Prediction of recurrence in patients with mass-forming intrahepatic cholangiocarcinoma using computed tomography-derived features correlated with histo-pathologic factors.

Authors

Hang Li, Hongyan Yang, Lei Xu, Shuo Wang, Xingguo Pang, NingJing Yang, Xiaoli Chen, Torkel B Brismar

Published in

European journal of radiology. Volume 203. Pages 113054. Jul 01, 2026. Epub Jul 01, 2026.

Abstract

To evaluate if preoperative imaging features from CT at mass-forming intrahepatic cholangiocarcinoma (MF-iCCA) are related to histo-pathologic factors, and to evaluate if those associations can be used to construct an imaging score to predict postoperative recurrence.
Consecutive patients with MF-iCCA who underwent preoperative contrast-enhanced CT at two centers between September 2017 and December 2025 were retrospectively reviewed by two radiologists. After independent annotation of 16 imaging features, univariate and multivariate regression analyses were performed to identify independent predictors for high-risk histo-pathologic factors (microvascular invasion, LNM [lymph node metastasis], or poor tumor differentiation). A risk scoring system was developed and used to predict very early recurrence (VER) and early recurrence (ER).
In total 152 patients (median age, 62 years [IQR, 54-69 years]; 57 women) were included from two medical centers (training cohort: n = 109; external validation cohort: n = 43). Peritumoral enhancement at arterial phase had the strongest association with high-risk histo-pathologic factors, followed by multinodularity, intrahepatic bile duct dilation, and CT-reported LNM (P < 0.05, all). The four features were used to construct the risk scoring system. Area under the curve (AUC) of VER-weighted and ER-weighted risk scoring system for high-risk histo-pathologic factors was 0.827 and 0.829 in external validation cohort, respectively. The risk scoring system based on high-risk histo-pathologic factors showed superior prognostic performance for VER (AUC, 0.870 [95% CI: 0.761, 0.978]) and ER (AUC, 0.860 [95% CI: 0.737, 0.983]) in external validation cohort.
Recurrence of MF-iCCA can be predicted by evaluating preoperative imaging features at CT.

PMID:
42407182
Bibliographic data and abstract were imported from PubMed on 07 Jul 2026.

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