Evidence map›Paper›PMID 41237161›Full record

ArticlePloS one2025

Impact of processing and analysis methodology on thalamic susceptibility assessment in multiple sclerosis.

Fahad Salman, Niels Bergsland, Michael G Dwyer, Jack A Reeves, Abhisri Ramesh, Dejan Jakimovski, Bianca Weinstock-Guttman, Robert Zivadinov, Ferdinand Schweser

Abstract read
In one paragraph

Article in PloS one, 2025. 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
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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

9 authors.

Fahad SalmanBuffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.ORCID https://orcid.org/0009-0000-3873-2301
Niels BergslandBuffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.ORCID https://orcid.org/0000-0002-7792-0433
Michael G DwyerBuffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.ORCID https://orcid.org/0000-0003-4684-4658
Jack A ReevesBuffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.
Abhisri RameshBuffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.
Dejan JakimovskiBuffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.ORCID https://orcid.org/0000-0001-7114-4958
Bianca Weinstock-GuttmanJacobs Neurological Institute, Buffalo, New York, United States of America.
Robert ZivadinovBuffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.
Ferdinand SchweserBuffalo Neuroimaging Analysis Center, Department of Neurology at the Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, The State University of New York, Buffalo, New York, United States of America.ORCID https://orcid.org/0000-0003-0399-9211

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStudies using quantitative susceptibility mapping (QSM) to investigate thalamic iron levels in people with multiple sclerosis (pwMS) have yielded inconsistent results. It has been speculated that cohort differences are responsible for these inconsistencies, leading to the phenomenological "early-rise late-decline" hypothesis, which posits that cohort age differences explain conflicting thalamic susceptibility findings. In a recent replication study, the authors failed to reproduce elevated thalamic susceptibility in pwMS previously reported by one of the only two QSM-based studies, despite matching cohort characteristics and processing, weakening the support for the phenomenological hypothesis.

objectiveTo investigate if the outcome of the recent replication study is robust with respect to different QSM algorithms and analysis methodologies.

methodsUsing the same MRI dataset as the previous replication study, we assessed thalamic susceptibility across 83 pwMS and 44 healthy controls. To comprehensively evaluate methodological variability, we tested combinations of three background field removal (BFR) algorithms using various regularization parameters, four dipole inversion algorithms, three reference regions, and two segmentation methods. Each unique combination of a BFR algorithm (with its specific parameter) and a dipole inversion algorithm constituted a distinct pipeline, yielding a total of 19,558 susceptibility maps across 154 different pipelines.

resultsThalamic susceptibility was lower in pwMS compared to controls independent of the chosen methodology, with differences in effect sizes primarily driven by the background field removal algorithms and their regularization parameters, reference region, and segmentation method. The impact of dipole inversion algorithms was minimal.

conclusionsOur study suggests high reproducibility of group-level clinical studies using QSM to study the thalamus in pwMS. In particular, methodological differences in processing and analysis are unlikely to explain contradicting findings of thalamic susceptibility in MS.

Indexed as

Image Processing, Computer-AssistedMagnetic Resonance ImagingMultiple SclerosisThalamusAdultAlgorithmsBrain MappingCase-Control StudiesDisease SusceptibilityFemaleHumansIronMaleMiddle AgedIron

Identifiers

PMID41237161
PMCPMC12617929

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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.