Evidence map›Paper›PMID 39169546›Full record

ArticleHuman brain mapping2024

Pooled analysis of multiple sclerosis findings on multisite 7 Tesla MRI: Protocol and initial observations.

Daniel M Harrison, Seongjin Choi, Rohit Bakshi, Erin S Beck, Alexis M Callen, Renxin Chu, Jonadab Dos Santos Silva, Dumitru Fetco, Matthew Greenwald, Shannon Kolind and 11 more

Abstract readMulticenter Study
In one paragraph

Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Imaging Outcomes for Phase 2 Trials Targeting Compartmentalized Inflammation.Multiple sclerosis (Houndmills, Basingstoke, England) · 2024
    Review
  3. 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

21 authors.

Daniel M HarrisonDepartment of Neurology, University of Maryland School of Medicine, Baltimore, Maryland, USA.ORCID 0000-0001-8707-2004
Seongjin ChoiDepartment of Neurology, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Rohit BakshiDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Erin S BeckDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Alexis M CallenDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Renxin ChuDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Jonadab Dos Santos SilvaDepartment of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Dumitru FetcoMcConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.
Matthew GreenwaldTranslational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA.
Shannon KolindDepartment of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.
Sridar NarayananMcConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.
Serhat V OkarTranslational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA.
Molly K QuattrucciDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Daniel S ReichTranslational Neuroradiology Section, National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA.
David RudkoMcConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada.
Bretta Russell-SchulzDepartment of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.
Matthew K SchindlerDepartment of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Shahamat TauhidDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Anthony TraboulseeDepartment of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.
Zachary VavasourDepartment of Medicine (Neurology), University of British Columbia, Vancouver, British Columbia, Canada.
Jonathan D ZurawskiDepartment of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Funding

Multimodal MRI in Multiple SclerosisZIANS003119 · NINDS · NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE · PI REICH, DANIEL · 2010 to 2025
$53.4M
In vivo assessment of meningeal inflammation and its clinical impact in multiple sclerosis by 7 Tesla MRIR01NS104403 · NINDS · UNIVERSITY OF MARYLAND BALTIMORE · PI HARRISON, DANIEL M · 2018 to 2022
$3.1M
Pooled analysis of multiple sclerosis findings on multi-site 7 Tesla MRIR01NS122980 · NINDS · UNIVERSITY OF MARYLAND BALTIMORE · PI HARRISON, DANIEL M · 2021 to 2025
$2.4M
Grey Matter of Lesions and Neurodegeration in Multiple Sclerosis on 7-Telsa MRIK23NS072366 · NINDS · UNIVERSITY OF MARYLAND BALTIMORE · PI HARRISON, DANIEL M · 2013 to 2017
$928k
Bristol-Myers SquibbCenter for Neuroinflammation and Experimental Therapeutics at the University of PennsylvaniaCIHR FRN 84367CIHR PJT153005Conrad N. Hilton Foundation 20220EMD SeronoIntramural NIH HHS ZIA NS003119National MS SocietyNational Multiple Sclerosis Society FG-2208-40289National Multiple Sclerosis Society TA-2109-38412NIH HHS ZIANS003119NINDS NIH HHS K23 NS072366NINDS NIH HHS K23NS072366NINDS NIH HHS R01 NS104403NINDS NIH HHS R01NS104403NINDS NIH HHS R01 NS122980NINDS NIH HHS R01NS122980NovartisRace to Erase MSRoche
6 · The paper itself

Abstract

Although 7 T MRI research has contributed much to our understanding of multiple sclerosis (MS) pathology, most prior data has come from small, single-center studies with varying methods. In order to truly know if such findings have widespread applicability, multicenter methods and studies are needed. To address this, members of the North American Imaging in MS (NAIMS) Cooperative worked together to create a multicenter collaborative study of 7 T MRI in MS. In this manuscript, we describe the methods we have developed for the purpose of pooling together a large, retrospective dataset of 7 T MRIs acquired in multiple MS studies at five institutions. To date, this group has contributed five-hundred and twenty-eight 7 T MRI scans from 350 individuals with MS to a common data repository, with plans to continue to increase this sample size in the coming years. We have developed unified methods for image processing for data harmonization and lesion identification/segmentation. We report here our initial observations on intersite differences in acquisition, which includes site/device differences in brain coverage and image quality. We also report on the development of our methods and training of image evaluators, which resulted in median Dice Similarity Coefficients for trained raters' annotation of cortical and deep gray matter lesions, paramagnetic rim lesions, and meningeal enhancement between 0.73 and 0.82 compared to final consensus masks. We expect this publication to act as a resource for other investigators aiming to combine multicenter 7 T MRI datasets for the study of MS, in addition to providing a methodological reference for all future analysis projects to stem from the development of this dataset.

Indexed as

Magnetic Resonance ImagingMultiple SclerosisAdultBrainFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedRetrospective Studies7 Tmulticentermultiple sclerosis

Identifiers

PMID39169546
PMCPMC11339124

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.