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3D Modeling of the Lateral Ventricles and Histological Characterization of Periventricular Tissue in Humans and Mouse
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Towards microstructure-informed material models for human brain tissue.

S Budday1, M Sarem2, L Starck2

  • 1Department of Mechanical Engineering, Friedrich-Alexander-University Erlangen-Nürnberg (FAU), Erlangen 91058, Germany.

Acta Biomaterialia
|December 31, 2019
PubMed
Summary
This summary is machine-generated.

This study links brain tissue microstructure to its mechanical properties, revealing how cell count, myelin, and proteoglycans affect stiffness and viscosity. Understanding these links can improve diagnostic markers for brain diseases.

Keywords:
Biomechanical testingHuman brain tissueHyperelasticityMaterial modelingMicrostructureOgden model

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Area of Science:

  • Biophysics
  • Neuroscience
  • Materials Science

Background:

  • Brain tissue mechanics are crucial for development, aging, and disease.
  • Current material models for brain tissue are often phenomenological and lack microstructural correlation.
  • Understanding brain tissue heterogeneity is key for predicting its mechanical behavior.

Purpose of the Study:

  • To establish general relations between brain tissue microstructure and its mechanical behavior.
  • To develop microstructurally motivated constitutive equations for human brain tissue.
  • To identify potential diagnostic markers for neurological conditions based on tissue mechanics.

Main Methods:

  • Histological staining to analyze microstructure in different brain regions (cortex, basal ganglia, corona radiata, corpus callosum).
  • Mechanical testing (simple shear, compression, tension) to determine regional stiffness and viscosity.
  • Correlation analysis between microstructural components (cell count, myelin, proteoglycans, lipids) and mechanical properties.

Main Results:

  • Negative correlation between cell count and stiffness.
  • Positive correlation between myelin content and stiffness.
  • Negative correlation between proteoglycan content and stiffness.
  • Positive correlation between lipid and proteoglycan content and viscosity.

Conclusions:

  • Brain tissue mechanics are directly influenced by microstructural composition.
  • Microstructure-informed models can capture regional heterogeneities in brain tissue.
  • Brain tissue stiffness and viscosity may serve as early diagnostic markers for diseases like CTE, Alzheimer's, Parkinson's, and MS.