Evidence map›Paper›PMID 38887966›Full record

ArticleAnnals of clinical and translational neurology2024

Diffusion kurtosis imaging-based habitat analysis identifies high-risk molecular subtypes and heterogeneity matching in diffuse gliomas.

Xiangli Yang, Wenju Niu, Kai Wu, Xiang Li, Heng Hou, Yan Tan, Xiaochun Wang, Guoqiang Yang, Lei Wang, Hui Zhang

Abstract read
In one paragraph

Article in Annals of clinical and translational neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

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0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

Who cites it

13 citing papers in PubMed.

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  10. Preoperative prediction of WHO/ISUP grade of ccRCC using intratumoral and peritumoral habitat imaging: multicenter study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Xiangli Yang *Department of Radiology, First Hospital of Shanxi Medical University, Taiyuan, 030001, China.ORCID 0009-0008-3009-0218
Wenju Niu *College of Medical Imaging, Shanxi Medical University, Taiyuan, 030001, China.
Kai WuDepartment of Information Management, First Hospital of Shanxi Medical University, Taiyuan, 030001, China.
Xiang LiCollege of Medical Imaging, Shanxi Medical University, Taiyuan, 030001, China.
Heng HouDepartment of Radiology, First Hospital of Shanxi Medical University, Taiyuan, 030001, China.
Yan TanDepartment of Radiology, First Hospital of Shanxi Medical University, Taiyuan, 030001, China.
Xiaochun WangDepartment of Radiology, First Hospital of Shanxi Medical University, Taiyuan, 030001, China.
Guoqiang YangDepartment of Radiology, First Hospital of Shanxi Medical University, Taiyuan, 030001, China.
Lei WangBeijing Tiantan Hospital, Capital Medical University, Beijing, 100050, China.ORCID 0000-0002-6916-704X
Hui ZhangDepartment of Radiology, First Hospital of Shanxi Medical University, Taiyuan, 030001, China.

Funding

Applied Basic Research Project of Shanxi Province, China 202303021211204National Natural Science Foundation of China 82071893National Natural Science Foundation of China 82371941National Natural Science Foundation of China U21A20386
6 · The paper itself

Abstract

objectiveHigh-risk types of diffuse gliomas in adults include isocitrate dehydrogenase (IDH) wild-type glioblastomas and grade 4 astrocytomas. Achieving noninvasive prediction of high-risk molecular subtypes of gliomas is important for personalized and precise diagnosis and treatment.

methodsWe retrospectively collected data from 116 patients diagnosed with adult diffuse gliomas. Multiple high-risk molecular markers were tested, and various habitat models and whole-tumor models were constructed based on preoperative routine and diffusion kurtosis imaging (DKI) sequences to predict high-risk molecular subtypes of gliomas. Feature selection and model construction utilized Least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM). Finally, the Wilcoxon rank-sum test was employed to explore the correlation between habitat quantitative features (intra-tumor heterogeneity score,ITH score) and heterogeneity, as well as high-risk molecular subtypes.

resultsThe results showed that the habitat analysis model based on DKI performed remarkably well (with AUC values reaching 0.977 and 0.902 in the training and test sets, respectively). The model's performance was further enhanced when combined with clinical variables. (The AUC values were 0.994 and 0.920, respectively.) Additionally, we found a close correlation between ITH score and heterogeneity, with statistically significant differences observed between high-risk and non-high-risk molecular subtypes.

interpretationThe habitat model based on DKI is an ideal means for preoperatively predicting high-risk molecular subtypes of gliomas, holding significant value for noninvasively alerting malignant gliomas and those with malignant transformation potential.

Indexed as

Brain NeoplasmsGliomaAdultAgedDiffusion Tensor ImagingFemaleHumansMaleMiddle AgedRetrospective StudiesYoung Adult

Identifiers

PMID38887966
PMCPMC11330218

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