A Reproducible MRI-to-FE Workflow for Generating Population-Specific and Subject-Specific Finite Element Head Models

Abstract

PURPOSE: Finite element (FE) models are widely used to study traumatic brain injury, but most are based on single-subject scans or generic atlases that may not represent specific cohorts, introducing variability in biomechanical outputs. This study presents a reproducible framework for generating a cohort-specific MRI-derived template brain and constructing a representative FE head model. METHODS: A cohort-specific template was created from T1-weighted and diffusion-weighted MRI scans of collision sport athletes (n = 78). An FE head model was then generated from this template, with material properties mapped using MRI-derived microstructural information. The anatomical accuracy of the template was evaluated using deformation-based morphometry against standard brain atlases. The FE model was validated against cadaveric head impact experiments. Subject-specific FE models were also developed to test the pipeline's applicability and model performance. RESULTS: Registration of an external non-collision sport controls (n = 20) to the template showed reduced deformation compared with registration to the MNI152 and an existing adolescent atlas, indicating improved cohort representation. Validation against cadaveric data demonstrated small to moderate correlations between simulated and experimental nodal displacements. The subject-specific model showed significantly different strain distributions from isotropic and fiber dispersion-informed models at both impact intensities; the two template models did not differ significantly. CONCLUSION: The proposed framework enables reproducible construction of cohort-specific FE brain models using open-access tools. Results highlight the importance of subject- and cohort-specific modeling for accurately characterizing brain biomechanics. This approach improves the anatomical and microstructural realism of FE models and supports more precise mapping of mechanical strain to clinical outcomes in TBI.