Integrating mouthguard kinematics, finite element brain strain, and plasma biomarkers to explore brain injury thresholds in collision sport
Hickey, J. W.; Chan, E. Y. K.; Evans, L. J.; O'Brien, W. T.; Xie, B.; Roberts, S. S. H.; Butler, S. E.; Ernst, J.; Zhou, W. J. Q.; Zimmerman, K. A.; Spitz, G.; Parker, T. D.; O'Brien, T. J.; Shultz, S. R.; Sharp, D. J.; Ghajari, M.; McDonald, S. J.
Show abstract
Purpose: Identifying 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. Methods: We 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. Results: For 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. Conclusion: Finite 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.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Hamstrings muscle dynamics during the Nordic hamstring exercise and high-speed running 93%
- Knee and Hip Joint Dynamics Differ between Sprinting and Nordic Hamstring Exercises 93%
- Using dynamic ultrasound to assess Achilles tendon mechanics during running: the effect on running pattern and muscle-tendon junction tracking 92%
Similar papers in this journal
- Subconcussive preconditioning prevents microglial morphology changes and improves cognitive outcomes in mice 94%
- Objective turning measures improve diagnostic accuracy and relate to real-world mobility/combat readiness in chronic mild traumatic brain injury 91%
- Regionally specific resting-state beta neural power predicts brain injury and symptom recovery in adolescents with concussion: a longitudinal study 90%
Similar papers in this journal
- Subconcussive head impact exposure differences between drill intensities in U.S. high school football 94%
- Expanding Capabilities to Evaluate Readiness for Return to Duty after mTBI: The CAMP Study Protocol 93%
- Self-reported concussion history is not related to cortical volume in college athletes. 92%
Similar papers in this journal
- Foot strike pattern during running alters muscle-tendon dynamics of the gastrocnemius and the soleus 92%
- Joint contact forces during barefoot, minimal and conventional shod running are highly individual 92%
- Adding carbon fiber to shoe soles does not improve running economy: a muscle-level explanation 91%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.