A combined radiomics and clinical model for preoperative differentiation of intrahepatic cholangiocarcinoma and intrahepatic bile duct stones with cholangitis: a machine learning approach.

ABSTRACT:

Background

This study aimed to develop and validate a predictive model integrating radiomics features and clinical variables to differentiate intrahepatic bile duct stones with cholangitis (IBDS-IL) from intrahepatic cholangiocarcinoma (ICC) preoperatively, as accurate distinction is crucial for determining appropriate treatment strategies.

Methods

A total of 169 patients (97 IBDS-IL and 72 ICC) who underwent surgical resection were retrospectively analyzed. Radiomics features were extracted from ultrasound images, and clinical variables with significant differences between groups were identified. Feature selection was performed using LASSO regression and recursive feature elimination (RFE). The radiomics model, clinical model, and combined model were constructed and evaluat

SUBMITTER: Qian H 

PROVIDER: S-EPMC11955465 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature