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Computational Assessment of Risk of Subdural Hematoma Associated with Ventriculoperitoneal Shunt Placement

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Computer Methods, Imaging and Visualization in Biomechanics and Biomedical Engineering (CMBBE 2019)

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 36))

Abstract

Hydrocephalus is an accumulation of cerebrospinal fluid within the brain. The condition yields increased pressure inside the skull. When excess cerebrospinal fluid collects in the ventricles of the brain, ventriculoperitoneal (cerebral) shunt is routinely implanted. A ventriculoperitoneal shunt redirects fluid from the ventricles to the abdominal cavity. However, the ventriculoperitoneal shunt is sometimes associated with several complications, e.g. subdural hematoma. A subdural hematoma is a collection of blood outside the brain caused by the sudden shrinkage of the brain as the cerebrospinal fluid is drained away by the shunt implant. However, the mechanism of the development of subdura hematoma remains not entirely clear due to the dynamic alterations between cerebrospinal fluid, intraparenchyma, and ventricular pressure. Therefore, we aim to establish a model to simulate this interaction to understand the mechanism.

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Data Availability Statement

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

References

  1. Chrissicopoulos, C., Mourgela, S., Kirgiannis, K., Sakellaropoulos, A., Ampertos, N., Petritsis, K., Spanos, A.: What is the appropriate shunt system for normal-pressure hydrocephalus? Acta Neurochir. Suppl. 113, 119–121 (2012). https://doi.org/10.1007/978-3-7091-0923-6_24

    Article  Google Scholar 

  2. Hoya, K., Tanaka, Y., Uchida, T., Takano, I., Nagaishi, M., Kowata, K., Hyodo, A.: Treatment of traumatic acute subdural hematoma in adult hydrocephalus patients with cerebrospinal fluid shunt. Clin. Neurol. Neurosurg. 114, 211–216 (2011)

    Article  Google Scholar 

  3. Tangen, K.M., Hsu, C.Y., Zhu, D.C., Linninger, A.A.: CNS wide simulation of flow resistance and drug transport due to spinal microanatomy. J. Biomech. 48(10), 2144–2154 (2015). https://doi.org/10.1016/j.jbiomech.2015.02.018

    Article  Google Scholar 

  4. Rengachary, S.S., Ellenbogen, R.G.: Principles of Neurosurgery. Elsevier Mosby (2005)

    Google Scholar 

  5. Linninger, A.A., Tangen, K.M., Hsu, C.Y., Frim, D.: Cerebrospinal fluid mechanics and its coupling to cerebrovascular dynamics. Annu. Rev. Fluid Mech. 48, 219–257 (2016). https://doi.org/10.1146/annurev-fluid-122414-034321

    Article  MathSciNet  MATH  Google Scholar 

  6. Ho, J., Kleiven, S.: Dynamic response of the brain with vasculature: a three-dimensional computational study. J. Biomech. 40(13), 3006–3012 (2007). https://doi.org/10.1016/j.jbiomech.2007.02.011

    Article  Google Scholar 

  7. Chen, Y., Ostoja-Starzewski, M.: MRI-based finite element modeling of head trauma: spherically focusing shear waves. Acta Mech. 213(1–2), 155–167 (2010). https://doi.org/10.1007/s00707-009-0274-0

    Article  MATH  Google Scholar 

  8. Watanabe, D., Yuge, K., Nishimoto, T., Murakami, S., Takao, H.: Impact injury analysis of the human head. AutoTechnology 7(6), 34–37 (2007). https://doi.org/10.1007/BF03247021

    Article  Google Scholar 

  9. Chafi, M.S., Dirisala, V., Karami, G., Ziejewski, M.: A finite element method parametric study of the dynamic response of the human brain with different cerebrospinal fluid constitutive properties. Proc. Inst. Mech. Eng. Part H: J. Eng. Med. 223(8), 1003–1019 (2009). https://doi.org/10.1243/09544119JEIM631

    Article  Google Scholar 

  10. Madhukar, A., Chen, Y., Ostoja-Starzewski, M.: Effect of cerebrospinal fluid modelling on spherically convergent shear waves during blunt head trauma. Int. J. Numer. Method Biomed. Eng. 33(12), e2881 (2017). https://doi.org/10.1002/cnm.2881

    Article  Google Scholar 

  11. Toma, M., Nguyen, P.D.H.: Fluid–structure interaction analysis of cerebrospinal fluid with a comprehensive head model subject to a rapid acceleration and deceleration. Brain Inj. 32(12), 1576–1584 (2018). https://doi.org/10.1080/02699052.2018.1502470

    Article  Google Scholar 

  12. Toma, M.: Predicting concussion symptoms using computer simulations. In: Advances in Intelligent Systems and Computing, vol. 880, pp. 557–569 (2018). https://doi.org/10.1007/978-3-030-02686-8_42

  13. Toma, M., Nguyen, P.D.H.: Coup-contrecoup brain injury: fluid-structure interaction simulations. Int. J. Crashworthiness (2019). https://doi.org/10.1080/13588265.2018.1550910

  14. Zhou, Z., Li, X., Kleiven, S.: Fluid–structure interaction simulation of the brain-skull interface for acute subdural haematoma prediction. Biomech. Model. Mechanobiol. 18(1), 155–173 (2019). https://doi.org/10.1007/s10237-018-1074-z

    Article  Google Scholar 

  15. Zhou, Z., Li, X., Kleiven, S.: Biomechanics of acute subdural hematoma in the elderly: a fluid–structure interaction study. J. Neurotrauma 36(13), 2099–2108 (2019). https://doi.org/10.1089/neu.2018.6143

    Article  Google Scholar 

  16. Vorwerk, J., Clerc, M., Burger, M., Wolters, C.H.: Comparison of boundary element and finite element approaches to the EEG forward problem. Biomed. Eng./Biomedizinische Technik. 57(SI-1 Track-O), 795–798 (2012). https://doi.org/10.1515/bmt-2012-4152

  17. Luo, Y., Li, Z., Chen, H.: Finite-element study of cerebrospinal fluid in mitigating closed head injuries. J. Eng. Med. 226(7), 499–509 (2012). https://doi.org/10.1177/0954411912445729

    Article  Google Scholar 

  18. Liang, Z., Luo, Y.: A QCT-based nonsegmentation finite element head model for studying traumatic brain injury. Appl. Bion. Biomech. 2015, e837585 (2015). https://doi.org/10.1155/2015/837585

    Article  Google Scholar 

  19. Bei, L., Shijie, R., Haiyan, L., Shihai, C., Lijuan, H.: The effects of different mesh density of the cerebrospinal fluid on the dynamic responses of a 6 years old child finite element head model. In: Eighth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), pp. 756–767 (2016). https://doi.org/10.1109/ICMTMA.2016.186

  20. Gilchrist, M.D., O’Donoghue, D.: Simulation of the development of the frontal head impact injury. Comput. Mech. 26(3), 229–235 (2000). https://doi.org/10.1007/s004660000179

    Article  MATH  Google Scholar 

  21. Toma, M., Njilie, F.E.A., Ghajari, M., Galvanetto, U.: Assessing motorcycle crash-related head injuries using finite element simulations. Int. J. Simul. Model. 9(3), 143–151 (2010). https://doi.org/10.2507/ijsimm09(3)3.164

    Article  Google Scholar 

  22. Durrwachter, J.: Hemodynamics of the left ventricle: validation of a smoothed–particle hydrodynamics fluid-structure interaction model. M.S. thesis, Georgia Institute of Technology (2016)

    Google Scholar 

  23. Caballero, A., Mao, W., Liang, L., Oshinski, J., Primianok, C., McKay, R., Kodali, S., Sun, W.: Modeling left ventricular blood flow using smoothed particle hydrodynamics. Cardiovasc. Eng. Technol. 8(4), 465–479 (2017)

    Article  Google Scholar 

  24. Toma, M., Bloodworth IV, C.H., Einstein, D.R., Pierce, E.L., Cochran, R.P., Yoganathan, A.P., Kunzelman, K.S.: High resolution subject-specific mitral valve imaging and modeling: experimental & computational methods. Biomech. Model. Mechanobiol. 15(6), 1619–1630 (2016). https://doi.org/10.1007/s10237-016-0786-1

    Article  Google Scholar 

  25. Mao, W., Li, K., Sun, W.: Fluid-structure interaction study of transcatheter aortic valve dynamics using smoothed particle hydrodynamics. Cardiovasc. Eng. Technol. 7(4), 374–388 (2016)

    Article  Google Scholar 

  26. Toma, M., Einstein, D.R., Bloodworth IV, C.H., Cochran, R.P., Yoganathan, A.P., Kunzelman, K.S.: Fluid–structure interaction and structural analyses using a comprehensive mitral valve model with 3D chordal structure. Int. J. Numer. Methods Biomed. Eng. 33(4) (2017). https://doi.org/10.1002/cnm.2815

  27. Toma, M., Bloodworth IV, C.H., Pierce, E.L., Einstein, D.R., Cochran, R.P., Yoganathan, A.P., Kunzelman, K.S.: Fluid-structure interaction analysis of ruptured mitral chordae tendineae. Ann. Biomed. Eng. 45(3), 619–631 (2017). https://doi.org/10.1007/s10439-016-1727-y

    Article  Google Scholar 

  28. Toma, M., Jensen, M.O., Einstein, D.R., Yoganathan, A.P., Cochran, R.P., Kunzelman, K.S.: Fluid-structure interaction analysis of papillary muscle forces using a comprehensive mitral valve model with 3D chordal structure. Ann. Biomed. Eng. 44(4), 942–953 (2016). https://doi.org/10.1007/s10439-015-1385-5

    Article  Google Scholar 

  29. Singh-Gryzbon, S., Sadri, V., Toma, M., Pierce, E.L., Wei, Z.A., Yoganathan, A.P.: Development of a computational method for simulating tricuspid valve dynamics. Ann. Biomed. Eng. 47(6), 1422–1434 (2019). https://doi.org/10.1007/s10439-019-02243-y

    Article  Google Scholar 

  30. Toma, M., Nguyen, P.D.H.: Fluid-structure interaction analysis of cerebral spinal fluid with a comprehensive head model subject to a car crash-related whiplash. In: 5th International Conference on Computational and Mathematical Biomedical Engineering - CMBE2017 (2017)

    Google Scholar 

  31. Toma, M.: The emerging use of SPH in biomedical applications. Significances Bioeng. Biosci. 1(1), SBB.000502 (2017). https://doi.org/10.31031/SBB.2017.01.000502

  32. Toma, M., Oshima, M., Takagi, S.: Decomposition and parallelization of strongly coupled fluid-structure interaction linear subsystems based on the Q1/P0 discretization. J. Comput. Struct. 173, 84–94 (2016). https://doi.org/10.1016/j.compstruc.2016.06.001

    Article  Google Scholar 

  33. Miller, J.D., Nader, R.: Acute subdural hematoma from bridging vein rupture: a potential mechanism for growth. J. Neurosurg. 120(6), 1259–1502 (2014). https://doi.org/10.3171/2013.10.JNS13272

    Article  Google Scholar 

  34. Depreitere, B., Lierde, C.V., Sloten, J.V., Audekercke, R.V., Perre, G.V.D., Plets, C., Goffin, J.: Mechanics of acute subdural hematomas resulting from bridging vein rupture. J. Neurosurg. 104(6), 950–956 (2006). https://doi.org/10.3171/jns.2006.104.6.950

    Article  Google Scholar 

  35. Cui, Z.Y., Famaey, N., Depreitere, B., Ivens, J., Kleiven, S., Sloten, V.J.: On the assessment of bridging vein rupture associated acute subdural hematoma through finite element analysis. Comput. Methods Biomech. Biomed. Eng. 20(5), 530–539 (2017). https://doi.org/10.1080/10255842.2016.1255942

    Article  Google Scholar 

  36. Lee, M.C., Haut, R.C.: Insensitivity of tensile failure properties of human bridging veins to strain rate: implications in biomechanics of subdural hematoma. J. Biomechan. 22(6–7), 537–542 (1989). https://doi.org/10.1016/0021-9290(89)90005-5

    Article  Google Scholar 

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Funding

This study has been partially supported by a faculty start-up fund provided by the New York Institute of Technology and by a donation from the New York Thoroughbred Horseman’s Association.

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Correspondence to Milan Toma .

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Toma, M., Kuo, SH. (2020). Computational Assessment of Risk of Subdural Hematoma Associated with Ventriculoperitoneal Shunt Placement. In: Ateshian, G., Myers, K., Tavares, J. (eds) Computer Methods, Imaging and Visualization in Biomechanics and Biomedical Engineering. CMBBE 2019. Lecture Notes in Computational Vision and Biomechanics, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-030-43195-2_4

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  • DOI: https://doi.org/10.1007/978-3-030-43195-2_4

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