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Embedded Finite Elements for Modeling Axonal Injury.

Harsha T Garimella1,2, Ritika R Menghani1, Jesse I Gerber1

  • 1Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University Park, 16801, USA.

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This study introduces a novel finite element method to model brain axonal fibers from imaging, enabling biomechanical analysis of brain injuries and correcting software errors.

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Area of Science:

  • Computational biomechanics
  • Neuroimaging analysis
  • Finite element modeling

Background:

  • Diffusion tensor imaging (DTI) is crucial for understanding brain structure.
  • Modeling axonal fiber bundles is essential for analyzing brain injury biomechanics.
  • Existing software may have limitations in accurately representing embedded fiber structures.

Purpose of the Study:

  • To develop a large strain embedded finite element formulation for modeling axonal fiber bundles.
  • To enable explicit tractography from DTI data.
  • To investigate the biomechanics of brain injury by monitoring tract-level strains.

Main Methods:

  • Developed a large strain embedded finite element formulation.
  • Applied the method to model axonal fiber bundles from DTI data.
  • Created and validated a new algorithm to address software discrepancies in volume and mass calculations.

Main Results:

  • The proposed formulation enables explicit modeling of axonal fiber bundles.
  • A discrepancy in volume and mass calculations in commercial software was identified and corrected by the new algorithm.
  • Validation analysis confirmed the accuracy of the method for stress and energy calculations.

Conclusions:

  • The developed finite element method accurately models axonal fiber bundles and their strains.
  • This approach provides insights into brain injury biomechanics.
  • The new algorithm resolves critical issues in existing software for embedded fiber modeling.