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Detecting axonal injury in individual patients after traumatic brain injury

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...

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Autores principales: Jolly, Amy E, Bălăeţ, Maria, Azor, Adriana, Friedland, Daniel, Sandrone, Stefano, Graham, Neil S N, Zimmerman, Karl, Sharp, David J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880666/
https://www.ncbi.nlm.nih.gov/pubmed/33257929
http://dx.doi.org/10.1093/brain/awaa372
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author Jolly, Amy E
Bălăeţ, Maria
Azor, Adriana
Friedland, Daniel
Sandrone, Stefano
Graham, Neil S N
Zimmerman, Karl
Sharp, David J
author_facet Jolly, Amy E
Bălăeţ, Maria
Azor, Adriana
Friedland, Daniel
Sandrone, Stefano
Graham, Neil S N
Zimmerman, Karl
Sharp, David J
author_sort Jolly, Amy E
collection PubMed
description 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.
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spelling pubmed-78806662021-02-17 Detecting axonal injury in individual patients after traumatic brain injury Jolly, Amy E Bălăeţ, Maria Azor, Adriana Friedland, Daniel Sandrone, Stefano Graham, Neil S N Zimmerman, Karl Sharp, David J Brain Original Articles 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. Oxford University Press 2020-11-30 /pmc/articles/PMC7880666/ /pubmed/33257929 http://dx.doi.org/10.1093/brain/awaa372 Text en © The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Jolly, Amy E
Bălăeţ, Maria
Azor, Adriana
Friedland, Daniel
Sandrone, Stefano
Graham, Neil S N
Zimmerman, Karl
Sharp, David J
Detecting axonal injury in individual patients after traumatic brain injury
title Detecting axonal injury in individual patients after traumatic brain injury
title_full Detecting axonal injury in individual patients after traumatic brain injury
title_fullStr Detecting axonal injury in individual patients after traumatic brain injury
title_full_unstemmed Detecting axonal injury in individual patients after traumatic brain injury
title_short Detecting axonal injury in individual patients after traumatic brain injury
title_sort detecting axonal injury in individual patients after traumatic brain injury
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880666/
https://www.ncbi.nlm.nih.gov/pubmed/33257929
http://dx.doi.org/10.1093/brain/awaa372
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