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Virginia Tech

Traumatic Brain Injury Mechanisms in the Gottingen Minipig in Response to Two Unique Input Modes

Abstract

dc:description.abstract

Traumatic brain injury (TBI) continues to be a widespread problem in the United States with approximately 1.7 million occurrences annually [1]. Current automotive crash test standards use the Head Injury Criterion (HIC) [2] to assess head injury potential, but this metric does not relate an impact to underlying damage. For an injury metric to effectively predict TBI, it is crucial to relate level of impact to resulting injury. The research presented in this dissertation explains the development and repeatability of two novel injury devices, impact response characterization over the course of 24 hours in the Gottingen minipig and the relationships between metabolite changes, underlying disruption, and impact kinematics, and the characterization of impact response over the course of 72 hours. The translation-input and combined translation and rotation-input injury devices were shown to be repeatable, minimizing the number of animals needed for testing. Impact response over the course of 24 hours showed axonal disruption through immunostaining and proton magnetic resonance spectroscopy. The translation-input injury group metabolite analyses revealed the initial stages of glutamate excitotoxicity while the combined-input injury group showed a clear pathway for glutamate excitotoxicity. Numerous correlative relationships and potential underlying disruption predictors were found between metabolites, immunostaining, and kinematics. The most promising predictor combination for the translation-input injury device was N-acetylaspartylglutamate/Scyllo at 24 hours compared to 1 hour and linear speed for predicting underlying light neurofilament disruption. For the combined-input injury device, the strongest predictor combination was Glutamine/N-acetylaspartylglutamate at 24 hours compared to baseline and angular acceleration for predicting underlying light neurofilament disruption. Statistically significant predictors were found between Glutamate+Glutamine/Total Creatine at 24 hours compared to baseline and all kinematics and injury metrics with an angular component for predicting heavy neurofilament disruption. Analyses over the course of 72 hours revealed persistent axonal disruption and metabolite perturbations. Overall, this dissertation and the complementary parts of this project have many societal implications. Due to the high incidence of traumatic brain injury, there is a need for prevention, mitigation, and treatment strategies. Developing a new injury metric will help improve prevention strategies, especially in the automotive, sporting, and military environments. 1 Faul, M., Xu, L., Wald, M. M., and Coronado, V. G. (2010). Traumatic Brain Injury in the United States. Atlanta, GA: Centers for Disease Control and Prevention, National Center for Injury Prevention and Control. 2 Versace, J. (1971). A Review of the Severity Index. SAE Technical Paper. No. 710881

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Biomedical Engineering
Department dc:contributor.department
Biomedical Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2015

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Fievisohn, Elizabeth Mary
Chair dc:contributor.committeechair
  • Hardy, Warren N.
Committee members dc:contributor.committeemember
  • Duma, Stefan M.
  • Galloway, Matthew P.
  • Gennarelli, Thomas A.
  • VandeVord, Pamela J.

Subjects

dc:subject × 5

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:6504
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/64280

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Fievisohn, Elizabeth Mary. Traumatic Brain Injury Mechanisms in the Gottingen Minipig in Response to Two Unique Input Modes. doctoral thesis, Virginia Tech, 2015. http://hdl.handle.net/10919/64280