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From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury
The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomech...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7990483/ https://www.ncbi.nlm.nih.gov/pubmed/33454735 http://dx.doi.org/10.1093/brain/awaa336 |
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author | Donat, Cornelius K Yanez Lopez, Maria Sastre, Magdalena Baxan, Nicoleta Goldfinger, Marc Seeamber, Reneira Müller, Franziska Davies, Polly Hellyer, Peter Siegkas, Petros Gentleman, Steve Sharp, David J Ghajari, Mazdak |
author_facet | Donat, Cornelius K Yanez Lopez, Maria Sastre, Magdalena Baxan, Nicoleta Goldfinger, Marc Seeamber, Reneira Müller, Franziska Davies, Polly Hellyer, Peter Siegkas, Petros Gentleman, Steve Sharp, David J Ghajari, Mazdak |
author_sort | Donat, Cornelius K |
collection | PubMed |
description | The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomechanical forces and patterns of white matter injuries, associated with persistent diffusion MRI abnormalities, is poorly understood. This limits the ability to predict the severity of head injuries and the design of appropriate protection. Our previously developed human finite element model of head injury predicted the location of post-traumatic neurodegeneration. A similar rat model now allows us to experimentally test whether strain patterns calculated by the model predicts in vivo MRI and histology changes. Using a controlled cortical impact, mild and moderate injuries (1 and 2 mm) were performed. Focal and axonal injuries were quantified with volumetric and diffusion 9.4 T MRI at 2 weeks post injury. Detailed analysis of the corpus callosum was conducted using multi-shell diffusion MRI and histopathology. Microglia and astrocyte density, including process parameters, along with white matter structural integrity and neurofilament expression were determined by quantitative immunohistochemistry. Linear mixed effects regression analyses for strain and strain rate with the employed outcome measures were used to ascertain how well immediate biomechanics could explain MRI and histology changes. The spatial pattern of mechanical strain and strain rate in the injured cortex shows good agreement with the probability maps of focal lesions derived from volumetric MRI. Diffusion metrics showed abnormalities in the corpus callosum, indicating white matter changes in the segments subjected to high strain, as predicted by the model. The same segments also exhibited a severity-dependent increase in glia cell density, white matter thinning and reduced neurofilament expression. Linear mixed effects regression analyses showed that mechanical strain and strain rate were significant predictors of in vivo MRI and histology changes. Specifically, strain and strain rate respectively explained 33% and 28% of the reduction in fractional anisotropy, 51% and 29% of the change in neurofilament expression and 51% and 30% of microglia density changes. The work provides evidence that strain and strain rate in the first milliseconds after injury are important factors in determining patterns of glial and axonal injury and serve as experimental validators of our computational model of traumatic brain injury. Our results provide support for the use of this model in understanding the relationship of biomechanics and neuropathology and can guide the development of head protection systems, such as airbags and helmets. |
format | Online Article Text |
id | pubmed-7990483 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-79904832021-03-31 From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury Donat, Cornelius K Yanez Lopez, Maria Sastre, Magdalena Baxan, Nicoleta Goldfinger, Marc Seeamber, Reneira Müller, Franziska Davies, Polly Hellyer, Peter Siegkas, Petros Gentleman, Steve Sharp, David J Ghajari, Mazdak Brain Original Articles The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomechanical forces and patterns of white matter injuries, associated with persistent diffusion MRI abnormalities, is poorly understood. This limits the ability to predict the severity of head injuries and the design of appropriate protection. Our previously developed human finite element model of head injury predicted the location of post-traumatic neurodegeneration. A similar rat model now allows us to experimentally test whether strain patterns calculated by the model predicts in vivo MRI and histology changes. Using a controlled cortical impact, mild and moderate injuries (1 and 2 mm) were performed. Focal and axonal injuries were quantified with volumetric and diffusion 9.4 T MRI at 2 weeks post injury. Detailed analysis of the corpus callosum was conducted using multi-shell diffusion MRI and histopathology. Microglia and astrocyte density, including process parameters, along with white matter structural integrity and neurofilament expression were determined by quantitative immunohistochemistry. Linear mixed effects regression analyses for strain and strain rate with the employed outcome measures were used to ascertain how well immediate biomechanics could explain MRI and histology changes. The spatial pattern of mechanical strain and strain rate in the injured cortex shows good agreement with the probability maps of focal lesions derived from volumetric MRI. Diffusion metrics showed abnormalities in the corpus callosum, indicating white matter changes in the segments subjected to high strain, as predicted by the model. The same segments also exhibited a severity-dependent increase in glia cell density, white matter thinning and reduced neurofilament expression. Linear mixed effects regression analyses showed that mechanical strain and strain rate were significant predictors of in vivo MRI and histology changes. Specifically, strain and strain rate respectively explained 33% and 28% of the reduction in fractional anisotropy, 51% and 29% of the change in neurofilament expression and 51% and 30% of microglia density changes. The work provides evidence that strain and strain rate in the first milliseconds after injury are important factors in determining patterns of glial and axonal injury and serve as experimental validators of our computational model of traumatic brain injury. Our results provide support for the use of this model in understanding the relationship of biomechanics and neuropathology and can guide the development of head protection systems, such as airbags and helmets. Oxford University Press 2021-01-17 /pmc/articles/PMC7990483/ /pubmed/33454735 http://dx.doi.org/10.1093/brain/awaa336 Text en © The Author(s) (2021). 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 Donat, Cornelius K Yanez Lopez, Maria Sastre, Magdalena Baxan, Nicoleta Goldfinger, Marc Seeamber, Reneira Müller, Franziska Davies, Polly Hellyer, Peter Siegkas, Petros Gentleman, Steve Sharp, David J Ghajari, Mazdak From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury |
title | From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury |
title_full | From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury |
title_fullStr | From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury |
title_full_unstemmed | From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury |
title_short | From biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury |
title_sort | from biomechanics to pathology: predicting axonal injury from patterns of strain after traumatic brain injury |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7990483/ https://www.ncbi.nlm.nih.gov/pubmed/33454735 http://dx.doi.org/10.1093/brain/awaa336 |
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