Material and Structural Modeling Aspects of Brain Tissue Deformation under Dynamic Loads

Area of Science:

• Biomechanics
• Computational Modeling
• Neuroscience

Background:

• Material modeling of brain tissue faces challenges due to scattered and poorly defined material data.
• Existing methods for determining brain characteristics lack standardization, hindering reliable numerical simulations.
• Technological advancements necessitate a review of structural and material modeling approaches for brain tissue under dynamic loading.

Purpose of the Study:

• To assess various approaches to structural and material modeling of brain tissue under dynamic loading.
• To identify key directions for the development of robust numerical brain models.
• To develop and validate a numerical brain model using medical imaging.

Main Methods:

• Literature review of existing structural and material modeling techniques for brain tissue.
• Development of a numerical brain model integrating medical imaging data.
• Verification of the model through comparison with experimental data from post-mortem human subjects and numerical tests.

Main Results:

• The developed numerical model enabled the assessment of changes in mechanical and geometrical parameters of brain tissue under impact loads.
• Model verification confirmed its ability to represent brain tissue behavior under dynamic conditions.
• Identification of critical aspects influencing the biomechanical response assessment in dynamic analyses.

Conclusions:

• Standardized methodologies and improved material data are crucial for accurate brain tissue modeling.
• Numerical models based on medical imaging offer a powerful tool for understanding brain biomechanics.
• This research provides essential insights for advancing the development of reliable numerical brain models for dynamic analyses.