Evidence map›Paper›PMID 40307202›Full record

ArticleKorean journal of radiology2025

Multi-Parameter MRI for Evaluating Glymphatic Impairment and White-Matter Abnormalities and Discriminating Refractory Epilepsy in Children.

Lu Qiu, Miaoyan Wang, Surui Liu, Bo Peng, Ying Hua, Jianbiao Wang, Xiaoyue Hu, Anqi Qiu, Yakang Dai, Haoxiang Jiang

Abstract read
In one paragraph

Article in Korean journal of radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  4. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Lu Qiu *Department of Diagnostic Radiology, Affiliated Children's Hospital of Jiangnan University, Wuxi, China.ORCID https://orcid.org/0000-0001-5510-9589
Miaoyan Wang *Department of Diagnostic Radiology, Affiliated Children's Hospital of Jiangnan University, Wuxi, China.ORCID https://orcid.org/0009-0008-8203-4277
Surui LiuSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.ORCID https://orcid.org/0009-0004-1105-6082
Bo PengSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China.ORCID https://orcid.org/0000-0002-6360-6574
Ying HuaDepartment of Neurology, Affiliated Children's Hospital of Jiangnan University, Wuxi, China.ORCID https://orcid.org/0000-0001-5723-4121
Jianbiao WangDepartment of Neurology, Affiliated Children's Hospital of Jiangnan University, Wuxi, China.ORCID https://orcid.org/0009-0005-3916-1543
Xiaoyue HuDepartment of Neurology, Affiliated Children's Hospital of Jiangnan University, Wuxi, China.ORCID https://orcid.org/0000-0001-8465-819X
Anqi QiuDepartment of Health Technology and Informatics, Hong Kong Polytechnic University, Hong Kong.ORCID https://orcid.org/0000-0002-0215-6338
Yakang DaiSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, China. daiyk@sibet.ac.cn.ORCID https://orcid.org/0000-0003-3357-1638
Haoxiang JiangDepartment of Diagnostic Radiology, Affiliated Children's Hospital of Jiangnan University, Wuxi, China. jianghaoxiang@jiangnan.edu.cn.ORCID https://orcid.org/0000-0003-1191-1398

Funding

Hong Kong global STEM scholar schemeHong Kong Polytechnic UniversityKey R&D Program of Jiangsu Science and Technology Project BE2022049-2Postgraduate Research & Practice Innovation Program of Jiangsu Province KYCX24_2647STI 2030-Major Project 2022ZD0209000Wuxi Municipal Health Commission's 'Double Hundred' Medical Health Young Elite Talent Project BJ2023088Wuxi Municipal Health Commission's Youth Project Q202275Wuxi Municipal Science and Technology Bureau's Medical and Health Tackling Project Y20232012
6 · The paper itself

Abstract

objectiveTo explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). MATERIALS AND

methodsWe retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson's partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation.

resultsIn the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement,

conclusionPediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Indexed as

Drug Resistant EpilepsyGlymphatic SystemMagnetic Resonance ImagingChildFemaleHumansLeukoencephalopathiesMaleRetrospective StudiesWhite MatterGlymphatic systemMachine-learningMulti-parameterPediatric refractory epilepsyWhite-matter abnormalities

Identifiers

PMID40307202
PMCPMC12055269

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.