High linear and angular accelerations of the skull can lead to rapid deformation of brain tissue and subsequent traumatic brain injury (TBI), but the precise mechanisms of TBI remain incompletely understood. Computer simulations of head-brain biomechanics offer enormous potential for improved understanding and prevention of TBI. However simulations must be complemented by biomechanical measurements to parameterize and evaluate the underlying mathematical models.
The nonlinear, anisotropic, viscoelastic, heterogeneous character of brain tissue, and the intricate connections between the brain and skull all play important roles in the brain’s response to skull acceleration. Studies of animal brains and ex vivo brain tissue have led to important insights, but the measurements of the response of the intact human brain are necessary and complementary. On the other hand, efforts to understand the motion of the human brain in vivo are complicated by the fact that it is delicate, hidden, and well-protected by the skull.
I will describe MR imaging techniques to characterize brain deformation, estimate brain material properties, and illuminate the boundary conditions between brain and skull, with the objective of improving the ability to model and simulate TBI.
Philip V. (Phil) Bayly is The Lee Hunter Distinguished Professor of Mechanical Engineering and Chair of the Department of Mechanical Engineering and Materials Science at Washington University in St. Louis. Dr. Bayly earned an A.B. in Engineering Science from Dartmouth College, an M.S. in Engineering from Brown University, and a Ph.D. in Mechanical Engineering from Duke University.
Before pursuing his doctorate, Bayly worked as research engineer for the Shriners Hospitals and as a design engineer for Pitney Bowes. He has been a member of the faculty at Washington University since 1993, and Chair since 2008. His research involves the study of nonlinear dynamic phenomena in mechanical and biological systems. He is particularly interested in the use of imaging technology and image processing to understanding the mechanics and material properties of biological tissues and cells.
His research has been funded by the National Science Foundation, the Whitaker Foundation, and the National Institutes of Health.