Journal of Pediatric Neurology 2020; 18(05): 223-230
DOI: 10.1055/s-0040-1708495
Original Article
Georg Thieme Verlag KG Stuttgart · New York

Cerebrospinal Fluid Interaction with Cerebral Cortex during Pediatric Abusive Head Trauma

1   Department of Osteopathic Manipulative Medicine, College of Osteopathic Medicine, New York Institute of Technology, Old Westbury Campus, Northern Boulevard, Old Westbury, New York, United States
2   Department of Mechanical Engineering, College of Engineering & Computing Sciences, New York Institute of Technology, Old Westbury Campus, Northern Boulevard, Old Westbury, New York, United States
2   Department of Mechanical Engineering, College of Engineering & Computing Sciences, New York Institute of Technology, Old Westbury Campus, Northern Boulevard, Old Westbury, New York, United States
Rosalyn Chan-Akaley
3   Lang Research Center, NewYork-Presbyterian Queens, Flushing, New York, United States
Paul D. H. Nguyen
4   Pennsylvania State College of Medicine, Hershey, Pennsylvania, United States
Hallie Zwibel
5   Department of Sports Medicine, College of Osteopathic Medicine, New York Institute of Technology, Westbury Campus, Northern Boulevard, Old Westbury, New York, United States
› Author Affiliations
Funding This study was funded by a seed grant provided by the New York Institute of Technology and a donation from the New York Thoroughbred Horsemen's Association.
Further Information

Publication History

12 November 2019

26 January 2020

Publication Date:
05 April 2020 (online)


Abusive head trauma is the leading cause of fatal brain injuries in children younger than 2 years. It is a preventable and severe form of physical child abuse often linked to the forceful shaking of an infant or toddler. Victims of abusive head trauma can suffer permanent neurological damage, resulting in developmental delay and disability. The long-term effects of abusive head trauma are difficult to diagnose and predict. In this model, we use a high-order finite element method paired with the most comprehensive and current head/brain model and next-generation smoothed particle hydrodynamics. This is one of the first fluid–structure interaction frameworks that uses fluid material properties to represent the cerebrospinal fluid (CSF) while including all major anatomical features of the brain. The interaction of CSF with the brain cortex during abusive head trauma is demonstrated during multiple shaking cycles. A comprehensive and precise model that calculates for the role of CSF in neurological trauma will be useful both in the prevention and treatment of abusive head trauma and the determination of prognosis and patient outcomes.

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

  • References

  • 1 Labbé J. Ambroise Tardieu: the man and his work on child maltreatment a century before Kempe. Child Abuse Negl 2005; 29 (04) 311-324
  • 2 Caffey J. Multiple fractures in the long bones of infants suffering from chronic subdural hematoma. Am J Roentgenol Radium Ther 1946; 56 (02) 163-173
  • 3 Kempe CH, Silverman FN, Steele BF, Droegemueller W, Silver HK. The battered-child syndrome. JAMA 1962; 181: 17-24
  • 4 Shaahinfar A, Whitelaw KD, Mansour KM. Update on abusive head trauma. Curr Opin Pediatr 2015; 27 (03) 308-314
  • 5 Klevens J, Leeb RT. Child maltreatment fatalities in children under 5: findings from the National Violence Death Reporting System. Child Abuse Negl 2010; 34 (04) 262-266
  • 6 Palusci VJ, Covington TM. Child maltreatment deaths in the U.S. national child death review case reporting system. Child Abuse Negl 2014; 38 (01) 25-36
  • 7 Klevens J, Luo F, Xu L, Peterson C, Latzman NE. Paid family leave's effect on hospital admissions for pediatric abusive head trauma. Inj Prev 2016; 22 (06) 442-445
  • 8 Chevignard MP, Lind K. Long-term outcome of abusive head trauma. Pediatr Radiol 2014; 44 (04) (Suppl. 04) S548-S558
  • 9 Lind K, Toure H, Brugel D, Meyer P, Laurent-Vannier A, Chevignard M. Extended follow-up of neurological, cognitive, behavioral and academic outcomes after severe abusive head trauma. Child Abuse Negl 2016; 51: 358-367
  • 10 Rengachary SS, Ellenbogen RG. Principles of Neurosurgery. Elsevier Mosby; 2005
  • 11 Ho J, Kleiven S. Dynamic response of the brain with vasculature: a three-dimensional computational study. J Biomech 2007; 40 (13) 3006-3012
  • 12 Chen Y, Ostoja-Starzewski M. MRI-based finite element modeling of head trauma: spherically focusing shear waves. Acta Mech 2010; 213 (1–2): 155-167
  • 13 Watanabe D, Yuge K, Nishimoto T, Murakami S, Takao H. Impact injury analysis of the human head. AutoTechnology 2007; 7 (06) 34-37
  • 14 Chafi MS, 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 H 2009; 223 (08) 1003-1019
  • 15 Madhukar A, Chen Y, Ostoja-Starzewski M. Effect of cerebrospinal fluid modelling on spherically convergent shear waves during blunt head trauma. Int J Numer Methods Biomed Eng 2017 33. (12). doi: 10.1002/cnm.2881
  • 16 Zhou Z, Li X, Kleiven S. Fluid-structure interaction simulation of the brain-skull interface for acute subdural haematoma prediction. Biomech Model Mechanobiol 2019; 18 (01) 155-173
  • 17 Zhou Z, Li X, Kleiven S. Biomechanics of acute subdural hematoma in the elderly: a fluid-structure interaction study. J Neurotrauma 2019; 36 (13) 2099-2108
  • 18 Toma M, Nguyen PDH. Fluid-structure interaction analysis of cerebrospinal fluid with a comprehensive head model subject to a rapid acceleration and deceleration. Brain Inj 2018; 32 (12) 1576-1584
  • 19 Toma M, Nguyen PDH. Coup-contrecoup brain injury: fluid-structure interaction simulations. Int J Crashworthiness 2019 . doi: 10.1080/13588265.2018.1550910
  • 20 Toma M. Predicting concussion symptoms using computer simulations. In: Arai K, Bhatia R, Kapoor S, eds. Proceedings of the Future Technologies Conference (FTC). Advances in Intelligent Systems and Computing. Volume 880, 2018: 557-569
  • 21 Duckworth H, Ghajari M. Modelling brain biomechanics using a hybrid smoothed particle hydrodynamics and finite element model. In Ohio State University Injury Biomechanics Symposium, 2019
  • 22 Vorwerk J, Clerc M, Burger M, Wolters CH. Comparison of boundary element and finite element approaches to the EEG forward problem. Biomed Tech (Berl) 2012; 57 (Suppl. 01) 795-798
  • 23 Yao HD, Svensson MY, Nilsson H. Deformation of dorsal root ganglion due to pressure transients of venous blood and cerebrospinal fluid in the cervical vertebral canal. J Biomech 2018; 76 (25) 16-26
  • 24 Luo Y, Li Z, Chen H. Finite-element study of cerebrospinal fluid in mitigating closed head injuries. Proc Inst Mech Eng H 2012; 226 (07) 499-509
  • 25 Liang Z, Luo Y. A qct-based nonsegmentation finite element head model for studying traumatic brain injury. Appl Bionics Biomech 2015; 2015: 837585
  • 26 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), 2016: 756-767
  • 27 Gilchrist MD, O'Donoghue D. Simulation of the development of the frontal head impact injury. Comput Mech 2000; 26: 229-235
  • 28 Zhou Z, Li X, Kleiven S. Biomechanics of periventricular injury. J Neurotrauma 2020; 37 (08) 1074-1090
  • 29 Warner A, Tate J, Burton B, Johnson CR. A high-resolution head and brain computer model for forward and inverse EEG simulation. bioRxiv 2019 Doi: 10.1101/552190
  • 30 Fry FJ, Barger JE. Acoustical properties of the human skull. J Acoust Soc Am 1978; 63 (05) 1576-1590
  • 31 Tyler WJ. The mechanobiology of brain function. Nat Rev Neurosci 2012; 13 (12) 867-878
  • 32 Barber TW, Brockway JA, Higgins LS. The density of tissues in and about the head. Acta Neurol Scand 1970; 46 (01) 85-92
  • 33 Elkin BS, Azeloglu EU, Costa KD, Morrison III B. Mechanical heterogeneity of the rat hippocampus measured by atomic force microscope indentation. J Neurotrauma 2007; 24 (05) 812-822
  • 34 Gefen A, Gefen N, Zhu Q, Raghupathi R, Margulies SS. Age-dependent changes in material properties of the brain and braincase of the rat. J Neurotrauma 2003; 20 (11) 1163-1177
  • 35 Kruse SA, Rose GH, Glaser KJ. , et al. Magnetic resonance elastography of the brain. Neuroimage 2008; 39 (01) 231-237
  • 36 Moore SW, Sheetz MP. Biophysics of substrate interaction: influence on neural motility, differentiation, and repair. Dev Neurobiol 2011; 71 (11) 1090-1101
  • 37 Lui AC, Polis TZ, Cicutti NJ. Densities of cerebrospinal fluid and spinal anaesthetic solutions in surgical patients at body temperature. Can J Anaesth 1998; 45 (04) 297-303
  • 38 Toma M, Einstein DR, Bloodworth IV CH, Cochran RP, Yoganathan AP, Kunzelman KS. Fluid-structure interaction and structural analyses using a comprehensive mitral valve model with 3D chordal structure. Int J Numer Methods Biomed Eng 2017; 33 (04) e2815
  • 39 Toma M, Oshima M, Takagi S. Decomposition and parallelization of strongly coupled fluid–structure interaction linear subsystems based on the Q1/P0 discretization. Comput Struc 2016; 173: 84-94
  • 40 Toma M. The emerging use of SPH in biomedical applications. Significances Bioeng Biosci 2017; 1 (Suppl. 01) SBB.000502
  • 41 Figaji AA. Anatomical and physiological differences between children and adults relevant to traumatic brain injury and the implications for clinical assessment and care. Front Neurol 2017; 08: 685
  • 42 Toma M, Kuo S-H. Computational Assessment of Risk of Subdural Hematoma Associated with Ventriculoperitoneal Shunt Placement. In: Computer Methods, Imaging and Visualization in Biomechanics and Biomedical Engineering. Switzerland AG: Springer Nature; 2020
  • 43 Hsu CY, Schneller B, Alaraj A, Flannery M, Zhou XJ, Linninger A. Automatic recognition of subject-specific cerebrovascular trees. Magn Reson Med 2017; 77 (01) 398-410
  • 44 Ghaffari M, Tangen KM, Alaraj A, Du X, Charbel FT, Linninger AA. Large-scale subject-specific cerebral arterial tree modeling simulation. Comput Biol Med 2017; 91: 353-365