Abstract
Non-destructive measurement of acceleration-induced displacement fields within a closed object is a fundamental challenge. Inferences of how the brain deforms following skull impact have thus relied largely on indirect estimates and course-resolution cadaver studies. We developed a magnetic resonance technique to quantitatively identify the modes of displacement of an accelerating soft object relative to an object enclosing it, and applied it to study acceleration-induced brain deformation in human volunteers. We show that, contrary to the prevailing hypotheses of the field, the dominant mode of interaction between the brain and skull in mild head acceleration is one of sliding arrested by meninges.
Highlights
What happens to the brain when the skull accelerates? This question is central to understanding the most common forms of mild traumatic brain injury, but it is still not completely answered [1,2,3,4,5]
We identify the dominant modes of brain displacement relative to the skull through a method based upon principal component analysis of tagged magnetic resonance (MR) images
Demonstration of the method on model data The principal component algorithm was first applied to data from a model of a supported Kirchoff plate subjected to a uniform, instantaneously-applied, face loading, with the goal of highlighting problems associated with deriving displacement modes from images
Summary
What happens to the brain when the skull accelerates? This question is central to understanding the most common forms of mild traumatic brain injury, but it is still not completely answered [1,2,3,4,5]. The first class consists of quasi-static data obtained during image-guided neurosurgery [7]. These data provide estimates of boundary conditions, obtained through solution of inverse problems that are combined with a computational model to update three-dimensional maps of the brain as the brain is manipulated during surgery. While these data are useful for estimating effects of distant boundaries on displacement of a tumor mass during surgery, they are not optimized for the distinct task of predicting dynamic effects of brain/skull interactions
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
