Density and Mechanical Properties of Selective Silicon Materials to Produce 3D Printed Paediatric Brain Model

Abstract:

This study presents a step towards exploring the possibility of using silicon materials as a surrogate to produce a multi-material 3D printed soft silicone brain model to be used in the investigation of Traumatic Brain Injury (TBI) in paediatric populations. Silicone represents a popular choice of material due to its viscoelastic properties, 3D printability, and capability to be tuned to possess different properties. Dynamic oscillatory shear tests were carried out for seven types of silicon materials at three different speeds against a different range of frequencies. The mechanical parameters response has been ranked on, which is the most appropriate to try. It also agrees with the range of reported paediatric brain tissue imitating grey and white matter as a surrogate brain material. Utilising of silicone for 3D printing represents a new approach to fabricate surrogate models that closely mimic biofidelic features and advance the medical engineering discipline.

• Periodical: Materials Science Forum (Volume 1021)
• Pages: 220-230
• DOI: https://doi.org/10.4028/www.scientific.net/MSF.1021.220
• Online since: February 2021
• Authors: Ghaidaa Abdulrahman khalid*
• Keywords: Material Properties, Mechanical Strength, Paediatric Brain, Silicon, Traumatic Brain Injury

References

[1] M. Faul, L. Xu, M.M. Wald, V. Coronado, A.M. Dellinger, Traumatic brain injury in the United States: national estimates of prevalence and incidence, Inj. Prev.16 A268 (2002-2006).

DOI: 10.1136/ip.2010.029215.951

[2] G.T. Fallenstein, V.D. Hulce, J.W. Melvin, Dynamic Mechanical Properties of Human Brain Tissue, J. Biomech. 2 (1969) 217-226.

DOI: 10.1016/0021-9290(69)90079-7

[3] J.E. Galford, J.H. McElhaney, A viscoelastic study of scalp, brain, and dura, J. Biomech. 3 (1970) 211-221.

DOI: 10.1016/0021-9290(70)90007-2

[4] E.H. Clayton, G.M. Genin, P.V. Bayly, Transmission, attenuation and reflection of shear waves in the human brain, J R Soc Interface. 9 (2012) 2899-2910.

DOI: 10.1098/rsif.2012.0325

[5] J. Zhang, M.A. Green, R. Sinkus, L.E. Bilston, Viscoelastic properties of human cerebellum using magnetic resonance elastography, J. Biomech. 44 (2011) 1909-1913.

DOI: 10.1016/j.jbiomech.2011.04.034

[6] M.A. Green, L.E. Bilston, R. Sinkus, In vivo brain viscoelastic properties measured by magnetic resonance elastography, NMR Biomed. 21 (2008) 755-764.

DOI: 10.1002/nbm.1254

[7] S.A. Kruse, G.H. Rose, K.J. Glaser, A. Manduca, J.P. Felmlee, C.R. Jack, R.L. Ehman, Magnetic resonance elastography of the brain, J. Neuroimaging. 39 (2008) 231-237.

DOI: 10.1016/j.neuroimage.2007.08.030

[8] G.A. Khalid, H. Bakhtiarydavijani, W.R. Whittington, R. Prabhu, M.D. Jones, Material Response Characterization of Three Poly Jet Printed Materials Used in a High Fidelity Human Infant Skull, Mater. Today: Proc. 20 (2020) 408-413.

DOI: 10.1016/j.matpr.2019.09.156

[9] M. Jones, G.A. Khalid, D. Darwall, R. Prabhu, A. Kemp, J.O. Arthurs, P. Theobald., Development and Validation of a Physical Model to Investigate the Biomechanics of Infant Head Impact, Forensic Sci. Int. 276 (2017) 111-119.

DOI: 10.1016/j.forsciint.2017.03.025

[10] G.A. Khalid, R.K. Prabhu, J.O. Arthurs, M.D. Jones, A Coupled Physical-Computational Methodology for The Investigation of Short Fall, Related Infant Head Impact Injury, Forensic Sci. Int. 300 (2019) 170-186.

DOI: 10.1016/j.forsciint.2019.04.034

[11] F. Zhu, C Wagner, A. Dal Cengio Leonardi, X. Jin, P. VandeVord., C. Chou, K.H. Yang, A.I. King, Using a gel/plastic surrogate to study the biomechanical response of the head under air shock loading: a combined experimenta l and numerical investigation, Biomech. Model. Mechanobiol. 11(2012) 341-353.

DOI: 10.1007/s10237-011-0314-2

[12] D.W. Brands, P.H. Bovendeerd, G.W. Peters, J.S. Wismans, M.H. Paas, J.L. Van Bree, Comparison of the dynamic behavior of brain tissue and two model materials, SAE Technical Paper. 99SC21 (1999).

DOI: 10.4271/99sc21

[13] S.S. Margulies, L.E. Thibault, T.A. Gennarelli, Physical model simulations of brain injury in the primate, J. Biomech.23(1990) 823-836.

DOI: 10.1016/0021-9290(90)90029-3

[14] A.E. Forte, S. Galvan, F. Manieri, F.R. Baena, D., Dini, A composite hydrogel for brain tissue phantoms, Mater. Des.112 (2016) 227-238.

DOI: 10.1016/j.matdes.2016.09.063

[15] K. Thibault, S. Margulies, Age-dependent material properties of the porcine cerebrum: effect on pediatric inertial head injury criteria, J. Biomech.31(1998) 1119-1126.

DOI: 10.1016/s0021-9290(98)00122-5

[16] S.S. Margulies, M.T. Prange, Regional, directional, and age-dependent properties of the brain undergoing large deformation, J. Biomech. 124 (2002) 244-252.

DOI: 10.1115/1.1449907

[17] B. Rashid, M. Destrade, M.D. Gilchrist, Mechanical characterization of brain tissue in compression at dynamic strain rates, J. Mech. Behav. Biomed. Mater. 10 (2012) 23-38.

DOI: 10.1016/j.jmbbm.2012.01.022

[18] S. Chatelin, J. Vappou, S. Roth, J.S. Raul, R. Willinger, Towards child versus adult brain mechanical properties, J. Mech. Behav. Biomed. Mater. 6 (2012) 166-173.

DOI: 10.1016/j.jmbbm.2011.09.013

[19] C. Macosko, Rheology Principles, Measurements and Applications. first ed., New York.

[20] A. Hill, Rheeology Basic: Introducing The Malern Kinexus a Practical Measurement Perspective, Malvern Instruments Ltd., 2013. Information on http://www.atascientific.com.au.

[21] Laerd Statistics, One-way ANOVA in SPSS Statistics, (2013a). Information on https://www.statistics.laerd.com/spss-tutorials/one-way-anova-using-spss-statistics.php.

DOI: 10.4135/9781506335254.n6

[22] A. Smith, C. Grandin, T. Duprez, F. Mataigne, G. Cosnard, Whole brain quantitative CBF and CBV measurements using MRI bolus tracking: Comparison of methodologies, Magn. Reson. Med. 43(2000) 559-564.

DOI: 10.1002/(sici)1522-2594(200004)43:4<559::aid-mrm10>3.0.co;2-n