Integrating mouthguard kinematics, finite element brain strain, and plasma biomarkers to explore brain injury thresholds in collision sport
- 1Monash University
Abstract
PurposeIdentifying head impacts linked to brain injury in sport remains challenging. Instrumented mouthguards quantify head-impact kinematics, and finite element (FE) modelling can transform these data into brain strain estimates, which may better reflect injury risk than kinematics alone. Here, we examined associations between mouthguard-measured kinematics, FE-derived strain, and plasma brain injury biomarker GFAP following head impacts.
MethodsWe analysed 41 video-verified impacts from male Australian football players, including 22 assessed for concussion (17 diagnosed) and 19 unassessed. Instrumented mouthguards recorded peak linear acceleration (PLA), peak rotational acceleration, and peak rotational velocity (PRV). Brain strain was estimated using the Imperial College FE brain model, and plasma GFAP was quantified using Simoa. Biomechanical-GFAP associations were examined using Spearman correlations and segmented regression.
ResultsFor impacts overall, plasma GFAP was moderately correlated with PLA ({rho}=0.46, 95% CI: 0.20-0.66), PRV ({rho}=0.53, 95% CI: 0.20-0.78), and strain ({rho}=0.60, 95% CI: 0.32-0.80). Associations were stronger within concussion cases for strain ({rho}=0.86, 95% CI: 0.58-0.97) and PRV ({rho}=0.64, 95% CI: 0.15-0.93). Piecewise regression identified strain levels above which strain-GFAP relationships steepened across the whole-brain and brainstem. In concussion cases, supra-threshold brainstem strain was associated with greater symptoms.
ConclusionFinite element brain strain may better predict brain injury risk following a sport-related head impact than peak acceleration metrics. Stronger associations with plasma GFAP, particularly among concussion cases, and evidence of a biomechanical threshold, support the use of biomarker-informed strain measures in future risk modelling and the development of brain injury screening thresholds.
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BibTeX
@misc{hickey2026integrating,
title = {{Integrating mouthguard kinematics, finite element brain strain, and plasma biomarkers to explore brain injury thresholds in collision sport}},
author = {J. W. Hickey and E. Y. K. Chan and L. J. Evans and W. T. O'Brien and B. Xie and S. S. H. Roberts and S. E. Butler and J. Ernst and W. J. Q. Zhou and K. A. Zimmerman and G. Spitz and T. D. Parker and T. J. O'Brien and S. R. Shultz and D. J. Sharp and M. Ghajari and S. J. McDonald},
howpublished = {medRxiv},
year = {2026},
month = aug,
doi = {10.64898/2026.08.26.26360869},
url = {https://www.medrxiv.org/content/10.64898/2026.08.26.26360869v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Integrating mouthguard kinematics, finite element brain strain, and plasma biomarkers to explore brain injury thresholds in collision sport
AU - J. W. Hickey
AU - E. Y. K. Chan
AU - L. J. Evans
AU - W. T. O'Brien
AU - B. Xie
AU - S. S. H. Roberts
AU - S. E. Butler
AU - J. Ernst
AU - W. J. Q. Zhou
AU - K. A. Zimmerman
AU - G. Spitz
AU - T. D. Parker
AU - T. J. O'Brien
AU - S. R. Shultz
AU - D. J. Sharp
AU - M. Ghajari
AU - S. J. McDonald
PY - 2026
DA - 2026/08/26
PB - medRxiv
DO - 10.64898/2026.08.26.26360869
UR - https://www.medrxiv.org/content/10.64898/2026.08.26.26360869v1
AB - PurposeIdentifying head impacts linked to brain injury in sport remains challenging. Instrumented mouthguards quantify head-impact kinematics, and finite element (FE) modelling can transform these data into brain strain estimates, which may better reflect injury risk than kinematics alone. Here, we examined associations between mouthguard-measured kinematics, FE-derived strain, and plasma brain injury biomarker GFAP following head impacts. MethodsWe analysed 41 video-verified impacts from male Australian football players, including 22 assessed for concussion (17 diagnosed) and 19 unassessed. Instrumented mouthguards recorded peak linear acceleration (PLA), peak rotational acceleration, and peak rotational velocity (PRV). Brain strain was estimated using the Imperial College FE brain model, and plasma GFAP was quantified using Simoa. Biomechanical-GFAP associations were examined using Spearman correlations and segmented regression. ResultsFor impacts overall, plasma GFAP was moderately correlated with PLA ({rho}=0.46, 95% CI: 0.20-0.66), PRV ({rho}=0.53, 95% CI: 0.20-0.78), and strain ({rho}=0.60, 95% CI: 0.32-0.80). Associations were stronger within concussion cases for strain ({rho}=0.86, 95% CI: 0.58-0.97) and PRV ({rho}=0.64, 95% CI: 0.15-0.93). Piecewise regression identified strain levels above which strain-GFAP relationships steepened across the whole-brain and brainstem. In concussion cases, supra-threshold brainstem strain was associated with greater symptoms. ConclusionFinite element brain strain may better predict brain injury risk following a sport-related head impact than peak acceleration metrics. Stronger associations with plasma GFAP, particularly among concussion cases, and evidence of a biomechanical threshold, support the use of biomarker-informed strain measures in future risk modelling and the development of brain injury screening thresholds.
ER -