Abstract Background The precise impact of LI-RADS-defined risk factors on the diagnosis and prognosis of intrahepatic cholangiocarcinoma (iC
Abstract Background The precise impact of LI-RADS-defined risk factors on the diagnosis and prognosis of intrahepatic cholangiocarcinoma (iCCA) remains unclear. Objective To assess the value of LI-RADS categories and features for iCCA diagnosis, focusing on the diagnostic and prognostic implications of LI-RADS-defined risk factors. Methods Totally 214 high risk patients, including 107 surgically-confirmed solitary iCCAs and 107 hepatocellular carcinomas (HCC) from two centers were retrospectively enrolled. Clinical and MRI features based on LI-RADS v2018 were compared, and the performance of targetoid features for discriminating iCCA was evaluated. Recurrence-free survival (RFS) was compared across different pathologic diagnoses and LI-RADS categories. Multivariate Cox analysis was performed to identify the independent risk factors for RFS. Results In the LI-RADS defined high-risk patients, iCCAs differed from HCCs in MRI manifestation. The LR-M category enabled the accurate classification of most iCCAs (89/107, 83.2%), achieving high sensitivity (83.2%), specificity (85.1%), and accuracy (84.1%). The optimal diagnostic performance for iCCA was achieved when at least one targetoid appearance was required for LR-M categorization (AUC = 0.828). Although 26.2% iCCAs presented at least one major feature and 15.0% iCCAs were miscategorized as probably or definitely HCC, only one iCCA case was categorized as LR-5. RFS varied according to both pathologic diagnosis (P = 0.030) and LI-RADS category (P = 0.028), with LI-RADS category demonstrating an independent association with RFS (HR = 1.736, P = 0.033). Conclusions In high-risk patients, iCCAs frequently exhibit HCC major features, leading to miscategorization as probable HCC. However, the LR-5 category remains highly specific for ruling out iCCA. Furthermore, in high-risk patients with solitary resected iCCA or HCC, LI-RADS category enables the prediction of postsurgical prognosis independently from pathological diagnosis.
