A multiscale computational approach to estimating axonal damage under inertial loading of the head.

A computational modeling framework is developed to estimate the location and degree of diffuse axonal injury (DAI) under inertial loading of the head. DAI is one of the most common pathological features of traumatic brain injury and is characterized by damage to the neural axons in the white matter regions of the brain. We incorporate the microstructure of the white matter (i.e., the fiber orientations and fiber dispersion) through the use of diffusion tensor imaging (DTI), and model the white matter with an anisotropic, hyper-viscoelastic constitutive model. The extent of DAI is estimated using an axonal strain injury criterion. A novel injury analysis method is developed to quantify the degree of axonal damage in the fiber tracts of the brain and identify the tracts that are at the greatest risk for functional failure. Our modeling framework is applied to analyze DAI in a real-life ice hockey incident that resulted in concussive injury. To simulate the impact, two-dimensional finite element (FE) models of the head were constructed from detailed MRI and DTI data and validated using available human head experimental data. Acceleration loading curves from accident reconstruction data were then applied to the FE models. The rotational (rather than translational) accelerations were shown to dominate the injury response, which is consistent with previous studies. Through this accident reconstruction, we demonstrate a conceptual framework to estimate the degree of axonal injury in the fiber tracts of the human brain, enabling the future development of relationships between computational simulation and neurocognitive impairment.

An axonal strain injury criterion for traumatic brain injury.

Computational models are often used as tools to study traumatic brain injury. The fidelity of such models depends on the incorporation of an appropriate level of structural detail, the accurate representation of the material behavior, and the use of an appropriate measure of injury. In this study, an axonal strain injury criterion is used to estimate the probability of diffuse axonal injury (DAI), which accounts for a large percentage of deaths due to brain trauma and is characterized by damage to neural axons in the deep white matter regions of the brain. We present an analytical and computational model that treats the white matter as an anisotropic, hyperelastic material. Diffusion tensor imaging is used to incorporate the structural orientation of the neural axons into the model. It is shown that the degree of injury that is predicted in a computational model of DAI is highly dependent on the incorporation of the axonal orientation information and the inclusion of anisotropy into the constitutive model for white matter.