Evidence map›Paper›PMID 41882380›Full record

ArticleBrain structure & function2026

Longitudinal visualization tools for advanced characterization of multiple sclerosis lesions using diffusion MRI and magnetization transfer imaging metrics.

Erick Hernandez-Gutierrez, Ricardo Coronado-Leija, Manon Edde, François Rheault, Matthieu Dumont, Jean-Christophe Houde, Muhamed Barakovic, Stefano Magon, Alonso Ramirez-Manzanares, Maxime Descoteaux

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Article in Brain structure & function, 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

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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

10 authors.

Erick Hernandez-GutierrezSherbrooke Connectivity Imaging Lab (SCIL), University of Sherbrooke, Sherbrooke, QC, Canada. erick.hernandez.gutierrez@usherbrooke.ca.
Ricardo Coronado-LeijaNew York University School of Medicine (NYU), New York, NY, USA.
Manon EddeSherbrooke Connectivity Imaging Lab (SCIL), University of Sherbrooke, Sherbrooke, QC, Canada.
François RheaultSherbrooke Connectivity Imaging Lab (SCIL), University of Sherbrooke, Sherbrooke, QC, Canada.
Matthieu DumontImeka Solutions Inc., Sherbrooke, QC, Canada.
Jean-Christophe HoudeImeka Solutions Inc., Sherbrooke, QC, Canada.
Muhamed BarakovicPharma Research and Early Development, Neuroscience and Rare Diseases Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Stefano MagonPharma Research and Early Development, Neuroscience and Rare Diseases Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland.
Alonso Ramirez-ManzanaresComputer Science Department, Centro de Investigación en Matemáticas (CIMAT), Guanajuato, GT, Mexico.
Maxime DescoteauxSherbrooke Connectivity Imaging Lab (SCIL), University of Sherbrooke, Sherbrooke, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding how white matter microstructure supports functional network organization requires tools capable of characterizing tissue properties across multiple complementary metrics and spatial scales simultaneously. White matter pathology disrupts the relationship between microstructural tissue organization and network-level function in spatial and temporal patterns that reveal fundamental principles of white matter organization. Multiple sclerosis (MS) exemplifies this principle through heterogeneous lesion formation, demyelination, and axonal injury that disrupts white matter at multiple scales and in multiple ways. Advanced neuroimaging techniques, particularly diffusion MRI (dMRI) and magnetization transfer imaging (MTI), provide sensitive measures of distinct microstructural properties. However, the high dimensionality and longitudinal complexity of multi-metric datasets pose significant challenges for analyzing how these tissue changes relate to white matter network organization. We introduce five complementary visualization tools designed to integrate fixel-based multi-tensor, magnetization transfer, and isotropic volume fraction across multiple time points while preserving the spatial organization of white matter tracts and tissue compartments. The framework enables investigation of structure-function relationships at multiple scales: patient-level network disruption patterns, tract-specific vulnerability, bundle-section-specific regional variations, lesion-specific microstructural dynamics, and microstructural characteristics in tissue regions where lesions subsequently develop. Applied to longitudinal datasets from multiple MS patients over five scanning periods, the visualization framework provides a descriptive characterization of microstructural heterogeneity and permits hypothesis-generating exploration of white matter structure-function relationships. The framework provides tools for exploratory investigation of microstructural heterogeneity at multiple scales and provides research tools for hypothesis-generating examination of white matter structure-function relationships in pathology. It has potential applications for understanding how tissue-level microstructural changes vary across patients, bundles, and lesions. The framework is designed as a research visualization tool for hypothesis generation and should not be interpreted as providing clinical prognostic utility for which further validation against clinical outcomes is needed.

Indexed as

BrainDiffusion Magnetic Resonance ImagingMultiple SclerosisWhite MatterFemaleHumansImage Processing, Computer-AssistedLongitudinal StudiesDiffusion MRILongitudinal visualizationMagnetization transferMultiple sclerosisMulti-tensorTractography

Identifiers

PMID41882380

What Socratic holds

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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 Socratic graph.