MRI-based prediction of very early recurrence within 1 year after resection of HCC: An international cohort study
Hong Wei1, Subin Heo2, Yang Yang3
1Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
Background & Aims:
Very early recurrence (within 1 year after resection) of hepatocellular carcinoma (HCC) indicates aggressive tumor biology and poor prognosis; however, non-invasive prediction tools remain scarce. This study aimed to develop and validate MRI-based models for predicting very early recurrence and to explore their biological underpinnings.
Methods:
This international, multicenter cohort study retrospectively included 1,811 consecutive patients who underwent curative-intent resection for a single BCLC 0/A HCC and preoperative contrast-enhanced MRI or CT at 14 tertiary care hospitals in China, South Korea, Singapore, France, and the USA, as well as 40 eligible patients from the TCGA-LIHC dataset. To predict 1-year recurrence-free survival (RFS), MRI for Very Early Recurrence Prediction (MERP) models were developed using either preoperative variables alone (MERP-pre) or a combination of pre- and postoperative variables (MERP-post) in the derivation cohort (n = 628). The models were externally validated in Eastern (n = 775) and Western (n = 178) test cohorts and further evaluated in a CT test cohort (n = 230). Biological correlates were investigated using whole-exome and RNA sequencing.
Results:
MERP-pre incorporated alpha-fetoprotein, tumor size, portal venous phase peritumoral hypoenhancement, and intratumoral blood products, whereas MERP-post replaced tumor size with microvascular invasion (MVI). Both models outperformed major staging systems and the IMbrave050 criteria across all test cohorts (C-index, 0.685-0.790 vs. 0.524-0.682; p values, <0.001 to 0.046) and improved risk reclassification (net reclassification improvement [NRI], 0.004-0.372). The MERP models consistently stratified patients into high- and low-risk groups with distinct 1-year RFS rates (all p <0.001). MERP-pre further improved MVI-based risk reclassification (NRI, 0.323) and survival risk stratification. Tumors classified as low risk by MERP-pre exhibited features of the non-proliferative class, increased lipid catabolism, and an immunoactive microenvironment.
Conclusions:
The MERP models may serve as robust, generalizable, and biologically informed tools for predicting very early HCC recurrence and may help refine risk-stratified management strategies.
Impact And Implications:
Very early recurrence (VER) of hepatocellular carcinoma (HCC) within 1 year after resection reflects aggressive tumor biology and is associated with poor prognosis, yet reliable tools for predicting VER remain scarce. In this large, international, multicenter cohort of patients with a single Barcelona Clinic Liver Cancer stage 0/A HCC undergoing curative-intent resection, we developed and externally validated two MRI-based models (MERP-pre and MERP-post) that integrate routinely available clinicopathological and imaging variables. The MERP models consistently outperformed existing prognostic systems and effectively stratified patients into high- and low-risk groups with distinct 1-year recurrence-free survival across diverse cohorts. These findings highlight the potential of the MERP models to complement existing prognostic systems and optimize risk-stratified management of HCC.
