Evidence map›Paper›PMID 42865233›Full record

ArticleAnnals of clinical and translational neurology2026

Diffusion Basis Spectrum Imaging of Tissue Microstructure and Early Treatment in Multiple Sclerosis.

Apisit Kaewsanit, Aime Luna, Bradley Judge, Nicole Shelley, Karl Friedrichsen, Jayashree Rajamanickam, Zhude Tu, Yong Wang, Tammie L S Benzinger, Qing Wang and 1 more

Abstract read
In one paragraph

Article in Annals of clinical and translational 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
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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

11 authors.

Apisit KaewsanitRoy and Diana Vagelos Division of Biology & Biomedical Sciences, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0003-0796-338X
Aime LunaDepartment of Biomedical Engineering, McKelvey School of Engineering, Washington University in St. Louis, St. Louis, Missouri, USA.
Bradley JudgeDepartment of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.ORCID https://orcid.org/0009-0008-3052-5912
Nicole ShelleyDepartment of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.ORCID https://orcid.org/0009-0003-9607-9840
Karl FriedrichsenDepartment of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
Jayashree RajamanickamMallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
Zhude TuMallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
Yong WangMallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
Tammie L S BenzingerMallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
Qing WangMallinckrodt Institute of Radiology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.
Matthew R BrierDepartment of Neurology, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA.ORCID https://orcid.org/0000-0001-5987-8705

Funding

PET SPHINGOSINE-1-PHOSPHATE RECEPTOR 1 (S1PR1) RADIOTRACERS FOR MULTIPLE SCLEROSISR01NS103988 · NINDS · WASHINGTON UNIVERSITY · PI Tammie Lee Smith Benzinger, Zhude Tu · 2017 to 2026
$5.3M
Quantitative Endogenous MRI Imaging of Neuroinflammation in ADR01AG074909 · NIA · WASHINGTON UNIVERSITY · PI QING WANG · 2022 to 2026
$3.7M
PET and MRI Evaluation of Cerebral Inflammation and Metabolic Stress in Relapsing Multiple SclerosisK23NS128325 · NINDS · WASHINGTON UNIVERSITY · PI Matthew Ryan Brier · 2023 to 2026
$931k
National Multiple Sclerosis Society RG-2406-43174NIA NIH HHS R01 AG074909NIH HHS K23 NS128325NIH HHS R01 AG074909NIH HHS R01 NS103988NINDS NIH HHS K23 NS128325NINDS NIH HHS R01 NS103988The Laura Fund
6 · The paper itself

Abstract

objectiveConventional MRI cannot resolve the coexisting pathological processes within multiple sclerosis tissue. Diffusion Basis Spectrum Imaging decomposes the diffusion signal into fiber, cell, and hindered ratios indexing axonal integrity, cellularity, and extracellular space, respectively. We asked how these ratios differ between early relapsing and established non-relapsing disease, change with early treatment, and relate to disability, and secondarily, whether lesions form reproducible microstructural subtypes.

methodsThirty-seven participants underwent multi-shell diffusion MRI: 11 healthy controls, 15 treatment-naïve relapsing, and 11 non-relapsing patients. Thirteen were rescanned ~3 months after starting high-efficacy disease-modifying therapy. Metrics were extracted from normal-appearing gray and white matter and lesions (core, rim, and perilesional white matter); Gaussian mixture model clustering of per-lesion fiber, cell, and hindered ratios identified lesion subtypes.

resultsTreatment-naïve relapsing patients showed reduced normal-appearing white matter fiber (p = 0.04) and elevated hindered ratios (p = 0.02) versus controls. Lesions had lower fiber and cell ratios and higher hindered ratio than within-subject normal-appearing white matter (all p < 0.001). After treatment, lesional fiber ratio increased (p = 0.01) while lesional and gray matter cell ratios declined (both p = 0.02). Lesional cell ratio was higher in relapsing than non-relapsing patients at the core (p = 0.03) and rim (p = 0.04) but not perilesionally; treatment-related improvement was similar across compartments. Clustering yielded four reproducible subtypes (edematous-hypocellular, moderately cellular, actively inflamed, structurally preserved); the inflamed subtype predominated in relapsing and the edematous-hypocellular in non-relapsing disease.

interpretationDiffusion basis spectrum imaging distinguishes relapsing from non-relapsing disease by lesion-body cellularity and detects treatment-related changes in fiber and cell compartments. Reproducible, hypothesis-generating lesion subtypes support its use for in vivo lesion phenotyping.

Indexed as

diffusion MRImultiple sclerosiswhite matter lesion

Identifiers

PMID42865233
PMCPMC13659309

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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.