An MRI-based fusion model for preoperative prediction of perineural invasion status in patients with intrahepatic cholangiocarcinoma.

ABSTRACT:

Background

To develop and validate an MRI-based fusion model for preoperative prediction of perineural invasion (PNI) status in patients with intrahepatic cholangiocarcinoma (ICC).

Methods

A retrospective collection of 192 ICC patients from three medical centers (training set: n = 147; external test set: n = 45) was performed. Patients were classified into the PNI-positive and PNI-negative groups based on postoperative pathological results. After image preprocessing, a total of 1,197 features were extracted from T2-weighted imaging (T2WI). Feature selection was performed, and a radiomics model was constructed using machine learning algorithms, followed by SHapley Additive exPlanations (SHAP) visualization. Subsequently, a deep learning model was constructed based on the pre-

SUBMITTER: Qi Z 

PROVIDER: S-EPMC12032683 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature