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Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretation

  • Concussions in Sports
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Annals of Biomedical Engineering Aims and scope Submit manuscript

Abstract

Brain tissue deformation resulting from head impacts is primarily caused by rotation and can lead to traumatic brain injury. To quantify brain injury risk based on measurements of kinematics on the head, finite element (FE) models and various brain injury criteria based on different factors of these kinematics have been developed, but the contribution of different kinematic factors has not been comprehensively analyzed across different types of head impacts in a data-driven manner. To better design brain injury criteria, the predictive power of rotational kinematics factors, which are different in (1) the derivative order (angular velocity, angular acceleration, angular jerk), (2) the direction and (3) the power (e.g., square-rooted, squared, cubic) of the angular velocity, were analyzed based on different datasets including laboratory impacts, American football, mixed martial arts (MMA), NHTSA automobile crashworthiness tests and NASCAR crash events. Ordinary least squares regressions were built from kinematics factors to the 95% maximum principal strain (MPS95), and we compared zero-order correlation coefficients, structure coefficients, commonality analysis, and dominance analysis. The angular acceleration, the magnitude and the first power factors showed the highest predictive power for the majority of impacts including laboratory impacts, American football impacts, with few exceptions (angular velocity for MMA and NASCAR impacts). The predictive power of rotational kinematics about three directions (x: posterior-to-anterior, y: left-to-right, z: superior-to-inferior) of kinematics varied with different sports and types of head impacts.

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Acknowledgements

This research was supported by the Pac-12 Conference’s Student-Athlete Health and Well-Being Initiative, the National Institutes of Health (R24NS098518), Taube Stanford Children’s Concussion Initiative and Stanford Department of Bioengineering. The authors also want to express their gratitude for the insights from the linear model course (STATS305A) offered by Dr. Trevor Hastie at Stanford University.

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  1. Xianghao Zhan and Yiheng Li contributed equally to this work.

Authors and Affiliations

  1. Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA

    Xianghao Zhan, Yuzhe Liu, August G. Domel, Hossein Vahid Alizadeh, Zhou Zhou, Nicholas J. Cecchi, Samuel J. Raymond & David B. Camarillo

  2. Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA

    Yiheng Li & Olivier Gevaert

  3. Technological University Dublin, Dublin, Ireland

    Stephen Tiernan

  4. Ford Motor Company, 3001 Miller Rd, Dearborn, MI, 48120, USA

    Jesse Ruan & Saeed Barbat

  5. Department of Radiology, Stanford University, Stanford, 94305, CA, USA

    Michael M. Zeineh

  6. Department of Neurosurgery, Stanford University, Stanford, 94305, CA, USA

    Gerald A. Grant

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  1. Xianghao Zhan
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Correspondence to Yuzhe Liu.

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Zhan, X., Li, Y., Liu, Y. et al. Predictive Factors of Kinematics in Traumatic Brain Injury from Head Impacts Based on Statistical Interpretation. Ann Biomed Eng 49, 2901–2913 (2021). https://doi.org/10.1007/s10439-021-02813-z

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