A computational model for traumatic brain injury based on an axonal injury criterion

Abstract

Traumatic brain injury (TBI) is a debilitating injury that affects millions of people in the United States. It is caused by an external mechanical stimulus to the head, such as from blast loading, impacts, or rapid accelerations. One of the most common pathological features of TBI is damage to the neural axons in the white matter. This type of damage is classified as diffuse axonal injury (DAI). The goal of this work is to develop a modeling framework that can be used to predict the degree and location of DAI. We apply a multi-scale modeling approach to couple the cellular mechanisms of injury to the deformations of the brain tissue. The injury is defined at the cellular level through an axonal strain injury criterion that is based on the stretch injury response of neural axons, and the white matter is modeled at the tissue level with an anisotropic, hyper-viscoelastic constitutive model. The structural orientation and fiber dispersion of the neural axons is incorporated through the use of diffusion tensor imaging (DTI), which provides the link between the cellular and tissue levels. We also develop a novel approach for quantifying the extent of axonal damage in the fiber tracts through the use of a white matter atlas. The injury response of several white matter regions is studied under biaxial stretch, and it is shown that the inclusion of anisotropy into a material model for white matter has a significant effect on the predicted injury locations. The modeling framework is also extended to a 2-D full head finite element model to estimate the degree of axonal damage in a real-life ice hockey incident that resulted in concussive injury. Through this analysis, we demonstrate the ability of our modeling framework to estimate the probability of diffuse axonal injury for a given loading condition to the head. Our modeling framework provides a platform for studying the development of traumatic brain injury and can be applied to develop new injury prevention and mitigation strategies for TBI.