Brain white matter model of orthotropic viscoelastic properties in frequency domain

Xuehai Wu, John G. Georgiadis, Assimina A. Pelegri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Finite element analysis is used to study brain axonal injury and develop Brain White Matter (BWM) models while accounting for both the strain magnitude and the strain rate. These models are becoming more sophisticated and complicated due to the complex nature of the BMW composite structure with different material properties for each constituent phase. State-of-the-art studies, focus on employing techniques that combine information about the local axonal directionality in different areas of the brain with diagnostic tools such as Diffusion-Weighted Magnetic Resonance Imaging (Diffusion-MRI). The diffusion-MRI data offers localization and orientation information of axonal tracks which are analyzed in finite element models to simulate virtual loading scenarios. Here, a BMW biphasic material model comprised of axons and neuroglia is considered. The model’s architectural anisotropy represented by a multitude of axonal orientations, that depend on specific brain regions, adds to its complexity. During this effort, we develop a finite element method to merge microscale Representative Volume Elements (RVEs) with orthotropic frequency domain viscoelasticity to an integrated macro-scale BWM finite element model, which incorporates local axonal orientation. Previous studies of this group focused on building RVEs that combined different volume fractions of axons and neuroglia and simulating their anisotropic viscoelastic properties. Via the proposed model, we can assign material properties and local architecture on each element based on the information from the orientation of the axonal traces. Consecutively, a BWM finite element model is derived with fully defined both material properties and material orientation. The frequency-domain dynamic response of the BMW model is analyzed to simulate larger scale diagnostic modalities such as MRI and MRE.

Original languageEnglish (US)
Title of host publicationBiomedical and Biotechnology Engineering
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791859407
DOIs
StatePublished - Jan 1 2019
EventASME 2019 International Mechanical Engineering Congress and Exposition, IMECE 2019 - Salt Lake City, United States
Duration: Nov 11 2019Nov 14 2019

Publication series

NameASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
Volume3

Conference

ConferenceASME 2019 International Mechanical Engineering Congress and Exposition, IMECE 2019
CountryUnited States
CitySalt Lake City
Period11/11/1911/14/19

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering

Keywords

  • Brain white matter
  • Computational modeling
  • Frequency
  • Neuron
  • Viscoelastic

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