Evidence map›Paper›PMID 42893439›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Foundation Model-Enabled Pathology-Informed MRI Model for Preoperative Prediction of Vessels Encapsulating Tumor Clusters in Resectable Hepatocellular Carcinoma: A Multicenter Retrospective Study.

Zhehan Shen, Wanmin Liu, Xiaoming Li, Wenjie Zou, Yiman Li, Jie Yuan, Yasen Yimit, Shihang Wang, Linhao Qu, Hui Dong and 3 more

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

13 authors.

Zhehan Shen *Department of Radiology, Ruijin Hospital, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-8399-0681
Wanmin Liu *Department of Radiology, Ruijin Hospital, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-8216-0424
Xiaoming Li *7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, The First Affiliated Hospital of Army Medical University, Chongqing, China.ORCID https://orcid.org/0009-0003-5875-7364
Wenjie ZouDepartment of Radiology, School of Medicine, Tongji Hospital, Tongji University, Shanghai, China.ORCID https://orcid.org/0009-0001-6488-5966
Yiman Li7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, The First Affiliated Hospital of Army Medical University, Chongqing, China.
Jie YuanDepartment of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Yasen YimitDepartment of Radiology, Ruijin Hospital, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID https://orcid.org/0009-0004-4503-6549
Shihang WangFaculty of Applied Sciences, Macao Polytechnic University, Macao, China.ORCID https://orcid.org/0000-0002-4714-6504
Linhao QuDepartment of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.
Hui DongDepartment of Pathology, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.ORCID https://orcid.org/0009-0003-0428-9593
Wei Chen7T Magnetic Resonance Translational Medicine Research Center, Department of Radiology, The First Affiliated Hospital of Army Medical University, Chongqing, China.ORCID https://orcid.org/0000-0002-6829-9067
Ningyang JiaDepartment of Radiology, Eastern Hepatobiliary Surgery Hospital, The Third Affiliated Hospital of Naval Medical University, Shanghai, China.
Peijun WangDepartment of Radiology, School of Medicine, Tongji Hospital, Tongji University, Shanghai, China.

Funding

National Natural Science Foundation of China 82227807Shanghai Municipal Commission of Health and Family Planning 2022JC017Shanghai Municipal Science and Technology Commission 25SF1908900Tongji University ITJ(ZD)2301Yunji Plan KJ2-0101-25-7262
6 · The paper itself

Abstract

Vessels encapsulating tumor clusters (VETC) are an aggressive vascular phenotype of hepatocellular carcinoma that is usually determined after surgery. A foundation model-enabled framework for pathology-informed VETC prediction on pretreatment magnetic resonance imaging (MRI), termed PIVOT, uses paired preoperative multiparametric MRI, postoperative hematoxylin and eosin whole-slide images, and CD34 immunohistochemistry during model development, while inference requires only preoperative MRI. PIVOT-MRI uses morphologic and vascular embedding alignment, and PIVOT-Clinical combines the PIVOT-MRI score with tumor size and alpha-fetoprotein. The multicenter retrospective study includes 2052 patients in a training cohort, an internal test cohort, and four external validation cohorts. PIVOT-MRI achieves an area under the receiver operating characteristic curve of 0.887 in the internal test cohort and 0.839-0.861 across external cohorts. PIVOT-Clinical increases the internal-test area under the curve to 0.904 and PIVOT-Clinical-defined groups are associated with different two-year recurrence risks. Removing both histopathologic alignment branches results in the largest ablation-related performance decrease. Exploratory radiotranscriptomic analyses showed that higher PIVOT-MRI scores were associated with angiogenesis-related, endothelial, and proliferative transcriptional programs. PIVOT enables noninvasive preoperative assessment of pathology-defined vascular aggressiveness in resectable hepatocellular carcinoma while preserving an MRI-only clinical inference pathway.

Indexed as

digital pathologyfoundation modelhepatocellular carcinomamagnetic resonance imagingmultimodal learningvessels encapsulating tumor clusters

Identifiers

PMID42893439
PMCPMC13676818

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.