Evidence map›Paper›PMID 33981994›Full record

ArticleBrain communications2021

Traumatic brain injury: a comparison of diffusion and volumetric magnetic resonance imaging measures.

Niall J Bourke, Maria Yanez Lopez, Peter O Jenkins, Sara De Simoni, James H Cole, Pete Lally, Emma-Jane Mallas, Hui Zhang, David J Sharp

Open access · goldAbstract read
In one paragraph

Article in Brain communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.7field-weighted citation impact, top 17% of its field
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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
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  4. Probabilistic mapping and automated segmentation of human brainstem white matter bundles.Proceedings of the National Academy of Sciences of the United States of America · 2026
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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

9 authors at 2 institutions in 1 country.

Niall J BourkeDivision of Brain Sciences, Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Hammersmith Hospital, London, UK.ORCID https://orcid.org/0000-0001-6478-1430
Maria Yanez LopezDivision of Brain Sciences, Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Hammersmith Hospital, London, UK.ORCID https://orcid.org/0000-0001-5187-2501
Peter O JenkinsDivision of Brain Sciences, Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Hammersmith Hospital, London, UK.ORCID https://orcid.org/0000-0003-2060-6766
Sara De SimoniDivision of Brain Sciences, Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Hammersmith Hospital, London, UK.
James H ColeUCL Department of Computer Science, Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK.ORCID https://orcid.org/0000-0003-1908-5588
Pete LallyDivision of Brain Sciences, Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Hammersmith Hospital, London, UK.ORCID https://orcid.org/0000-0003-0075-0103
Emma-Jane MallasDivision of Brain Sciences, Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Hammersmith Hospital, London, UK.ORCID https://orcid.org/0000-0002-4050-0208
Hui ZhangUCL Department of Computer Science, Centre for Medical Image Computing, University College London, London WC1V 6LJ, UK.ORCID https://orcid.org/0000-0002-5426-2140
David J SharpDivision of Brain Sciences, Computational, Cognitive and Clinical Neuroimaging Laboratory, Imperial College London, Hammersmith Hospital, London, UK.
Hammersmith Hospital · GBUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cognitive impairment after traumatic brain injury remains hard to predict. This is partly because axonal injury, which is of fundamental importance, is difficult to measure clinically. Advances in MRI allow axonal injury to be detected after traumatic brain injury, but the most sensitive approach is unclear. Here, we compare the performance of diffusion tensor imaging, neurite orientation dispersion and density-imaging and volumetric measures of brain atrophy in the identification of white-matter abnormalities after traumatic brain injury. Thirty patients with moderate-severe traumatic brain injury in the chronic phase and 20 age-matched controls had T1-weighted and diffusion MRI. Neuropsychological tests of processing speed, executive functioning and memory were used to detect cognitive impairment. Extensive abnormalities in neurite density index and orientation dispersion index were observed, with distinct spatial patterns. Fractional anisotropy and mean diffusivity also indicated widespread abnormalities of white-matter structure. Neurite density index was significantly correlated with processing speed. Slower processing speed was also related to higher mean diffusivity in the corticospinal tracts. Lower white-matter volumes were seen after brain injury with greater effect sizes compared to diffusion metrics; however, volume was not sensitive to changes in cognitive performance. Volume was the most sensitive at detecting change between groups but was not specific for determining relationships with cognition. Abnormalities in fractional anisotropy and mean diffusivity were the most sensitive diffusion measures; however, neurite density index and orientation dispersion index may be more spatially specific. Lower neurite density index may be a useful metric for examining slower processing speed.

Indexed as

diffuse axonal injurydiffusion tensorneurite densityorientation dispersiontraumatic brain injury

Identifiers

PMID33981994
PMCPMC8105496
OpenAlexW3128579955

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.