Evidence map›Paper›PMID 41476136›Full record

ArticleNPJ precision oncology2025

Noninvasive imaging analysis of vascular phenotypes improves prognostic stratification in primary liver cancer: a multi-cohort study.

Hongjie Xin, Ying Wang, Hongwei Xin, Qianwei Lai, Xuyi Wang, Huiyan Wang, Jun Hu, Yi Zhang, Keyang Zhou, Bihong Liao and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in NPJ precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

12 authors.

Hongjie Xin *Guangdong Provincial Key Laboratory of Gastroenterology, Institute of Gastroenterology of Guangdong Province, Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Ying Wang *Department of Gastroenterology, The Fourth Hospital of Changsha, Hunan Normal University, Changsha, China.
Hongwei Xin *Fujian Key Laboratory of Pattern Recognition and Image Understanding, School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China.
Qianwei LaiGuangdong Provincial Key Laboratory of Gastroenterology, Institute of Gastroenterology of Guangdong Province, Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Xuyi WangDepartment of Radiology, The Second Affiliated Hospital, University of South China, Hengyang, China.
Huiyan WangDepartment of Radiology, The Second Affiliated Hospital, University of South China, Hengyang, China.
Jun HuDepartment of Radiology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China.
Yi ZhangDepartment of Radiology, The Second Affiliated Hospital, University of South China, Hengyang, China.
Keyang ZhouDepartment of Radiology, The Second Affiliated Hospital, University of South China, Hengyang, China.
Bihong LiaoDepartment of Radiology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, China. liaobh2023@163.com.
Yang BaiGuangdong Provincial Key Laboratory of Gastroenterology, Institute of Gastroenterology of Guangdong Province, Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, China. baiyang1030@hotmail.com.
Zhihua ChenDepartment of Radiology, The Second Affiliated Hospital, University of South China, Hengyang, China. chen_zhi2003@163.com.

Funding

The Natural Science Foundation of Guangdong province 2022A1515011230The President Foundation of Nanfang Hospital, Southern Medical University 2024B003
6 · The paper itself

Abstract

Tumor vascular microenvironment (TVME) critically governs biological properties in primary liver cancers (PLC), yet noninvasive tools to decode its heterogeneity remain clinically unavailable. In this study, data from six clinical cohorts encompassing hepatocellular carcinoma (HCC), intrahepatic cholangiocarcinoma (ICC), and combined hepatocellular-cholangiocarcinoma, were comprehensively analyzed. Based on quantitative vascular features extracted from computed tomography (CT) images, a novel multi-task learning computational framework (MTV-Net) was constructed to generate two imaging biomarkers: TAVS

Identifiers

PMID41476136
PMCPMC12864754

What OpenQuestion holds

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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.