Visco-hyperelastic characterization of human brain white matter micro-level constituents in different strain rates.

In this study, we propose a computational characterization technique for obtaining the material properties of axons and extracellular matrix (ECM) in human brain white matter. To account for the dynamic behavior of the brain tissue, data from time-dependent relaxation tests of human brain white matt...

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Published in:Medical & Biological Engineering & Computing Vol. 58; no. 9; pp. 2107 - 2119
Main Authors: Ramzanpour, Mohammadreza, Hosseini-Farid, Mohammad, McLean, Jayse, Ziejewski, Mariusz, Karami, Ghodrat
Format: equations & formulas pictorial research tables/charts Journal Article
Published: Springer Nature Sep2020
Online Access:View this record in EBSCOhost
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      dt: Sep2020
      vid: 58
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s11517-020-02228-3
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        atl: Visco-hyperelastic characterization of human brain white matter micro-level constituents in different strain rates.
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        au:
          Ramzanpour, Mohammadreza
          Hosseini-Farid, Mohammad
          McLean, Jayse
          Ziejewski, Mariusz
          Karami, Ghodrat
        affil: Department of Mechanical Engineering, North Dakota State University, Fargo, ND, USA
      sug:
        subj:
          Brain Physiology
          Biomedical Engineering
          Extracellular Space
          Finite Element Analysis
          Kinematics
          Nerve Fibers Physiology
          Elasticity
          Models, Biological
          Animals
          Stress, Mechanical
          Brain Anatomy and Histology
          Computer Simulation
          Nerve Fibers
          Viscosity
          Extracellular Space Physiology
      ab: In this study, we propose a computational characterization technique for obtaining the material properties of axons and extracellular matrix (ECM) in human brain white matter. To account for the dynamic behavior of the brain tissue, data from time-dependent relaxation tests of human brain white matter in different strain rates are extracted and formulated by a visco-hyperelastic constitutive model consisting of the Ogden hyperelastic model and the Prony series expansion. Through micromechanical finite element simulation, a derivative-free optimization framework designed to minimize the difference between the numerical and experimental data is used to identify the material properties of the axons and ECM. The Prony series expansion parameters of axons and ECM are found to be highly affected by the Prony series expansion coefficients of the brain white matter. The optimal parameters of axons and ECM are verified through micromechanical simulation by comparing the averaged numerical response with that of the experimental data. Moreover, the initial shear modulus and the reduced shear modulus of the axons are found for different strain rates of 0.0001, 0.01, and 1 s-1. Consequently, first- and second-order regressions are used to find relations for the prediction of the shear modulus at the intermediate strain rates. Graphical Abstract The applied procedure for characterization of brain white matter micro-level constituents. The macro-level experimental data in different strain rates are used in the context of simulation-based optimization to obtain the properties of axons and extracellular matrix material.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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