Evidence map›Paper›PMID 39613905›Full record

ArticleInsights into imaging2024

Identification of neural alterations in patients with Crohn's disease with a novel multiparametric brain MRI-based radiomics model.

Ruo-Nan Zhang, Yang-di Wang, Hai-Jie Wang, Yao-Qi Ke, Xiao-di Shen, Li Huang, Jin-Jiang Lin, Wei-Tao He, Chen Zhao, Zhou-Lei Li and 4 more

Abstract read
In one paragraph

Article in Insights into imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

14 authors.

Ruo-Nan Zhang *Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
Yang-di Wang *Department of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
Hai-Jie WangShanghai Key Laboratory of Magnetic Resonance, East China Normal University, Dongchuan Road, Minhang District, Shanghai, 200241, People's Republic of China.
Yao-Qi KeDepartment of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
Xiao-di ShenDepartment of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
Li HuangDepartment of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
Jin-Jiang LinDepartment of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
Wei-Tao HeDepartment of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
Chen ZhaoMR Research Collaboration Team, Siemens Healthineers, Guangzhou, People's Republic of China.
Zhou-Lei LiDepartment of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
Ren MaoDepartment of Gastroenterology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China.
Ye-Jun WangYouth Innovation Team of Medical Bioinformatics, Shenzhen University Medical School, Shenzhen, 518060, People's Republic of China.
Guang YangShanghai Key Laboratory of Magnetic Resonance, East China Normal University, Dongchuan Road, Minhang District, Shanghai, 200241, People's Republic of China. gyang@phy.ecnu.edu.cn.
Xue-Hua LiDepartment of Radiology, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, People's Republic of China. lxueh@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-7476-2644

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2023B1515020070Fundamental Research Funds for the Central Universities, Sun Yat-sen University 24ykqb003National Natural Science Foundation of China 82070680National Natural Science Foundation of China 82270693
6 · The paper itself

Abstract

objectivesGut-brain axis dysfunction has emerged as a key contributor to the pathogenesis of Crohn's disease (CD). The elucidation of neural alterations may provide novel insights into its management. We aimed to develop a multiparameter brain MRI-based radiomics model (RM) for characterizing neural alterations in CD patients and to interpret these alterations using multiomics traits.

methodsThis prospective study enrolled 230 CD patients and 46 healthy controls (HCs). Participants voluntarily underwent brain MRI and psychological assessment (n = 155), blood metabolomics analysis (n = 260), and/or fecal 16S rRNA sequencing (n = 182). The RM was developed using 13 features selected from 13,870 first-order features extracted from multiparameter brain MRI in training cohort (CD, n = 75; HCs, n = 32) and validated in test cohort (CD, n = 34; HCs, n = 14). Multiomics data (including gut microbiomics, blood metabolomics, and brain radiomics) were compared between CD patients and HCs.

resultsIn the training cohort, area under the receiver operating characteristic curve (AUC) of RM for distinguishing CD patients from HCs was 0.991 (95% confidence interval (CI), 0.975-1.000). In test cohort, RM showed an AUC of 0.956 (95% CI, 0.881-1.000). CD-enriched blood metabolites such as triacylglycerol (TAG) exhibited significant correlations with both brain features detected by RM and CD-enriched microbiota (e.g., Veillonella). One notable correlation was found between Veillonella and Ctx-Lh-Middle-Temporal-CBF-p90 (r = 0.41). Mediation analysis further revealed that dysbiosis, such as of Veillonella, may regulate the blood flow in the middle temporal cortex through TAG.

conclusionWe developed a multiparameter MRI-based RM that characterized the neural alterations of CD patients, and multiomics data offer potential evidence to support the validity of our model. Our study may offer clues to help provide potential therapeutic targets. CRITICAL RELEVANCE STATEMENT: Our brain-gut axis study developed a novel model using multiparameter MRI and radiomics to characterize brain changes in patients with Crohn's disease. We validated this model's effectiveness using multiomics data, making it a potential biomarker for better patient management. KEY POINTS: Utilizing multiparametric MRI and radiomics techniques could unveil Crohn's disease's neurophenotype. The neurophenotype radiomics model is interpreted using multiomics data. This model may serve as a novel biomarker for Crohn's disease management.

Indexed as

Brain MRICrohn’s diseaseGut-brain axisMultiomicsRadiomics

Identifiers

PMID39613905
PMCPMC11607295

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