Evidence map›Paper›PMID 41998160›Full record

ArticleNPJ precision oncology2026

Supervoxel-based multimodal MRI biomarkers reveal tumor heterogeneity in high-grade glioma for prognostic stratification and therapy response prediction.

Yan Zhu, Xiwen Zhu, Dian Huang, Yang Ji, Ranchao Wang, Yang Li, Yuhao Xu, Yifeng Luo, Yan Zhuang, Zhe Liu and 3 more

Abstract read
In one paragraph

Article in NPJ precision oncology, 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
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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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

13 authors.

Yan Zhu *Department of Radiology, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
Xiwen Zhu *Department of Otolaryngology, Nanjing Lishui People's Hospital, Lishui, China.
Dian HuangDepartment of Radiology, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
Yang JiDepartment of Radiology, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
Ranchao WangDepartment of Radiology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
Yang LiDepartment of Radiology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.
Yuhao XuDepartment of Neurology, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
Yifeng LuoDepartment of Radiology, The Affiliated Yixing Hospital of Jiangsu University, Yixing, China.
Yan ZhuangDepartment of Neurosurgery, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
Zhe LiuSchool of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, China.
Wei WangDepartment of Radiology, Affiliated Hospital of Yangzhou University, Yangzhou, China.
Subo ZhangDepartment of Radiology, Lianyungang Second People's Hospital, Lianyungang, China. zhangsubo@lygey.com.
Yuefeng LiSchool of Medicine, Jiangsu University, Zhenjiang, China. jiangdalyf@163.com.

Funding

National Natural Science Foundation of China 81871343the Social Development Program of Zhenjiang (Social Development) SH2025003
6 · The paper itself

Abstract

High-grade glioma (HGG) exhibits substantial biological heterogeneity, which complicates prognosis and treatment, and clarifying the interplay between proliferating tumor cells and tumor-associated microvasculature may improve patient outcomes. We prospectively enrolled 221 patients with HGG from four institutions and integrated diffusion-weighted and dynamic contrast-enhanced MRI within a supervoxel-based framework to delineate tumor subregions termed density-enhancement compounded voxels (DECV). Four DECV subregions (DECV1-4) with distinct imaging characteristics were identified. DECV4, characterized by low apparent diffusion coefficient and gradual enhancement, was strongly associated with tumor aggressiveness and treatment resistance. Clustering analysis further revealed two DECV phenotypes that differed significantly in progression-free and overall survival; phenotype II showed a higher DECV4 proportion and a poorer prognosis. DECV phenotypes outperformed conventional imaging markers as independent predictors of survival and were validated in an independent cohort. These DECV-based imaging phenotypes provide a robust, non-invasive biomarker for characterizing HGG heterogeneity and show potential to enhance prognostic stratification and guide personalized therapy.

Identifiers

PMID41998160
PMCPMC13275803

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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.