Evidence map›Paper›PMID 42236621›Full record

ArticleJournal of neurology2026

Ultra-low-field MRI for bedside imaging of severe multiple sclerosis.

Niels Bergsland, Alex Burnham, Michael G Dwyer, Alex Bartnik, Ferdinand Schweser, Cheryl Kennedy, Ashley Tranquille, Mehak Semy, Ella Schnee, Suyog Pol and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Niels BergslandBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 77 Goodell Street, Suite 450, Buffalo, NY, 14203, USA.
Alex BurnhamThe Boston Home, Dorchester, MA, USA.
Michael G DwyerBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 77 Goodell Street, Suite 450, Buffalo, NY, 14203, USA.
Alex BartnikBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 77 Goodell Street, Suite 450, Buffalo, NY, 14203, USA.
Ferdinand SchweserBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 77 Goodell Street, Suite 450, Buffalo, NY, 14203, USA.
Cheryl KennedyBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 77 Goodell Street, Suite 450, Buffalo, NY, 14203, USA.
Ashley TranquilleBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 77 Goodell Street, Suite 450, Buffalo, NY, 14203, USA.
Mehak SemyBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 77 Goodell Street, Suite 450, Buffalo, NY, 14203, USA.
Ella SchneeBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 77 Goodell Street, Suite 450, Buffalo, NY, 14203, USA.
Suyog PolCenter for Biomedical Imaging, University at Buffalo, State University of New York, Buffalo, NY, USA.
Aaron KrawczykCenter for Biomedical Imaging, University at Buffalo, State University of New York, Buffalo, NY, USA.
David Young-HongThe Boston Home, Dorchester, MA, USA.
Svetlana EckertDepartment of Neurology, Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
David HojnackiDepartment of Neurology, Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
Christine ReillyThe Boston Home, Dorchester, MA, USA.
Ralph H B BenedictDepartment of Neurology, Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
Bianca Weinstock-GuttmanDepartment of Neurology, Jacobs Comprehensive MS Treatment and Research Center, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
Robert ZivadinovBuffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, 77 Goodell Street, Suite 450, Buffalo, NY, 14203, USA. rz4@buffalo.edu.ORCID http://orcid.org/0000-0002-7799-1485

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSevere multiple sclerosis (MS) presents challenges for clinical research due to patient mobility constraints and specialized care needs. Traditional MRI studies often exclude this population but portable, ultra-low-field (ULF) MRI at 0.064 T enables bedside imaging.

objectivesTo (i) compare ULF MRI volumetry with standard 3 T, (ii) assess the capability of portable ULF MRI in characterizing severe MS.

methodsThis prospective study enrolled two cohorts. Cohort 1 included healthy controls (HC) and people with MS (pwMS). Cohort 2 enrolled individuals with progressive MS, with either severe or less severe MS. Both cohorts underwent ULF MRI while those in Cohort 1 were also scanned on 3 T MRI. Clinical assessments included disability and cognition. MRI data was processed using both conventional (e.g., SIENAX) and AI-driven (e.g., WMH-SynthSeg) techniques. Group comparisons and MRI-clinical associations were assessed.

resultsCohort 1 included 14 HCs (39 ± 13 years, 11 females) and 33 pwMS (32 ± 10 years, 24 females). Cohort 2 included 24 severe MS individuals (62 ± 10, 15 females) and 16 less severe MS individuals (61 years ± 11, 8 females). MRI passed quality control except for scans from 2 individuals in Cohort 2. In Cohort 1, 3 T and ULF MRI showed robust disease differences, with strongest effect sizes for ULF MRI-derived whole brain (partial η

conclusionPortable, ULF MRI is feasible in pwMS and provides insights into late-stage neurodegeneration in severe MS.

Indexed as

BrainMagnetic Resonance ImagingMultiple SclerosisAdultCohort StudiesFemaleHumansMaleMiddle AgedProspective StudiesSeverity of Illness IndexAtrophyCorticalDisabilityGray matterHigh-field MRIMultiple sclerosisSevere MSThalamusUltra-low-field MRI

Identifiers

PMID42236621
PMCPMC13234000

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.