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Predicting calvarial growth in normal and craniosynostotic mice using a computational approach

Marghoub, Arsalan; Libby, Joseph; Babbs, Christian; Pauws, Erwin; Fagan, Michael J.; Moazen, Mehran

Authors

Arsalan Marghoub

Joseph Libby

Christian Babbs

Erwin Pauws

Michael J. Fagan

Mehran Moazen



Abstract

© 2017 Anatomical Society During postnatal calvarial growth the brain grows gradually and the overlying bones and sutures accommodate that growth until the later juvenile stages. The whole process is coordinated through a complex series of biological, chemical and perhaps mechanical signals between various elements of the craniofacial system. The aim of this study was to investigate to what extent a computational model can accurately predict the calvarial growth in wild-type (WT) and mutant type (MT) Fgfr2 C342Y/+ mice displaying bicoronal suture fusion. A series of morphological studies were carried out to quantify the calvarial growth at P3, P10 and P20 in both mouse types. MicroCT images of a P3 specimen were used to develop a finite element model of skull growth to predict the calvarial shape of WT and MT mice at P10. Sensitivity tests were performed and the results compared with ex vivo P10 data. Although the mod els were sensitive to the choice of input parameters, they predicted the overall skull growth in the WT and MT mice. The models also captured the difference between the ex vivoWT and MT mice. This modelling approach has the potential to be translated to human skull growth and to enhance our understanding of the different reconstruction methods used to manage clinically the different forms of craniosynostosis, and in the long term possibly reduce the number of re-operations in children displaying this condition and thereby enhance their quality of life.

Citation

Marghoub, A., Libby, J., Babbs, C., Pauws, E., Fagan, M. J., & Moazen, M. (2018). Predicting calvarial growth in normal and craniosynostotic mice using a computational approach. Journal of anatomy, 232(3), 440-448. https://doi.org/10.1111/joa.12764

Journal Article Type Article
Acceptance Date Nov 21, 2017
Online Publication Date Dec 15, 2017
Publication Date 2018-03
Deposit Date Jan 8, 2018
Publicly Available Date Mar 28, 2024
Journal Journal of Anatomy
Print ISSN 0021-8782
Electronic ISSN 1469-7580
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 232
Issue 3
Pages 440-448
DOI https://doi.org/10.1111/joa.12764
Keywords Anatomy; Developmental Biology; Cell Biology; Ecology, Evolution, Behavior and Systematics; Molecular Biology; Histology
Public URL https://hull-repository.worktribe.com/output/515912
Publisher URL http://onlinelibrary.wiley.com/doi/10.1111/joa.12764/abstract

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