Evidence map›Paper›PMID 41282678›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Normal appearing white matter and disability in multiple sclerosis.

Valentin N Stepanov, Santiago Coelho, Benjamin Ades-Aron, Jenny Chen, Timothy M Shepherd, Dmitry S Novikov, Ilya Kister, Els Fieremans

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Valentin N StepanovBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.ORCID 0000-0003-0007-8054
Santiago CoelhoBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.ORCID 0000-0002-1039-4803
Benjamin Ades-AronBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.ORCID 0000-0001-5077-3341
Jenny ChenBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.
Timothy M ShepherdBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.ORCID 0000-0003-0232-1636
Dmitry S NovikovBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.ORCID 0000-0002-4213-3050
Ilya KisterDepartment of Neurology, NYU Langone Medical Center, New York, NY, USA.ORCID 0000-0003-3549-949X
Els FieremansBernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, NY, USA.ORCID 0000-0002-1384-8591

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Li Feng · 2014 to 2026
$19.3M
Mesoscopic Biomarkers of Neurodegeneration with Diffusion MRIR01NS088040 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FIEREMANS, ELS, NOVIKOV, DMITRY S · 2014 to 2023
$5.2M
Random Matrix Theory-Based Noise Removal in MRIR01EB027075 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FIEREMANS, ELS, NOVIKOV, DMITRY S · 2019 to 2022
$2.7M
Quantifying Demyelination and Axonal Loss with Diffusion MRIR21NS081230 · NINDS · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI FIEREMANS, ELS, KIM, SUNGHEON GENE · 2012 to 2013
$561k
Fast High-Resolution Microstructure Diffusion MRI Exploiting Data RedundancyK99EB036080 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI COELHO, SANTIAGO · 2024 to 2025
$222k
NIBIB NIH HHS K99 EB036080NIBIB NIH HHS P41 EB017183NIBIB NIH HHS R01 EB027075NINDS NIH HHS R01 NS088040NINDS NIH HHS R21 NS081230
6 · The paper itself

Abstract

Background and Objectives: Multiple sclerosis (MS) is characterized by lesions and atrophy on conventional MRI, yet these often fail to explain disability. Diffusion MRI (dMRI) detects microstructural injury with diffusion tensor (DTI) and kurtosis imaging (DKI) offering sensitivity, and Standard Model Imaging (SMI) providing biologically interpretable parameters. We evaluated whether these clinically feasible dMRI metrics are associated with disability beyond volumetric and lesion measures, and whether effects arise from normal-appearing white matter (NAWM). Methods: This cross-sectional study included MS patients who underwent 3T MRI including T1- and T2-weighted and a ~7-minute multi-shell dMRI protocol. Brain volumes (gray matter, white matter, thalamus) and lesion load were derived using FreeSurfer and Icobrain. Diffusion metrics included radial diffusivity (RD) from DTI, radial kurtosis (RK) from DKI, intra-axonal water fraction ( Results: Ninety-two patients (68 women; mean age 48, range 24-73; median disease duration 14 years; EDSS 3.0, range 0-8.5) were included. dMRI revealed widespread associations with all clinical measures that persisted after lesion exclusion, implicating NAWM. Functional outcomes were tract-specific: 9HPT correlated with corticospinal tract and optic radiations (RD ρ=0.45; RK ρ=-0.44; Discussion: dMRI detects NAWM injury underlying functional impairment beyond atrophy and lesions. SMI adds specificity (

Indexed as

Brain VolumeDiffusion Kurtosis Imaging (DKI)Diffusion Tensor Imaging (DTI)Disease ProgressionMicrostructural PathologyMultiple Sclerosis (MS)Standard Model of Diffusion (SMI)

Identifiers

PMID41282678
PMCPMC12637795

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.