Development of a Metric for Predicting Brain Strain Responses Using Head Kinematics

  • Lee F. Gabler
  • Jeff R. Crandall
  • Matthew B. Panzer
Article

Abstract

Diffuse brain injuries are caused by excessive brain deformation generated primarily by rapid rotational head motion. Metrics that describe the severity of brain injury based on head motion often do not represent the governing physics of brain deformation, rendering them ineffective over a broad range of head impact conditions. This study develops a brain injury metric based on the response of a second-order mechanical system, and relates rotational head kinematics to strain-based brain injury metrics: maximum principal strain (MPS) and cumulative strain damage measure (CSDM). This new metric, universal brain injury criterion (UBrIC), is applicable over a broad range of kinematics encountered in automotive crash and sports. Efficacy of UBrIC was demonstrated by comparing it to MPS and CSDM predicted in 1600 head impacts using two different finite element (FE) brain models. Relative to existing metrics, UBrIC had the highest correlation with the FE models, and performed better in most impact conditions. While UBrIC provides a reliable measurement for brain injury assessment in a broad range of head impact conditions, and can inform helmet and countermeasure design, an injury risk function was not incorporated into its current formulation until validated strain-based risk functions can be developed and verified against human injury data.

Keywords

Brain deformation Finite element modeling Rotational Second-order system 

Notes

Acknowledgments

The authors thank the Partnership for Dummy Technology and Biomechanics (PDB) for support and funding for this research.

Supplementary material

10439_2018_2015_MOESM1_ESM.pdf (254 kb)
Supplementary material 1 (PDF 253 kb)

References

  1. 1.
    Alshareef, A., J. S. Giudice, J. Forman, R. S. Salzar, and M. B. Panzer. A novel method for quantifying human in situ whole brain deformation under rotational loading using sonomicrometry. J. Neurotrauma 2017.  https://doi.org/10.1089/neu.2017.5362.Google Scholar
  2. 44.
    Department of Transportation NHTSA Docket Number 69-7, Notice 19. Occupant Crash Protection: Head Injury Criterion, S6.2 of MVSS 208.Google Scholar
  3. 2.
    Elkin, B. S., and B. Morrison, III. Region-specific tolerance criteria for the living brain. Stapp Car Crash J. 51:127–138, 2007.PubMedGoogle Scholar
  4. 3.
    Forman, J., J. Michaelson, R. Kent, S. Kuppa, and O. Bostrom. Occupant restraint in the rear seat: ATD responses to standard and pre-tensioning, force-limiting belt restraints. Ann. Adv. Automot. Med. 52:141–154, 2008.PubMedCentralPubMedGoogle Scholar
  5. 4.
    Frieden, T. R., D. Houry, and G. Baldwin. Report to Congress on Traumatic Brain Injury in the United States: Epidemiology and Rehabilitation. Atlanta, GA: National Center for Injury Prevention and Control, Division for Unintentional Injury Prevention, 2015.Google Scholar
  6. 5.
    Gabler, L. F., J. R. Crandall, and M. B. Panzer. Investigating brain injury tolerance in the sagittal plane using a finite element model of the human head. Int. J. Automot. Eng. 7:37–43, 2016.Google Scholar
  7. 6.
    Gabler, L. F., J. R. Crandall, and M. B. Panzer. Assessment of kinematic brain injury metrics for predicting strain responses in diverse automotive impact conditions. Ann. Biomed. Eng. 2016.  https://doi.org/10.1007/s10439-016-1697-0.Google Scholar
  8. 7.
    Gabler, L. F., H. Joodaki, J. R. Crandall, and M. B. Panzer. Development of a single-degree-of-freedom mechanical model for predicting strain-based brain injury responses. J. Biomech. Eng. 2017.  https://doi.org/10.1115/1.4038357.Google Scholar
  9. 8.
    Gadd, C. W. Use of a Weighted-Impulse Criterion for Estimating Injury Hazard. SAE Technical Paper, 1966.Google Scholar
  10. 9.
    Gennarelli, T. A., L. E. Thibault, and A. K. Omaya. Comparison of linear and rotational acceleration in experimental cerebral concussion. Proc. 15th Stapp Car Crash Conf., New York, 1971.Google Scholar
  11. 10.
    Greenwald, R. M., J. T. Gwin, J. J. Chu, and J. J. Crisco. Head impact severity measures for evaluating mild traumatic brain injury risk exposure. Neurosurgery 62:789, 2008.CrossRefPubMedCentralPubMedGoogle Scholar
  12. 11.
    Hardy, W. N., C. D. Foster, M. J. Mason, K. H. Yang, A. I. King, and S. Tashman. Investigation of head injury mechanisms using neutral density technology and high-speed biplanar X-ray. Stapp Car Crash J. 45:337–368, 2001.PubMedGoogle Scholar
  13. 12.
    Hardy, W. N., M. J. Mason, C. D. Foster, C. S. Shah, J. M. Kopacz, K. H. Yang, A. I. King, J. Bishop, M. Bey, W. Anderst, et al. A study of the response of the human cadaver head to impact. Stapp Car Crash J. 51:17, 2007.PubMedCentralPubMedGoogle Scholar
  14. 13.
    Harmon, K. G., J. A. Drezner, M. Gammons, K. M. Guskiewicz, M. Halstead, S. A. Herring, J. S. Kutcher, A. Pana, M. Putukian, and W. O. Roberts. American Medical Society for Sports Medicine position statement: concussion in sport. Br. J. Sports Med. 47:15–26, 2013.CrossRefPubMedGoogle Scholar
  15. 14.
    Holbourn, A. H. S. Mechanics of head injuries. Lancet 242:438–441, 1943.CrossRefGoogle Scholar
  16. 45.
    J211/1: Instrumentation for Impact Test—Part 1—Electronic Instrumentation. Warrendale, PA: SAE International.Google Scholar
  17. 15.
    Ji, S., and W. Zhao. A pre-computed brain response atlas for instantaneous strain estimation in contact sports. Ann. Biomed. Eng. 43:1877–1895, 2015.CrossRefPubMedGoogle Scholar
  18. 16.
    Kimpara, H., and M. Iwamoto. Mild traumatic brain injury predictors based on angular accelerations during impacts. Ann. Biomed. Eng. 40:114–126, 2012.CrossRefPubMedGoogle Scholar
  19. 17.
    King, A. I., K. H. Yang, L. Zhang, W. Hardy, and D. C. Viano. Is head injury caused by linear or angular acceleration. IRCOBI Conf., Lisbon, Portugal, September 2003.Google Scholar
  20. 18.
    Kleiven, S. Influence of impact direction on the human head in prediction of subdural hematoma. J. Neurotrauma 20:365–379, 2003.CrossRefPubMedGoogle Scholar
  21. 19.
    Kleiven, S. Predictors for traumatic brain injuries evaluated through accident reconstructions. Stapp Car Crash J. 51:81–114, 2007.PubMedGoogle Scholar
  22. 20.
    Laituri, T. R., R. E. El-Jawahri, S. Henry, and K. Sullivan. Field-Based Assessments of Various AIS2+ Head Risk Curves for Frontal Impact. SAE Technical Paper, 2015.Google Scholar
  23. 21.
    Lobo, B., R. Lin, D. Brown, T. Kim, and M. Panzer. Predicting pedestrian injury metrics based on vehicle front-end design. In: Internet of Vehicles—Safe and Intelligent Mobility. Cham: Springer, 2015, pp. 114–126.Google Scholar
  24. 22.
    Mao, H., L. Zhang, B. Jiang, V. V. Genthikatti, X. Jin, F. Zhu, R. Makwana, A. Gill, G. Jandir, A. Singh, et al. Development of a finite element human head model partially validated with thirty five experimental cases. J. Biomech. Eng. 135:111002, 2013.CrossRefPubMedGoogle Scholar
  25. 23.
    Margulies, S. S., and L. E. Thibault. A proposed tolerance criterion for diffuse axonal injury in man. J. Biomech. 25:917–923, 1992.CrossRefPubMedGoogle Scholar
  26. 24.
    Milton, S. J., and J. C. Arnold. Introduction to Probability and Statistics Principles and Applications for Engineering and the Computing Sciences. New York: McGraw-Hill College, 2002.Google Scholar
  27. 25.
    Mueller, B., A. MacAlister, J. Nolan, and D. Zuby. Comparison of HIC and BRIC head injury risk in IIHS frontal crash tests to real-world head injuries. Proc. 24th Int. Tech. Conf. Enhanc. Saf. Veh., 2015.Google Scholar
  28. 26.
    National Operating Committee on the Standards for Athletic Equipment (NOCSAE). Standard Test Method and Equipment Used in Evaluating the Performance Characteristics of Protective Headgear/Equipment, 2012.Google Scholar
  29. 27.
    Newman, J. A generalized acceleration model for brain injury threshold (GAMBIT). Proc. 1986 Int. IRCOBI Conf. Biomech. Impact, 1986.Google Scholar
  30. 28.
    Newman, J. A., N. Shewchenko, and E. Welbourne. A proposed new biomechanical head injury assessment function—the maximum power index. Stapp Car Crash J. 44:215–247, 2000.PubMedGoogle Scholar
  31. 46.
    NHTSA NVS | Vehicle Crash Test Database. www.nrd.nhtsa.dot.gov/database/VSR/veh/QueryTest.
  32. 29.
    Panzer, M. B., B. S. Myers, B. P. Capehart, and C. R. Bass. Development of a finite element model for blast brain injury and the effects of CSF cavitation. Ann. Biomed. Eng. 40:1530–1544, 2012.CrossRefPubMedGoogle Scholar
  33. 30.
    Patrick, L. M., H. R. Lissner, and E. S. Gurdjian. Survival by design: head protection. Proc. 7th Stapp Car Crash Field Demonstr. Conf., 1963.Google Scholar
  34. 31.
    Rowson, S., and S. M. Duma. Brain injury prediction: assessing the combined probability of concussion using linear and rotational head acceleration. Ann. Biomed. Eng. 41:873–882, 2013.CrossRefPubMedCentralPubMedGoogle Scholar
  35. 32.
    Sanchez, E. J., L. F. Gabler, J. S. McGhee, A. V. Olszko, V. C. Chancey, J. Crandall, and M. B. Panzer. Evaluation of head and brain injury risk functions using sub-injurious human volunteer data. J. Neurotrauma 2017.  https://doi.org/10.1089/neu.2016.4681.Google Scholar
  36. 33.
    Santiago, L. A., B. C. Oh, P. K. Dash, J. B. Holcomb, and C. E. Wade. A clinical comparison of penetrating and blunt traumatic brain injuries. Brain Inj. 26:107–125, 2012.CrossRefPubMedGoogle Scholar
  37. 34.
    Saunders, J., D. Parent, and E. Ames. NHTSA oblique crash test results: vehicle performance and occupant injury risk assessment in vehicles with small overlap countermeasures. In: The 24th International Technical Conference for the Enhanced Safety of Vehicles, 2015.Google Scholar
  38. 35.
    Sullivan, S., et al. White matter tract-oriented deformation predicts traumatic axonal brain injury and reveals rotational direction-specific vulnerabilities. Biomech. Model. Mechanobiol. 14:877–896, 2015.CrossRefPubMedGoogle Scholar
  39. 36.
    Takhounts, E. G., V. Hasija, S. A. Ridella, S. Rowson, and S. M. Duma. Kinematic Rotational Brain Injury Criterion (BRIC). Paper Number: 11-026, 2011.Google Scholar
  40. 37.
    Takhounts, E. G., S. A. Ridella, V. Hasija, R. E. Tannous, J. Q. Campbell, D. Malone, K. Danelson, J. Stitzel, S. Rowson, and S. Duma. Investigation of traumatic brain injuries using the next generation of simulated injury monitor (SIMon) finite element head model. Stapp Car Crash J. 52:1–31, 2008.PubMedGoogle Scholar
  41. 38.
    Takhounts, E. G., M. J. Craig, K. Moorhouse, J. McFadden, and V. Hasija. Development of brain injury criteria (Br IC). Stapp Car Crash J. 57:243–266, 2013.PubMedGoogle Scholar
  42. 39.
    Taylor, C. A. Traumatic brain injury-related emergency department visits, hospitalizations, and deaths—United States, 2007 and 2013. MMWR Surveill. Summ. 2017.  https://doi.org/10.15585/mmwr.ss6609a1.Google Scholar
  43. 40.
    Thibault, L. E., and T. A. Gennarelli. Biomechanics of Diffuse Brain Injuries. SAE Technical Paper, 1985.Google Scholar
  44. 41.
    Versace, J. A Review of the Severity Index. Warrendale, PA: SAE International, 1971.CrossRefGoogle Scholar
  45. 42.
    Viano, D. C., C. Withnall, and D. Halstead. Impact performance of modern football helmets. Ann. Biomed. Eng. 40:160–174, 2012.CrossRefPubMedGoogle Scholar
  46. 43.
    von Gierke, H. E. Transient acceleration, vibration and noise problems in space flight. In: Bioastronautics, edited by K. E. Schaefer. New York: Mac-Millan Co., 1964, p. 61.Google Scholar
  47. 47.
    Yanaoka, T., Y. Dokko, and Y. Takahashi. Investigation on an Injury Criterion Related to Traumatic Brain Injury Primarily Induced by Head Rotation. SAE Technical Paper, 2015.Google Scholar

Copyright information

© Biomedical Engineering Society 2018

Authors and Affiliations

  • Lee F. Gabler
    • 1
  • Jeff R. Crandall
    • 1
  • Matthew B. Panzer
    • 1
  1. 1.Department of Mechanical and Aerospace EngineeringUniversity of Virginia, Center for Applied BiomechanicsCharlottesvilleUSA

Personalised recommendations