Brain Strain: Computational Model-Based Metrics for Head Impact Exposure and Injury Correlation

Area of Science:

• Biomechanics
• Neuroscience
• Sports Medicine

Background:

• Contact sports athletes experience repetitive head impacts with potential long-term neurological effects.
• Current kinematic metrics for head impacts lack strong correlation with measurable brain changes.
• Finite element (FE)-based metrics are emerging to quantify local brain deformations.

Purpose of the Study:

• To develop and evaluate novel cumulative strain-based metrics for quantifying head impact exposure in youth football.
• To assess the potential of these new metrics to improve the analysis of head impact effects on the brain.
• To investigate the importance of directional dependence and spatial distribution of brain strain responses.

Main Methods:

• Utilized an atlas-based brain model (ABM) to predict brain strain responses to impacts in 116 youth football athletes.
• Developed 36 new cumulative strain-based metrics to quantify the total burden of head impacts over a season.
• Analyzed the spatial distribution and directional dependence of the predicted brain strain.

Main Results:

• Proposed 36 novel cumulative strain-based metrics derived from FE modeling.
• Demonstrated the potential of these strain-based metrics for improved analytics compared to existing kinematic and cumulative metrics.
• Highlighted the significance of considering directional dependence in head impact analysis.

Conclusions:

• The developed strain-based metrics offer a promising advancement for analyzing cumulative head impact exposure in contact sports.
• These metrics have the potential to enhance our understanding of the relationship between head impacts and neurological changes.
• Future research should incorporate directional dependence and spatial distribution for more comprehensive brain impact analysis.