Liang, Ce;
(2024)
Characterising and predicting normal postnatal craniofacial growth and development in human.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
The human craniofacial system consists of several bony components, connected via fibrous or cartilaginous joints. It houses several key organs including the brain and eyes, works together with the masticatory system and contribute to the respiratory system via nasal cavity. During the early stages of postnatal ontogeny, internal organs increase in volume hand in hand with their overlying complex of bones, joints and other associated soft tissues. However, our fundamental understanding of the mechanics of post-natal craniofacial ontogeny is still limited and this was the main focus of this study. The overall aim of this study was to characterise and predict normal postnatal craniofacial growth and development in human. This was achieved through three separate bodies of interlinked work. The first was to characterise the normal postnatal craniofacial growth and development at the macro morphological scale over the first 48 months of age, based on an extensive and longitudinal CT datasets of 217 normal individuals. This then formed the bases for a computational framework, integrating a physico-mechanical model and several novel algorithms, to predict the craniofacial skeletal morphology during the ontogeny. Finally, the biomechanical interactions between the developing skeleton and masticatory system were examined. Results highlighted that: (1) the postnatal craniofacial growth and development is allometric, and dominant by size change of its associated internal organs and capsules; (2) biomechanical models based on finite element method are capable of predicting the craniofacial morphology during ontogeny and revealing the physical interactions among its constituents; (3) infant cranium undergoes significant adaptations in response to the mechanical loadings arising from increasing masticatory demands. In conclusion, the characterisation and modelling approaches developed and validated here present huge potentials to serve as powerful tools to study fundamental questions in developmental biology and to advance treatment of conditions affecting the craniofacial system such as craniosynostosis.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Characterising and predicting normal postnatal craniofacial growth and development in human |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10197106 |
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