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Performance Evaluation of a Pre-computed Brain Response Atlas in Dummy Head Impacts

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Abstract

A pre-computed brain response atlas (pcBRA) may have the potential to accelerate the investigation of the biomechanical mechanisms of traumatic brain injury on a large-scale. In this study, we further enhance the technique and evaluate its performance using six degree-of-freedom angular velocity profiles from dummy head impacts. Using the pcBRA to simplify profiles into acceleration-only shapes, sufficiently accurate strain estimates were obtained for impacts with a major dominating velocity peak. However, they were largely under-estimated when substantial deceleration occurred that reversed the direction of the angular velocity. For these impacts, estimation accuracy was substantially improved with a biphasic profile simplification (average correlation coefficient and linear regression slope of 0.92 ± 0.03 and 0.95 ± 0.07 for biphasic shapes, respectively, vs. 0.80 ± 0.06 and 0.80 ± 0.08 for acceleration-only shapes). Peak maximum principal strain (ɛ p) and cumulative strain damage measure (CSDM) from the estimated strains consistently correlated stronger than kinematic metrics with respect to the baseline ɛ p and CSDM from the directly simulated responses, regardless of the brain region, and by a large margin (e.g., correlation of 0.93 vs. 0.75 compared to Brain Injury Criterion (BrIC) for ɛ p in the whole-brain, and 0.91 vs. 0.47 compared to BrIC for CSDM in the corpus callosum). These findings further support the pre-computation technique for accurate, real-time strain estimation, which could be important to accelerate model-based brain injury studies in the future.

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Acknowledgments

Funding is provided by the NIH Grants R01 NS092853 and R21 NS088781.

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No competing financial interests exist.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Worcester Polytechnic Institute, 60 Prescott Street, Worcester, MA, 01506, USA

    Wei Zhao & Songbai Ji

  2. Department of Mechanical Engineering, Stanford University, Stanford, CA, USA

    Calvin Kuo & David B. Camarillo

  3. Department of Bioengineering, Stanford University, Stanford, CA, USA

    Lyndia Wu & David B. Camarillo

  4. Thayer School of Engineering, Dartmouth College, Hanover, NH, USA

    Songbai Ji

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  1. Wei Zhao
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Correspondence to Songbai Ji.

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Associate Editor Joel D. Stitzel oversaw the review of this article.

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Zhao, W., Kuo, C., Wu, L. et al. Performance Evaluation of a Pre-computed Brain Response Atlas in Dummy Head Impacts. Ann Biomed Eng 45, 2437–2450 (2017). https://doi.org/10.1007/s10439-017-1888-3

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