4.5 Article

An anatomically detailed and personalizable head injury model: Significance of brain and white matter tract morphological variability on strain

Journal

BIOMECHANICS AND MODELING IN MECHANOBIOLOGY
Volume 20, Issue 2, Pages 403-431

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s10237-020-01391-8

Keywords

Traumatic brain injury; Subject-specific head model; Demons and Dramms image registration; Mesh morphing; Axonal strain; Finite element analysis

Funding

  1. Royal Institute of Technology
  2. 16 NIH Institutes and Centers - NIH Blueprint for Neuroscience Research [1U54MH091657]
  3. McDonnell Center for Systems Neuroscience at Washington University
  4. KTH-Royal Institute of Technology, Stockholm
  5. Swedish Research Council [2016-04203, 2016-05314]
  6. European Union's Horizon 2020 research and innovation program under the Marie Curie Grant [642662]
  7. Swedish Research Council [2016-05314, 2016-04203] Funding Source: Swedish Research Council

Ask authors/readers for more resources

Finite element head models are important for studying head injuries and protection systems. This study presents two developments: an anatomically detailed FE head model with conforming hexahedral meshes, and a new hierarchical image registration pipeline for generating subject-specific head models. By comparing model predictions with experimental data, the study demonstrates the efficiency and accuracy of the pipeline in generating detailed subject-specific head models.
Finite element head (FE) models are important numerical tools to study head injuries and develop protection systems. The generation of anatomically accurate and subject-specific head models with conforming hexahedral meshes remains a significant challenge. The focus of this study is to present two developmental works: first, an anatomically detailed FE head model with conforming hexahedral meshes that has smooth interfaces between the brain and the cerebrospinal fluid, embedded with white matter (WM) fiber tracts; second, a morphing approach for subject-specific head model generation via a new hierarchical image registration pipeline integrating Demons and Dramms deformable registration algorithms. The performance of the head model is evaluated by comparing model predictions with experimental data of brain-skull relative motion, brain strain, and intracranial pressure. To demonstrate the applicability of the head model and the pipeline, six subject-specific head models of largely varying intracranial volume and shape are generated, incorporated with subject-specific WM fiber tracts. DICE similarity coefficients for cranial, brain mask, local brain regions, and lateral ventricles are calculated to evaluate personalization accuracy, demonstrating the efficiency of the pipeline in generating detailed subject-specific head models achieving satisfactory element quality without further mesh repairing. The six head models are then subjected to the same concussive loading to study the sensitivity of brain strain to inter-subject variability of the brain and WM fiber morphology. The simulation results show significant differences in maximum principal strain and axonal strain in local brain regions (one-way ANOVA test,p < 0.001), as well as their locations also vary among the subjects, demonstrating the need to further investigate the significance of subject-specific models. The techniques developed in this study may contribute to better evaluation of individual brain injury and the development of individualized head protection systems in the future. This study also contains general aspects the research community may find useful: on the use of experimental brain strain close to or at injury level for head model validation; the hierarchical image registration pipeline can be used to morph other head models, such as smoothed-voxel models.

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