Evidence map›Paper›PMID 42500825›Full record

Observational studyLiver international : official journal of the International Association for the Study of the Liver2026

Preoperative MRI Intratumoral Heterogeneity Radiomics for Microvascular Invasion and Recurrence-Free Survival in HCC.

Ruishan Liu, Yangyang Xie, Lv Yue, Jing Jia, Lu Wang, Juan Liao, Hong-Wei Li, Hongchao Yao, Jie Zhang, Yanju Wang and 12 more

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Liver international : official journal of the International Association for the Study of the Liver, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

Ruishan LiuDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Yangyang XieZhejiang Key Laboratory of Multi-Omics Precision Diagnosis and Treatment of Liver Diseases, Department of General Surgery, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Lv YueDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Jing JiaDepartment of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China.
Lu WangDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Juan LiaoDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Hong-Wei LiDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Hongchao YaoDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Jie ZhangDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Yanju WangDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Xingxiong ZhouDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Wei ShiDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Jiangqin MaDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Qian ChenDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Xueqin MaDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Wei ZhouSchool of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Lian YangDepartment of Radiology, Huazhong University of Science and Technology, Wuhan, China.
Gang NingDepartment of Radiology, West China Second Hospital, Sichuan University, Chengdu, China.ORCID 0000-0003-2241-9825
Yong ZhouDepartment of Radiology, Luzhou Hospital of Traditional Chinese Medicine, Luzhou, China.
Peixi HuDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.
Fan LiDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.ORCID 0009-0009-7828-7586
Lihua ZhuoDepartment of Radiology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China.ORCID 0009-0005-5674-0854

Funding

National Key Research and Development Program of China 2024YFC2419303Natural Science Foundation of Ningxia Province 2023AAC03684Science and Technology Project of Mianyang Municipal Health Commission 2025013
6 · The paper itself

Abstract

BACKGROUND AND

aimsMicrovascular invasion (MVI) is a major determinant of postoperative recurrence and poor prognosis in hepatocellular carcinoma (HCC), yet MVI cannot be reliably identified before surgery: pathologic evaluation is invasive, prone to sampling bias, and available only after resection. We aimed to develop and evaluate a preoperative radiomics biomarker for noninvasive MVI prediction and postoperative risk stratification of recurrence-free survival.

methodsIn this retrospective multicenter study, 567 patients with HCC from four centers were included. Based on pretreatment MRI and clinical variables available before surgery, radiomics models characterising the global tumour region (GTR) and intratumoral heterogeneity (ITH) were developed and integrated into a Fusion model for preoperative prediction of MVI. Discrimination, calibration, and clinical utility were assessed using AUC, calibration curves, and decision-curve analysis (DCA). Prognostic stratification was evaluated using C-index, time-dependent ROC analysis, and Kaplan-Meier analysis of recurrence-free survival, and benchmarked against the Barcelona Clinic Liver Cancer (BCLC), China Liver Cancer (CNLC), and American Joint Committee on Cancer (AJCC) staging systems.

resultsThe Fusion model showed higher discrimination than comparators in the validation and external test sets, achieving AUCs of 0.924 and 0.895, respectively. Ablation analyses showed incremental gains with the sequential addition of GTR features, ITH features, and clinical covariates. Fusion score-based stratification identified high- and low-risk groups with markedly divergent recurrence-free survival. In the external test set, the prognostic model achieved a C-index of 0.766 and time-dependent AUCs of 0.825 at 2 years and 0.878 at 5 years, showing higher discrimination than BCLC, CNLC, and AJCC staging (all p < 0.001). Performance remained robust across HBV status, histologic differentiation, and BCLC stage.

conclusionsA radiomics biomarker integrating global tumour phenotype, intratumoral heterogeneity, and preoperative clinical variables enables noninvasive preoperative MVI assessment and may complement morphology-based staging for recurrence risk stratification in HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsMagnetic Resonance ImagingMicrovesselsAgedDisease-Free SurvivalFemaleHumansKaplan-Meier EstimateMaleMiddle AgedNeoplasm InvasivenessNeoplasm Recurrence, LocalPrognosisRadiomicsRetrospective Studiesintratumoral heterogeneitymicrovascular invasionMRIrecurrence

Identifiers

PMID42500825
PMCPMC13401225

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.