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Validation of Embedded Element Method in the Prediction of White Matter Disruption in Concussions

[+] Author Affiliations
Harsha T. Garimella, Reuben H. Kraft

Pennsylvania State University, University Park, PA

Paper No. IMECE2016-67785, pp. V003T04A045; 10 pages
doi:10.1115/IMECE2016-67785
From:
  • ASME 2016 International Mechanical Engineering Congress and Exposition
  • Volume 3: Biomedical and Biotechnology Engineering
  • Phoenix, Arizona, USA, November 11–17, 2016
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5053-4
  • Copyright © 2016 by ASME

abstract

A better understanding of the axonal injury would help us develop improved diagnostic tools, protective measures, and rehabilitation treatments. Computational modeling coupled with advanced neuroimaging techniques might be a promising tool for this purpose. However, before the models can be used for real life applications, they need to be validated and cross-verified with real life scenarios to establish the credibility of the model. In this work, progress has been made in validating a human head finite element model with embedded axonal fiber tractography (using embedded element method) using pre- and post-diffusion tensor imaging data (DTI) of a concussed athlete. Fractional anisotropy (FA) was used to determine the microstructural changes during injury. These damaged locations correlated well with the damaged locations observed from the finite element model. This work could be characterized as a first step towards the development of a more comprehensively validated human head finite element model.

Copyright © 2016 by ASME

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