Evidence map›Paper›PMID 33257929›Full record

ArticleBrain : a journal of neurology2021

Detecting axonal injury in individual patients after traumatic brain injury.

Amy E Jolly, Maria Bălăeţ, Adriana Azor, Daniel Friedland, Stefano Sandrone, Neil S N Graham, Karl Zimmerman, David J Sharp

Abstract read
In one paragraph

Article in Brain : a journal of neurology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
60citing papers in PubMed, 1 pooled it
–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

60 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Observational
  5. Article
  6. Traumatic Microhemorrhages Are Not Synonymous With Axonal Injury.Annals of clinical and translational neurology · 2026
    Article
  7. Review
  8. Sub-Networks of the Brain RHuman brain mapping · 2026
    Article
  9. Article
  10. Article
  11. Review
  12. Observational
  13. Article
  14. Article
  15. Article
  16. Revisiting the critical roles of reactive microglia in traumatic brain injury.International journal of surgery (London, England) · 2025
    Review
  17. Article
  18. Review
  19. Article
  20. 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.

Amy E JollyClinical, cognitive and computational neuroimaging laboratory (C3NL), Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.
Maria BălăeţClinical, cognitive and computational neuroimaging laboratory (C3NL), Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.
Adriana AzorClinical, cognitive and computational neuroimaging laboratory (C3NL), Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.
Daniel FriedlandClinical, cognitive and computational neuroimaging laboratory (C3NL), Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.
Stefano SandroneClinical, cognitive and computational neuroimaging laboratory (C3NL), Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.
Neil S N GrahamClinical, cognitive and computational neuroimaging laboratory (C3NL), Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.
Karl ZimmermanClinical, cognitive and computational neuroimaging laboratory (C3NL), Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.
David J SharpClinical, cognitive and computational neuroimaging laboratory (C3NL), Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.

Funding

Department of Health NIHR-RP-011-048
6 · The paper itself

Abstract

Poor outcomes after traumatic brain injury (TBI) are common yet remain difficult to predict. Diffuse axonal injury is important for outcomes, but its assessment remains limited in the clinical setting. Currently, axonal injury is diagnosed based on clinical presentation, visible damage to the white matter or via surrogate markers of axonal injury such as microbleeds. These do not accurately quantify axonal injury leading to misdiagnosis in a proportion of patients. Diffusion tensor imaging provides a quantitative measure of axonal injury in vivo, with fractional anisotropy often used as a proxy for white matter damage. Diffusion imaging has been widely used in TBI but is not routinely applied clinically. This is in part because robust analysis methods to diagnose axonal injury at the individual level have not yet been developed. Here, we present a pipeline for diffusion imaging analysis designed to accurately assess the presence of axonal injury in large white matter tracts in individuals. Average fractional anisotropy is calculated from tracts selected on the basis of high test-retest reliability, good anatomical coverage and their association to cognitive and clinical impairments after TBI. We test our pipeline for common methodological issues such as the impact of varying control sample sizes, focal lesions and age-related changes to demonstrate high specificity, sensitivity and test-retest reliability. We assess 92 patients with moderate-severe TBI in the chronic phase (≥6 months post-injury), 25 patients in the subacute phase (10 days to 6 weeks post-injury) with 6-month follow-up and a large control cohort (n = 103). Evidence of axonal injury is identified in 52% of chronic and 28% of subacute patients. Those classified with axonal injury had significantly poorer cognitive and functional outcomes than those without, a difference not seen for focal lesions or microbleeds. Almost a third of patients with unremarkable standard MRIs had evidence of axonal injury, whilst 40% of patients with visible microbleeds had no diffusion evidence of axonal injury. More diffusion abnormality was seen with greater time since injury, across individuals at various chronic injury times and within individuals between subacute and 6-month scans. We provide evidence that this pipeline can be used to diagnose axonal injury in individual patients at subacute and chronic time points, and that diffusion MRI provides a sensitive and complementary measure when compared to susceptibility weighted imaging, which measures diffuse vascular injury. Guidelines for the implementation of this pipeline in a clinical setting are discussed.

Indexed as

Diffusion Magnetic Resonance ImagingAdultAnisotropyAxonsBrain Injuries, TraumaticFemaleHumansImage Processing, Computer-AssistedMaleMiddle AgedReproducibility of ResultsWhite Matterdiagnostic pipelinediffuse axonal injurydiffusion tensor imagingtraumatic brain injury

Identifiers

PMID33257929
PMCPMC7880666

What OpenQuestion holds

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LicenceCC BY
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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.