Prognostic value of functional MRI and liver function synergy in hepatocellular carcinoma patients receiving combined locoregional-systemic therapy: A multicenter scoring model

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Authors: Langlang Tang, Kaiqian Que, Yanfen Lan, Yimin Li, Bin Wang, Zhuting Fang
Cited by: 0
References: 21

Abstract

PURPOSE: To develop and validate a prognostic model integrating pretreatment MRI features and clinical characteristics for hepatocellular carcinoma (HCC) patients undergoing transarterial chemoembolization (TACE) and hepatic arterial infusion chemotherapy (HAIC) combined targeted immunotherapy (TII). A weighted scoring system was developed to improve the model's clinical utility. METHODS: We retrospectively recruited 141 patients with HCC from multiple centers, with 98 in the training cohort and 43 in the validation cohort. The independent predictors were identified using univariate and multivariate Cox regression analyses and developed a clinical nomogram. We constructed an 10-point weighted scoring system incorporating imaging features. Model performance was evaluated using AUC, decision curve analysis (DCA), and calibration curves assessed via bootstrapping. RESULTS: Logistic regression identified four risk factors for objective response (OR): irregular tumor border, absent of Intratumoral artery, albumin-bilirubin (ALBI) score ≥ -2.352, number ≥ 2, and tumor histopathological enhancement (THPE). The AUC was 0.804 in the training cohort and 0.580 in the validation cohort. The Akaike Information Criterion (AIC) for the scoring model was lower than the other model for predicting OR, progression-free survival (PFS), and overall survival (OS). Patients with a scoring model value > 5.5 points were classified as high-risk. The Kaplan-Meier (K-M) curves of the scoring model showed the better discriminative ability for PFS and OS. CONCLUSION: The functional imaging-liver function synergy model demonstrates superior prognostic accuracy over conventional tumor burden parameters in hepatocellular carcinoma patients receiving quadruple therapy. Furthermore, the derived 10-point scoring system enables clinically actionable risk stratification.

Fields of Study & Subjects

Hepatocellular Carcinoma Treatment and Prognosis MRI in cancer diagnosis Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
European Journal of Radiology
Volume
196
Pages
112705–112705
Publication date
28 January 2026
Language
EN