nomogram was combined with radiomics model and clinical model. Six features were selected to construct the radiomics model. The radiomics signature showed better discrimination than the clinical model in the training cohort (Area Under the Curve (AUC), 0.92; 95% confidence interval (CI), 0.87-0.96 vs. AUC, 0.74; 95% CI, 0.66-0.83) and the external validation cohort (AUC, 0.90; 95% CI, 0.82-0.98 vs. AUC, 0.81; 95% CI, 0.69-0.93). The radiomics nomogram showed the best discrimination performance with favorable calibration in the training cohort (AUC, 0.94; 95% CI, 0.90-0.97) and the external validation cohort (AUC, 0.92; 95% CI, 0.84-1.00). The radiomics nomogram combining radiomics signatures based on multiparameter MRI with clinical factors (serum carcinoembryonic antigen level and tumor diameter) may provide a reliable and noninvasive tool to discriminate IMCC from CRLM, which could help guide treatment strategies and prognosis preoperatively prediction.