Citation

Wu T, Antona-makoshi J, Alshareef A, Giudice JS, Panzer MB. J. Neurotrauma 2019; ePub(ePub): ePub.

Affiliation

University of Virginia, Center for Applied Biomechanics, 4040 Lewis and Clark Dr., Charlottesville, Virginia, United States, 22911; panzer@virginia.edu.

Copyright

(Copyright © 2019, Mary Ann Liebert Publishers)

DOI

10.1089/neu.2019.6576

PMID

31382861

Abstract

Scaling methods are used to relate animal exposure data to humans by determining equivalent biomechanical impact conditions that result in similar tissue-level mechanics for different species. However, existing scaling methods for traumatic brain injury (TBI) do not account for the anatomical and morphological complexity of the brains for different species and have not been validated based on accurate anatomy and realistic material properties. In this study, the relationship between the head impact condition and brain tissue deformation was investigated using human, baboon, and macaque brain finite element (FE) models, which featured macroscale and mesoscale anatomical details. The objective was to evaluate existing scaling methods in predicting similar biomechanical responses in the different species using both idealized and real-world head impact pulses. A second objective was to develop a new method to improve how animal data is scaled to humans. As previously found in humans, the animal's brain response to the rotational head motion was well characterized by single-degree-of-freedom (sDOF) mechanical systems with resonance at certain natural frequency, and this concept was leveraged to develop a new TBI scaling method based the natural frequency of the sDOF models representing each species. Previously described biomechanical scaling methods based on mass or inertia ratios were poor predictors of equivalent strain. The novel frequency-based scaling method was an improved approach to scaling the equivalent loading conditions. The findings of this study enable better interpretation of mechanical-trauma responses obtained from animal data to the human, thus effectively advance the development of human injury criteria and contribute towards the mitigation of TBI.

Language: en

Keywords

ANIMAL STUDIES; AXONAL INJURY; FINITE ELEMENT MODELS; TRAUMATIC BRAIN INJURY