ORIGINAL RESEARCH article
Front. Oncol.
Sec. Gastrointestinal Cancers: Hepato Pancreatic Biliary Cancers
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1632630
This article is part of the Research TopicNovel Therapeutic Approaches for Biliary Tract Cancer and Hepatocellular Carcinoma, Volume IIView all 5 articles
Preoperative Assessment of Longitudinal Extent in Hilar Cholangiocarcinoma Using Noninvasive Enhanced MR Radiomics：A multicenter study
Provisionally accepted
- 1Southwest Medical University, Luzhou, China
- 2Jiangsu Province Hospital of Chinese Medicine Chongqing Hospital (Chongqing Yongchuan Hospital of Chinese Medicine), Chongqing, China
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This study aims to develop a noninvasive radiomics model based on magnetic resonance imaging (MRI) for accurately predicting the longitudinal extent of hilar cholangiocarcinoma (HCCA), to assist in subsequent surgical decision making.This study retrospectively collected and analyzed data from patients with HCCA across three medical centers in China. Radiomics quantitative features were extracted from T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and enhanced T1 high-resolution isotropic volume examination (e-THRIVE) sequences. L1 regularization was employed to select features, and three single-sequence radiomics models were developed to predict Bismuth type Ⅳ of HCCA. To improve the predictive accuracy for Bismuth type Ⅳ, the fusion model integrating the three single-sequence models was constructed. The performance of these models was evaluated comprehensively, and the optimal radiomics model for predicting longitudinal extent was identified.A total of 154 patients with HCCA were included in the analysis. The radiomics models based on T2WI, DWI, and e-THRIVE sequences demonstrated predictive capabilities, with AUC values in the training set of 0.867, 0.923, and 0.872, respectively, and AUC values in the test set of 0.809, 0.823, and 0.808, respectively. The fusion model, which combined features from all three sequences, achieved superior predictive performance, with an AUC of 0.980 in the training set and 0.907 in the test set. This model demonstrated robust potential for predicting whether the HCCA was classified as Bismuth type Ⅳ.The multi-sequence MRI-based radiomics model can effectively predict Bismuth type Ⅳ of HCCA, assisting in clinical surgical decision-making, facilitating R0 resection to improve the prognosis of patients with HCCA.
Keywords: Longitudinal extent, MRI, Radiomics, Bismuth-Corlette classification, Hilar cholangiocarcinoma
Received: 24 May 2025; Accepted: 25 Aug 2025.
Copyright: © 2025 Quan, Huang, Liu, Yuan and Shu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jian Shu, Southwest Medical University, Luzhou, China
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