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Approximating subject-specific brain injury models via scaling based on head-brain morphological relationships
Shaoju Wu1, Wei Zhao1, Zheyang Wu2
1Department of Biomedical Engineering, Worcester Polytechnic Institute, 60 Prescott Street, Worcester, MA, 01609, USA.
Biomechanics and Modeling in Mechanobiology
|October 6, 2022
Summary
This study creates subject-specific brain models for traumatic brain injury (TBI) research without needing neuroimages. Simple regression models use head dimensions, age, and sex to scale generic brain models, improving accuracy for TBI simulations.
Area of Science:
- Biomechanics
- Neuroscience
- Medical Imaging
Background:
- Generic adult male head/brain models lack accuracy for subject-specific traumatic brain injury (TBI) research.
- Developing subject-specific models typically requires neuroimages, which are often unavailable.
- Existing models may not capture crucial individual brain morphological variations.
Purpose of the Study:
- To develop regression models for approximating subject-specific brain models without neuroimages.
- To assess the geometrical accuracy of scaled subject-specific brain models.
- To compare impact-induced brain strains between scaled models, morphed models, and generic models.
Main Methods:
- Established regression models correlating brain outer surface morphology with head dimensions, age, and sex using data from 191 subjects (14-25 years).
- Scaled a generic brain model using regression models to create approximate subject-specific brain models.
- Assessed geometrical accuracy using adjusted R-squared and absolute percentage error for brain volume.
- Compared impact-induced brain strains in scaled models against "morphed models" (neuroimage-based) and generic models for 11 subjects.
Main Results:
- Regression models demonstrated good geometrical accuracy in approximating subject-specific brain models (e.g., 3.09 ± 2.38% absolute percentage error for brain volume).
- Scaled subject-specific models showed comparable regional peak strains to "morphed models" derived from neuroimages.
- Generic models significantly overestimated brain strains (up to ~20%) compared to scaled subject-specific models, especially for smaller brains.
Conclusions:
- Approximating subject-specific brain models without neuroimages is feasible using age, sex, and measurable head dimensions.
- Incorporating individual brain morphological variations is crucial for accurate impact simulations in TBI research.
- The developed scaled models offer improved subject specificity for future TBI investigations.
Keywords:
Brain injury modelConcussionHead morphologySubject-specific modelWorcester head injury model (WHIM)
