Evidence map›Paper›PMID 40443948›Full record

ArticleBrain communications2025

Sensitivity of diffusion tensor imaging to regional mixed cerebrovascular pathology.

Jennifer K Ferris, Julia Dahlby, Shie Rinat, Brian Greeley, Joel Ramirez, Sandra E Black, Lara A Boyd

Abstract read
In one paragraph

Article in Brain communications, 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

7 authors.

Jennifer K FerrisGraduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada  V6T 1Z3.ORCID https://orcid.org/0000-0003-3624-6996
Julia DahlbyGraduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada  V6T 1Z3.ORCID https://orcid.org/0000-0001-7854-9288
Shie RinatGraduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada  V6T 1Z3.
Brian GreeleyDepartment of Physical Therapy, University of British Columbia, Vancouver, Canada  V6T 1Z3.
Joel RamirezLC Campbell Cognitive Neurology Research Unit, Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Canada  M4N 3M5.ORCID https://orcid.org/0000-0002-5582-1776
Sandra E BlackLC Campbell Cognitive Neurology Research Unit, Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Canada  M4N 3M5.
Lara A BoydGraduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada  V6T 1Z3.ORCID https://orcid.org/0000-0002-2828-4549

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diffusion tensor imaging is a candidate biomarker in cerebrovascular disease. Yet, little is known about the sensitivity of diffusion tensor imaging to mixed forms of cerebrovascular pathology: stroke and white matter hyperintensities. We evaluated the sensitivity of diffusion tensor imaging to regional lesion load, considering both stroke and white matter hyperintensity lesions. 65 older adults and 39 individuals with chronic stroke underwent diffusion tensor imaging and comprehensive cerebrovascular lesion segmentation. We tested relationships between fractional anisotropy or mean diffusivity and cerebrovascular lesions with linear mixed effects regression. In older adults, tract microstructure related to white matter hyperintensity lesion load (fractional anisotropy:

Indexed as

cerebral small vessel diseasediffusion tensor imaginglesion volumestrokewhite matter hyperintensities

Identifiers

PMID40443948
PMCPMC12120440

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.