Which brain injury metrics are suitable for supporting sports head injury assessment? A multi-sport brain strain evaluation

Emily Yik Kwan Chan, Eleni Koumantou, Lucas Low, Isaac Siy, Chris M. Jones, Kieran Austin, Mike Loosemore, Stuart J. McDonald, Mazdak Ghajari

medRxiv, 2026

Abstract

Objective To identify brain injury metrics suitable for supporting sports head injury assessment by evaluating their association with brain tissue strain and consistency across sports. Methods Head kinematics from 3,139 impacts in boxing, mixed martial arts, and rugby matches were recorded using instrumented mouthguards and used to calculate nine brain injury metrics. Impacts were simulated using an anatomically detailed finite element brain model to estimate peak 95 th -percentile maximum principal strain (MPS) in brain and brainstem, a measure of tissue deformation associated with long-term pathology. Sport-specific ordinary least squares models estimated x E , the metric value equivalent to a reference MPS of 0.21. Metric-MPS correlations and x E uncertainties were quantified using 5000 bootstrap resamples. Cross-sport consistency was assessed using the coefficient of variation (CV) of sport-specific median x E values, and uncertainty using the normalised confidence interval size (NCIS). Results XGB, an extreme gradient boosting strain-prediction model, showed the strongest and most consistent correlations with whole-brain ( r =0.924–0.974) and brainstem MPS ( r =0.887–0.954)…

Cite as (BibTeX)

@article{chan-2026-which-brain-injury-metrics,
  title={Which brain injury metrics are suitable for supporting sports head injury assessment? A multi-sport brain strain evaluation},
  author={Emily Yik Kwan Chan and Eleni Koumantou and Lucas Low and Isaac Siy and Chris M. Jones and Kieran Austin and Mike Loosemore and Stuart J. McDonald and Mazdak Ghajari},
  journal={medRxiv},
  year={2026},
  doi={10.64898/2026.06.30.26356946}
}