IN VIVO MEASUREMENT OF BRAIN BIOMECHANICS

Washington University, Saint Louis MO

Investigators

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Abstract

DESCRIPTION (provided by applicant): PROJECT ABSTRACT: Computer models of brain biomechanics are needed to understand traumatic brain injury (TBI) and develop methods for prevention, but current computer models have not been fully validated, primarily due to the paucity of direct measurements of brain deformation. This lack of experimental confirmation represents an important barrier to progress. We have developed and applied MR tagging and MR elastography (MRE) methods to measure 2D brain motion and mechanical properties of the brain. In this renewal project we will extend our methods to 3D, and transition the results into computer models. We will acquire high-resolution 3D experimental data on brain deformation in human subjects to address basic questions on the biomechanics of TBI and to accelerate development of validated, reliable computer models. The project is driven by the need to validate simulations, and it will clarify the roles of key features of the brain. Three specific aims are proposed: Aim 1: Measure 3D relative motion between the brain and skull, and estimate 3D strain fields in live human and cadaver brains, during mild linear and angular head acceleration. Aim 2: Characterize 3D wave propagation and assess the effects of residual stress, fiber stretch, fiber-matrix interaction, and interfaces on wave propagation in the live human and ex vivo ovine brain. Aim 3: Compare 3D displacement and strain fields quantitatively to the predictions of a computer model of brain biomechanics, and assess the importance of variations in anatomy and material properties. In Aim 1 we will address the question: What are the roles of tethering and supporting structures (vessels and meninges) in the brain's response to skull acceleration? In Aim 2, we ask how these structures, as well as residual stress and anisotropy, affect shear wave propagation in the brain. In Aim 3, we will test directly how well simulations can predict brain motion, and we will use simulation to ask how individual variations in anatomy affect brain biomechanics and susceptibility to TBI. Key contributions of this project will be new data and analysis techniques for validation of computer models of TBI, enabled by the project team's technology developments in imaging of 3D brain motion, automated image segmentation and registration, and mathematical modeling of the brain and skull. The direct integration of computer modeling with acquisition of experimental data from MR tagging and MR elastography will accelerate development of reliable, accurate simulations. At the end of the project we will have: (1) computer models validated against our data that will allow visualization and quantitative prediction of the 3D strain experienced by the brain during selected acceleration/impacts; (2) publicly available data for others to build and validate new computer models of TBI.