Evidence map›Paper›PMID 40800808›Full record

ArticleImaging neuroscience (Cambridge, Mass.)2025

Microstructure-informed brain tissue classification using clustering of quantitative MRI measures.

Sharada Balaji, Marek Obajtek, Irene M Vavasour, Adam Dvorak, Guillaume Gilbert, Poljanka Johnson, Roger Tam, Cornelia Laule, David K B Li, Anthony Traboulsee and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Imaging neuroscience (Cambridge, Mass.), 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
–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

12 authors.

Sharada BalajiPhysics and Astronomy, University of British Columbia, Vancouver, BC, Canada.ORCID https://orcid.org/0000-0002-6232-8488
Marek ObajtekPhysics and Astronomy, University of British Columbia, Vancouver, BC, Canada.
Irene M VavasourRadiology, University of British Columbia, Vancouver, BC, Canada.
Adam DvorakPhysics and Astronomy, University of British Columbia, Vancouver, BC, Canada.
Guillaume GilbertMR Clinical Science, Philips Canada, Missisauga, ON, Canada.
Poljanka JohnsonMedicine (Neurology), University of British Columbia, Vancouver, BC, Canada.
Roger TamRadiology, University of British Columbia, Vancouver, BC, Canada.
Cornelia LaulePhysics and Astronomy, University of British Columbia, Vancouver, BC, Canada.
David K B LiRadiology, University of British Columbia, Vancouver, BC, Canada.
Anthony TraboulseeMedicine (Neurology), University of British Columbia, Vancouver, BC, Canada.
Alex MacKayPhysics and Astronomy, University of British Columbia, Vancouver, BC, Canada.
Shannon H KolindPhysics and Astronomy, University of British Columbia, Vancouver, BC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional tissue classification approaches in vivo use voxel intensities from conventional clinical magnetic resonance (MR) images for segmentation, which does not incorporate information about specific aspects of microstructure. With the Clustering for Anatomical Quantification and Evaluation (CAQE) framework, quantitative MRI measures can be used to classify tissue based only on microstructural features with no spatial enforcement, and pathological changes in disease can be evaluated. In this study, maps of whole-brain myelin water fraction, microscopic fractional anisotropy, and tissue heterogeneity were used to classify brain tissue in 25 healthy participants. CAQE was then applied to 25 participants with multiple sclerosis (MS), where tissue classifications indicated areas of increased demyelination and axonal injury in white matter compared with a healthy average tissue classification. Severity scores were derived from tissue classifications to quantify diffuse white matter damage, and correlated significantly with cognitive ability in MS. The CAQE framework can be adapted for other applications and extended to use different quantitative MRI measures.

Indexed as

clusteringmyelin water imagingtensor-valued diffusiontissue classificationtissue microstructure

Identifiers

PMID40800808
PMCPMC12319851

What OpenQuestion 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 OpenQuestion graph.