Added Value of Tissue Level Brain Injury Criteria
Traumatic brain injury (TBI) is the leading cause of death and permanent impairment over the last decades. In both the severe and mild TBI, diffuse axonal injury (DAI) is the most common pathology. Computation of axon elongation by using finite element (FE) head model in numerical simulation can enl...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Society of Automotive Engineers of Japan, Inc.
2019-04-01
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| Series: | International Journal of Automotive Engineering |
| Online Access: | https://www.jstage.jst.go.jp/article/jsaeijae/10/2/10_20194103/_article/-char/ja |
| _version_ | 1797356801045299200 |
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| author | Caroline Deck Rémy Willinger |
| author_facet | Caroline Deck Rémy Willinger |
| author_sort | Caroline Deck |
| collection | DOAJ |
| description | Traumatic brain injury (TBI) is the leading cause of death and permanent impairment over the last decades. In both the severe and mild TBI, diffuse axonal injury (DAI) is the most common pathology. Computation of axon elongation by using finite element (FE) head model in numerical simulation can enlighten the DAI mechanism and help to establish advanced head injury criteria. The main objective of this study is to propose a brain injury criterion per age-class based on multiscale computation of axonal elongation of real world head trauma. The implementation of advanced skull mechanical properties and new medical imaging data such as fractional anisotropy and axonal fiber orientation from Diffuse Tensor Imaging (DTI) into the FE brain model was performed to improve the brain constitutive material law with more efficient heterogeneous anisotropic visco-hyper-elastic material law and enables it to compute axon elongation at the time of impact .Further, well-documented head trauma cases were simulated by using this finite element head model in order to derive head injury criteria for different injury mechanisms. Coming to brain injury, the head trauma database was divided into three different groups depending on victims’ age: under 30 years old, between 30 to 50 years old and over 50 years old. An extensive real-world head trauma simulation exercise including age-class analysis was performed on an advanced head FE model including the computation of axonal elongation. Based on the statistical analysis, axonal strain was the most relevant candidate parameter to predict moderate DAI. It was showed that the threshold value in terms of axonal strain for a 50% risk of moderate DAI decrease with the increase of victim’s age. Senior people seem to be more sensitive to moderate DAI than the other age-classes. |
| first_indexed | 2024-03-08T14:32:50Z |
| format | Article |
| id | doaj.art-46445ba47b294dbcb5243d9e3cf2ad8f |
| institution | Directory Open Access Journal |
| issn | 2185-0992 |
| language | English |
| last_indexed | 2024-03-08T14:32:50Z |
| publishDate | 2019-04-01 |
| publisher | Society of Automotive Engineers of Japan, Inc. |
| record_format | Article |
| series | International Journal of Automotive Engineering |
| spelling | doaj.art-46445ba47b294dbcb5243d9e3cf2ad8f2024-01-12T07:15:38ZengSociety of Automotive Engineers of Japan, Inc.International Journal of Automotive Engineering2185-09922019-04-0110219119610.20485/jsaeijae.10.2_191Added Value of Tissue Level Brain Injury CriteriaCaroline Deck0Rémy Willinger1The University of StrasbourgThe University of StrasbourgTraumatic brain injury (TBI) is the leading cause of death and permanent impairment over the last decades. In both the severe and mild TBI, diffuse axonal injury (DAI) is the most common pathology. Computation of axon elongation by using finite element (FE) head model in numerical simulation can enlighten the DAI mechanism and help to establish advanced head injury criteria. The main objective of this study is to propose a brain injury criterion per age-class based on multiscale computation of axonal elongation of real world head trauma. The implementation of advanced skull mechanical properties and new medical imaging data such as fractional anisotropy and axonal fiber orientation from Diffuse Tensor Imaging (DTI) into the FE brain model was performed to improve the brain constitutive material law with more efficient heterogeneous anisotropic visco-hyper-elastic material law and enables it to compute axon elongation at the time of impact .Further, well-documented head trauma cases were simulated by using this finite element head model in order to derive head injury criteria for different injury mechanisms. Coming to brain injury, the head trauma database was divided into three different groups depending on victims’ age: under 30 years old, between 30 to 50 years old and over 50 years old. An extensive real-world head trauma simulation exercise including age-class analysis was performed on an advanced head FE model including the computation of axonal elongation. Based on the statistical analysis, axonal strain was the most relevant candidate parameter to predict moderate DAI. It was showed that the threshold value in terms of axonal strain for a 50% risk of moderate DAI decrease with the increase of victim’s age. Senior people seem to be more sensitive to moderate DAI than the other age-classes.https://www.jstage.jst.go.jp/article/jsaeijae/10/2/10_20194103/_article/-char/ja |
| spellingShingle | Caroline Deck Rémy Willinger Added Value of Tissue Level Brain Injury Criteria International Journal of Automotive Engineering |
| title | Added Value of Tissue Level Brain Injury Criteria |
| title_full | Added Value of Tissue Level Brain Injury Criteria |
| title_fullStr | Added Value of Tissue Level Brain Injury Criteria |
| title_full_unstemmed | Added Value of Tissue Level Brain Injury Criteria |
| title_short | Added Value of Tissue Level Brain Injury Criteria |
| title_sort | added value of tissue level brain injury criteria |
| url | https://www.jstage.jst.go.jp/article/jsaeijae/10/2/10_20194103/_article/-char/ja |
| work_keys_str_mv | AT carolinedeck addedvalueoftissuelevelbraininjurycriteria AT remywillinger addedvalueoftissuelevelbraininjurycriteria |