Evidence map›Paper›PMID 40593438›Full record

ReviewInsights into imaging2025

Developments in MRI radiomics research for vascular cognitive impairment.

Xuezhi Chen, Xianting Luo, Liang Chen, Hao Liu, Xiaoping Yin, Zhiying Chen

Abstract readReview
In one paragraph

Review in Insights into imaging, 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. Review
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

6 authors.

Xuezhi ChenUniversity of Shanghai for Science and Technology, Shanghai, China.
Xianting LuoDepartment of Imaging, Affiliated Hospital of Jiujiang University, Jiujiang, China.
Liang ChenDepartment of Imaging, Affiliated Hospital of Jiujiang University, Jiujiang, China.
Hao LiuDepartment of Imaging, Affiliated Hospital of Jiujiang University, Jiujiang, China.
Xiaoping YinDepartment of Neurology, Affiliated Hospital of Jiujiang University, Jiujiang, China.
Zhiying ChenDepartment of Neurology, Affiliated Hospital of Jiujiang University, Jiujiang, China. zychenjj@jju.edu.cn.ORCID http://orcid.org/0000-0002-8481-3927

Funding

Jiangxi Provincial Administration of Traditional Chinese Medicine science and technology plan project 2022A322 to ZYCJiangxi Provincial Health Commission Science and Technology Plan project 202311506 to ZYCthe National Natural Science Foundation of China 81960221 to XPYthe National Natural Science Foundation of China 82260249 to XPYYouth Foundation of Natural Science Foundation of Jiangxi Province 20224BAB216045 to ZYC
6 · The paper itself

Abstract

Vascular cognitive impairment (VCI) is an umbrella term for diseases associated with cognitive decline induced by substantive brain damage following pathological changes in the cerebrovascular system. The primary clinical manifestations include behavioral abnormalities and diminished learning and memory cognitive functions. If the location and extent of brain injury are not identified early and therapeutic interventions are not promptly administered, it may lead to irreversible cognitive impairment. Therefore, the early diagnosis of VCI is crucial for its prevention and treatment. Prior to the onset of cognitive impairment in VCI, magnetic resonance imaging (MRI) radiomics can be utilized for early assessment and diagnosis, thereby guiding clinicians in providing precise treatment for patients, which holds significant potential for development. This article reviews the classification of VCI, the concept of radiomics, the application of MRI radiomics in VCI, and the limitations of radiomics in the context of advancements in its application within the central nervous system. CRITICAL RELEVANCE STATEMENT: This article explores how MRI radiomics can be used to detect VCI early, enhancing clinical radiology practice by offering a reliable method for prediction, diagnosis, and identification, which also promotes standardization in research and integration of disciplines. KEY POINTS: MRI radiomics can predict VCI early. MRI radiomics can diagnose VCI. MRI radiomics distinguishes VCI from Alzheimer's disease.

Indexed as

Artificial intelligenceMagnetic resonance imagingRadiomicsVascular cognitive impairmentWhite matter lesions

Identifiers

PMID40593438
PMCPMC12214101

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.