Modelling human skull growth: a validated computational model

Libby, Joseph; Marghoub, Arsalan; Johnson, David; Khonsari, Roman H.; Fagan, Michael J.; Moazen, Mehran

Abstract

© 2017 The Author(s) Published by the Royal Society. All rights reserved. During the first year of life, the brain grows rapidly and the neurocranium increases to about 65% of its adult size. Our understanding of the relationship between the biomechanical forces, especially from the growing brain, the craniofacial soft tissue structures and the individual bone plates of the skull vault is still limited. This basic knowledge could help in the future planning of craniofacial surgical operations. The aim of this study was to develop a validated computational model of skull growth, based on the finite-element (FE) method, to help understand the biomechanics of skull growth. To do this, a two-step validation study was carried out. First, an in vitro physical three-dimensional printed model and an in silico FE model were created from the same micro-CT scan of an infant skull and loaded with forces from the growing brain from zero to two months of age. The results from the in vitro model validated the FE model before it was further developed to expand from 0 to 12 months of age. This second FE model was compared directly with in vivo clinical CT scans of infants without craniofacial conditions (n = 56). The various models were compared in terms of predicted skull width, length and circumference, while the overall shape was quantified using three-dimensional distance plots. Statistical analysis yielded no significant differences between the male skull models. All size measurements from the FE model versus the in vitro physical model were within 5%, with one exception showing a 7.6% difference. The FE model and in vivo data also correlated well, with the largest percentage difference in size being 8.3%. Overall, the FE model results matched well with both the in vitro and in vivo data. With further development and model refinement, this modelling method could be used to assist in preoperative planning of craniofacial surgery procedures and could help to reduce reoperation rates.

Citation

Libby, J., Marghoub, A., Johnson, D., Khonsari, R. H., Fagan, M. J., & Moazen, M. (2017). Modelling human skull growth: a validated computational model. Journal of the Royal Society interface / the Royal Society, 14(130), 20170202. https://doi.org/10.1098/rsif.2017.0202

• Acceptance Date: May 9, 2017
• Online Publication Date: May 31, 2017
• Publication Date: 2017-05
• Deposit Date: May 9, 2017
• Publicly Available Date: Jun 6, 2018
• Journal: Journal of the Royal Society interface
• Print ISSN: 1742-5689
• Electronic ISSN: 1742-5662
• Publisher: The Royal Society
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Issue: 130
• Article Number: ARTN 20170202
• Pages: 20170202
• DOI: https://doi.org/10.1098/rsif.2017.0202
• Keywords: Biotechnology; Biophysics; Biochemistry; Bioengineering; Biomaterials; Biomedical Engineering
• Public URL: https://hull-repository.worktribe.com/output/451221
• Publisher URL: http://rsif.royalsocietypublishing.org/content/14/130/20170202
• Additional Information: This is the accepted manuscript of an article published in Journal of the Royal Society interface, 2017. The version of record is available at the DOI link in this record.