To develop a classification system which helps differentiate cystic intraductal papillary neoplasm of the bile duct from mucinous cystic neoplasm of the liver.

Objective: To establish a classification system which differentiates cystic intraductal papillary neoplasm of the bile duct (cystic IPNB) from hepatic mucinous cystic tumors (MCN) based on their radiological difference.

Methods: A total of 75 patients pathologically diagnosed as MCN and IPNB in two major hospitals from 2015 to 2024 were enrolled. Radiological features were recorded and compared between these two tumors. Variables with significant differences were included in multivariate logistic regression (LR) analysis. A decision model was built and simplified based on importance ranking of variables. K-nearest-neighbor (KNN) model was introduced to learn distribution of individuals in main dimensions based on multiple correspondence analysis (MCA) and predicted diagnosis. The diagnostic efficacy of the classification system and the KNN model was compared.

Results: Significant differences existed in Dmax-IVC angle, septation, mural nodule, upstream and downstream biliary dilatation, communication with bile duct between MCN and cystic IPNB. Downstream biliary dilatation and communication with bile duct were highly specific for IPNB (specificity, 97.9 % and 100 %, respectively), which could independently diagnose IPNB. Among four significant indicators in LR analysis, upstream biliary dilatation and Dmax-IVC angle were used for a simplified decision model to attain good applicability. The KNN model based on MCA data achieved highest accuracy (0.910) when K = 11. Overall, the classification system achieved an AUC of 0.882 (0.95CI: 0.797-0.966), compared with 0.911 (0.95CI: 0.818-1.000) in the KNN model, which demonstrated no significant difference (p = 0.655) in differential performance.

Conclusion: The classification system combining four important indicators had equivalent performance to KNN model in discrimination, which was simple and applicable for clinical practice, and also accessible on unenhanced examinations.