A Radiomics Approach Predicts Lymph Node Metastasis and Clinical Outcomes in Intrahepatic Mass-Forming Cholangiocarcinoma

Background: To develop and validate a radiomics model for predicting lymph node (LN) metastasis in intrahepatic mass-forming cholangiocarcinoma (IMCC), and to determine its prognostic value. Methods: A radiomics model was developed in a primary cohort of 103 IMCC patients who underwent curative-intent resection and regional lymphadenectomy. Radiomic features were extracted from arterial-phase computed tomography (CT) scans. A radiomics signature was built based on high reproducible features using the Lasso method. Multivariate logistic regression analysis was adopted to establish a radiomics model incorporating radiomics signature and other independent predictors. Model performance was determined by its discrimination, calibration, and clinical usefulness. The model was internally validated in 52 consecutive patients. Findings: The radiomics signature comprised eight LN-status-related features and showed significant association with LN metastasis in both cohorts (P<0.001). A radiomics nomogram that incorporates radiomics signature and CA 19-9 level showed good calibration and discrimination in primary cohort (AUC 0.8462) and validation cohort (AUC 0.8921). Promisingly, the radiomics nomogram yielded an AUC of 0.9224 in CT-reported LN-negative subgroup. Decision curve analysis confirmed the clinical utility of this nomogram. High-risk metastasis portended significantly lower overall and recurrence-free survival than low-risk metastasis (both P<0.001). The radiomics nomogram represented an independent preoperative predictor of overall and recurrence-free survival. Interpretation: Our radiomics nomogram provides an individualized approach for preoperative detection of LN metastasis in IMCC patients, especially in CT-reported LN-negative patients. This model allows prediction of the metastasizing potential of IMCCs with poor prognosis even after curative-intent resection and thus may improve clinical decision-making. Funding: This study was supported by the Natural Science Foundation of China (81530048, 81470901, 81670570), and the Key research and development program of Jiangsu Province (BE2016789). Declaration of Interest: All authors declare no potential conflicts of interest. Ethical Approval: The ethics committee of Nanjing Medical University approved this retrospective analysis and waived the requirement for informed consent.