Evidence map›Paper›PMID 37343344›Full record

ArticleNeuroImage. Clinical2023

Personalized estimates of morphometric similarity in multiple sclerosis and neuromyelitis optica spectrum disorders.

Jie Sun, Wenjin Zhao, Yingying Xie, Fuqing Zhou, Lin Wu, Yuxin Li, Haiqing Li, Yongmei Li, Chun Zeng, Xuemei Han and 2 more

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2023. 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
0.3field-weighted citation impact, top 40% of its field
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 citations in OpenAlex.

  1. Article
  2. Article
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

12 authors at 6 institutions in 1 country.

Jie SunDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
Wenjin ZhaoDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
Yingying XieDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China.
Fuqing ZhouDepartment of Radiology, The First Afliated Hospital, Nanchang University, Nanchang 330006, Jiangxi Province, China; Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi Province, China.
Lin WuDepartment of Radiology, The First Afliated Hospital, Nanchang University, Nanchang 330006, Jiangxi Province, China; Neuroimaging Lab, Jiangxi Province Medical Imaging Research Institute, Nanchang 330006, Jiangxi Province, China.
Yuxin LiDepartment of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China.
Haiqing LiDepartment of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China.
Yongmei LiDepartment of Radiology, The First Afliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Chun ZengDepartment of Radiology, The First Afliated Hospital of Chongqing Medical University, Chongqing 400016, China.
Xuemei HanDepartment of Neurology, China-Japan Union Hospital of Jilin University, Changchun 130031, Jilin Province, China.
Yaou LiuDepartment of Radiology, Beijing Tiantan Hospital, Capital Medical University, No.119, The West Southern 4th Ring Road, Fengtai District, Beijing 100070, China.
Ningnannan ZhangDepartment of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China. Electronic address: znnn2010@sina.com.
Tianjin Medical University General Hospital · CNFudan University · CNNanchang University · CNCapital Medical University · CNJilin University · CNThe Affiliated Yongchuan Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain morphometric alterations involve multiple brain regions on progression of the disease in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) and exhibit age-related degenerative changes during the pathological aging. Recent advance in brain morphometry as measured using MRI have leveraged Person-Based Similarity Index (PBSI) approach to assess the extent of within-diagnosis similarity or heterogeneity of brain neuroanatomical profiles between individuals of healthy populations and validate in neuropsychiatric disorders. Brain morphometric changes throughout the lifespan would be invaluable for understanding regional variability of age-related structural degeneration and the substrate of inflammatory demyelinating disease. Here, we aimed to quantify the neuroanatomical profiles with PBSI measures of cortical thickness (CT) and subcortical volumes (SV) in 263 MS, 207 NMOSD, and 338 healthy controls (HC) from six separate central datasets (aged 11-80). We explored the between-group comparisons of PBSI measures, as well as the advancing age and sex effects on PBSI measures. Compared to NMOSD, MS showed a lower extent of within-diagnosis similarity. Significant differences in regional contributions to PBSI score were observed in 29 brain regions between MS and NMOSD (P < 0.05/164, Bonferroni corrected), of which bilateral cerebellum in MS and bilateral parahippocampal gyrus in NMOSD represented the highest divergence between the two patient groups, with a high similarity effect within each group. The PBSI scores were generally lower with advancing age, but their associations showed different patterns depending on the age range. For MS, CT profiles were significantly negatively correlated with age until the early 30 s (ρ = -0.265, P = 0.030), while for NMOSD, SV profiles were significantly negatively correlated with age with 51 year-old and older (ρ = -0.365, P = 0.008). The current study suggests that PBSI approach could be used to quantify the variation in brain morphometric changes in CNS inflammatory demyelinating disease, and exhibited a greater neuroanatomical heterogeneity pattern in MS compared with NMOSD. Our results reveal that, as an MR marker, PBSI may be sensitive to distribute the disease-associated grey matter diversity and complexity. Disease-driven production of regionally selective and age stage-dependency changes in the neuroanatomical profile of MS and NMOSD should be considered to facilitate the prediction of clinical outcomes and assessment of treatment responses.

Indexed as

Multiple SclerosisNeuromyelitis OpticaBrainGray MatterHumansMagnetic Resonance ImagingMiddle AgedCortical thicknessMultiple SclerosisNeuromyelitis optica spectrum disordersPerson-based similarity indexSubcortical volume

Identifiers

PMID37343344
PMCPMC10509529
OpenAlexW4381033531

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.