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In silico investigation of blast-induced intracranial fluid cavitation as it potentially leads to traumatic brain injury

Abstract

We conducted computational macroscale simulations predicting blast-induced intracranial fluid cavitation possibly leading to brain injury. To further understanding of this problem, we developed microscale models investigating the effects of blast-induced cavitation bubble collapse within white matter axonal fiber bundles of the brain. We model fiber tracks of myelinated axons whose diameters are statistically representative of white matter. Nodes of Ranvier are modeled as unmyelinated sections of axon. Extracellular matrix envelops the axon fiber bundle, and gray matter is placed adjacent to the bundle. Cavitation bubbles are initially placed assuming an intracranial wave has already produced them. Pressure pulses, of varied strengths, are applied to the upper boundary of the gray matter and propagate through the model, inducing bubble collapse. Simulations, conducted using the shock wave physics code CTH, predict an increase in pressure and von Mises stress in axons downstream of the bubbles after collapse. This appears to be the result of hydrodynamic jetting produced during bubble collapse. Interestingly, results predict axon cores suffer significantly lower shear stresses from proximal bubble collapse than does their myelin sheathing. Simulations also predict damage to myelin sheathing, which, if true, degrades axonal electrical transmissibility and general health of the white matter structures in the brain.

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References

  1. 1.

    Defense and Veterans Brain Injury Center: DoD worldwide numbers for TBI \(\vert \) DVBIC (Online). http://www.dvbic.org/dod-worldwide-numbers-tbi. Accessed: 05 July 2012

  2. 2.

    Moore, D.F., Radovitzky, R.A., Shupenko, L., Klinoff, A., Jaffee, M.S., Rosen, J.M.: Blast physics and central nervous system injury. Future Neurol. 3(3), 243–250 (2008). doi:10.2217/14796708.3.3.243

    Article  Google Scholar 

  3. 3.

    Moore, D.F., Jérusalem, A., Nyein, M., Noels, L., Jaffee, M.S., Radovitzky, R.A.: Computational biology—modeling of primary blast effects on the central nervous system. NeuroImage 47(Supplement 2), T10–T20 (2009). doi:10.1016/j.neuroimage.2009.02.019

    Article  Google Scholar 

  4. 4.

    Taylor, P.A., Ford, C.C.: Simulation of blast-induced early-time intracranial wave physics leading to traumatic brain injury. J. Biomech. Eng. 131(6), 061007 (2009). doi:10.1115/1.3118765

    Article  Google Scholar 

  5. 5.

    Grujicic, M., Arakere, G., He, T.: Material-modeling and structural-mechanics aspects of the traumatic brain injury problem. Multidiscip. Model. Mater. Struct. 6(3), 335–363 (2009). doi:10.1108/15736101011080097

    Article  Google Scholar 

  6. 6.

    Ganpule, S., Alai, A., Plougonven, E., Chandra, N.: Mechanics of blast loading on the head models in the study of traumatic brain injury using experimental and computational approaches. Biomech. Model. Mechanobiol. 12, 511–531 (2012). doi:10.1007/s10237-012-0421-8

    Article  Google Scholar 

  7. 7.

    Gu, L., Chafi, M.S., Ganpule, S., Chandra, N.: The influence of heterogeneous meninges on the brain mechanics under primary blast loading. Compos. Part B 43, 3160–3166 (2012). doi:10.1016/j.compositesb.2012.04.014

    Article  Google Scholar 

  8. 8.

    Taylor, P.A., Ludwigsen, J.S., Ford, C.C.: Investigation of blast-induced traumatic brain injury. Brain Inj. 28(7), 879–895 (2014). doi:10.3109/02699052.2014.888478

    Article  Google Scholar 

  9. 9.

    Moss, W., King, M., Blackman, E.: Skull flexure from blast waves: A mechanism for brain injury with implications for helmet design. Phys. Rev. Lett. 103(10), 108702 (2009). doi:10.1103/PhysRevLett.103.108702

    Article  Google Scholar 

  10. 10.

    Nyein, M.K., Jason, A.M., Yu, L., Pita, C.M., Joannopoulos, J.D., Moore, D.F., Radovitzky, R.A.: In silico investigation of intracranial blast mitigation with relevance to military traumatic brain injury. Proc. Natl. Acad. Sci. 107(48), 20703–20708 (2010). doi:10.1073/pnas.1014786107

    Article  Google Scholar 

  11. 11.

    Grujicic, M., Bell, W.C., Pandurangan, B., Glomski, P.S.: Fluid/structure interaction computational investigation of blast-wave mitigation efficacy of the advanced combat helmet. J. Mater. Eng. Perform. 20(6), 877–893 (2011). doi:10.1007/s11665-010-9724-z

    Article  Google Scholar 

  12. 12.

    Vakhtin, A.A., Calhoun, V.D., Jung, R.E., Prestopnik, J.L., Taylor, P.A., Ford, C.C.: Changes in intrinsic functional brain networks following blast-induced mild traumatic brain injury. Brain Inj. 27(11), 1304–1310 (2013). doi:10.3109/02699052.2013.823561

    Article  Google Scholar 

  13. 13.

    Taylor, P.A., Ludwigsen, J.S., Vakhtin, A.A., Ford, C.C.: Simulation and clinical assessment of blast-induced traumatic brain injury. IBIA Neurotrauma Lett. 35 (2014). http://www.internationalbrain.org/simulation-and-clinical-assessment-of-blastinduced-traumatic-brain-injury/

  14. 14.

    Calhoun, V.D., Adali, T., Pearlson, G.D., Pekar, J.J.: A method for making group inferences from functional MRI data using independent component analysis. Hum. Brain Mapp. 14(3), 140–151 (2001). doi:10.1002/hbm.1048

    Article  Google Scholar 

  15. 15.

    Lubock, P., Goldsmith, W.: Experimental cavitation studies in a model head–neck system. J. Biomech. 13, 1041–1052 (1980). doi:10.1016/0021-9290(80)90048-2

    Article  Google Scholar 

  16. 16.

    Brennen, C.E.: Cavitation in biological and bioengineering contexts. In: Proceedings of the 5th International Symposium on Cavitation, Osaka (2003)

  17. 17.

    Nakagawa, A., Fujimura, M., Kato, K., Okuyama, H., Hashimoto, T., Takayama, K., Tominaga, T.: Shock wave-induced brain injury in rat: Novel traumatic brain injury animal model. Acta Neurochir. Suppl. 102, 421–424 (2008). doi:10.1007/978-3-211-85578-2_82

  18. 18.

    Goeller, J., Wardlaw, A., Treichler, D., O’Bruba, J., Weiss, G.: Investigation of cavitation as a possible damage mechanism in blast-induced traumatic brain injury. J. Neurotrauma 29(10), 1970–1981 (2012). doi:10.1089/neu.2011.2224

    Article  Google Scholar 

  19. 19.

    Haniff, S., Taylor, P., Brundage, A., Burnett, D., Cooper, C., Gullerud, A., Terpsma, R.: Virtual simulation of the effects of intracranial fluid cavitation in blast-induced traumatic brain injury. In: Proceedings of the ASME 2015 International Mechanical Engineering Congress and Exposition. ASME, Houston (2015). doi:10.1115/IMECE2015-52696

  20. 20.

    Marieb, E., Hoehn, K.: Human Anatomy and Physiology. Person Benjamin Cummings, San Francisco (2007)

    Google Scholar 

  21. 21.

    Friedlander, F.G.: Simple progressive solutions of the wave equation. Math. Proc. Camb. Philos. Soc. 43(3), 360–373 (1947). doi:10.1017/S0305004100023598

    MathSciNet  Article  MATH  Google Scholar 

  22. 22.

    Virchow, R.: Ueber das ausgebreitete Vorkommen einer dem Nervenmark analogen Substanz in den thierischen Geweben. Arch. Für Pathol. Anat. Physiol. Für Klin. Med. 6(4), 562–572 (1854). doi:10.1007/BF02116709

    Google Scholar 

  23. 23.

    van der Knaap, M.S., Valk, J. (eds.): Myelin and white matter. In: Magnetic Resonance of Myelination and Myelin Disorders, pp. 1–19. Springer, Berlin (2005). doi:10.1007/3-540-27660-2_1

  24. 24.

    Liewald, D., Miller, R., Logothetis, N., Wagner, H.-J., Schuz, A.: Distribution of axon diameters in cortical white matter: An electron-microscopic study on three human brains and a macaque. Biol. Cybern. 108, 541–557 (2014). doi:10.1007/s00422-014-0626-2

    Article  Google Scholar 

  25. 25.

    Shreiber, D.I., Hao, H., Elias, R.A.I.: Probing the influence of myelin and glia on the tensile properties of the spinal cord. Biomech. Model. Mechanobiol. 8, 311–321 (2009). doi:10.1007/s10237-008-0137-y

    Article  Google Scholar 

  26. 26.

    Karami, G., Grundman, N., Abolfathi, N., Naik, A., Ziejewski, M.J.: A micromechanical hyperelastic modeling of brain white matter under large deformation. J. Mech. Behav. Biomed. Mater. 2, 243–254 (2009). doi:10.1016/j.jmbbm.2008.08.003

    Article  Google Scholar 

  27. 27.

    Snaidero, N., Simons, M.: Myelination at a glance. J. Cell Sci. 127, 2999–3004 (2014). doi:10.1242/jcs.151043

    Article  Google Scholar 

  28. 28.

    Swanson, S.R.: A constitutive model for high elongation elastic materials. J. Eng. Mater. Technol. 107, 110–114 (1985). doi:10.1115/1.3225782

    Article  Google Scholar 

  29. 29.

    Pervin, F., Chen, W.: Dynamic mechanical response of bovine gray matter and white matter brain tissues under compression. J. Biomech. 42, 731–735 (2009). doi:10.1016/j.jbiomech.2009.01.023

    Article  Google Scholar 

  30. 30.

    Brundage, A.L.: Implementation of Tillotson equation of state for hypervelocity impact of metals, geologic materials, and liquids. Proc. Eng. 58, 461–470 (2013). doi:10.1016/j.proeng.2013.05.053

    Article  Google Scholar 

  31. 31.

    Tillotson, J.H.: Metallic Equations of State for Hypervelocity Impact. GA-3216, San Diego (1962)

    Google Scholar 

  32. 32.

    Brundage, A.L.: Prediction of shock-induced cavitation in water. J. Phys: Conf. Ser. 500, 102002 (2014). doi:10.1088/1742-6596/500/10/102002

    Google Scholar 

  33. 33.

    Brundage, A.L.: Private Communication, Sandia National Laboratories (2014)

  34. 34.

    Hertel, E.S., Kerley, G.I.: CTH reference manual: The equation of state package. SAND98-0947, Sandia National Laboratories Report SAND98-0947, Albuquerque (1998)

  35. 35.

    Hertel, E.S., Bell, R., Elrick, M., Farnsworth, A., Kerley, G., McGlaun, J., Petney, S., Silling, S., Taylor, P.: CTH: a software family for multi-dimensional shock physics analysis. In: Proc. 19th Int. Symp. Shock Waves, vol. 1, 377–382 (1993). doi: 10.1007/978-3-642-78829-1_61

  36. 36.

    Medana, I.M., Esiri, M.M.: Axonal damage: a key predictor of outcome in human CNS diseases. Brain 126, 515–530 (2003). doi:10.1093/brain/awg061

    Article  Google Scholar 

Download references

Acknowledgements

This work funded through the US Office of Naval Research, T. Bentley, Project funding manager, under Contract No. N0001414IP20020. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International, Inc., for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525.

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Correspondence to S. Haniff.

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Communicated by O. Petel and S. Ouellet.

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Haniff, S., Taylor, P.A. In silico investigation of blast-induced intracranial fluid cavitation as it potentially leads to traumatic brain injury. Shock Waves 27, 929–945 (2017). https://doi.org/10.1007/s00193-017-0765-1

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Keywords

  • Traumatic brain injury (TBI)
  • Microscale model
  • Cavitation
  • Virtual simulation