A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis

The neonate skull consists of several bony plates, connected by fibrous soft tissue called sutures. Premature fusion of sutures is a medical condition known as craniosynostosis. Sagittal synostosis, caused by premature fusion of the sagittal suture, is the most common form of this condition. The opt...

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Bibliographic Details
Main Authors: Connor Cross, Roman H. Khonsari, Giovanna Patermoster, Eric Arnaud, Dawid Larysz, Lars Kölby, David Johnson, Yiannis Ventikos, Mehran Moazen
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-05-01
Series:Frontiers in Bioengineering and Biotechnology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fbioe.2022.913190/full
Description
Summary:The neonate skull consists of several bony plates, connected by fibrous soft tissue called sutures. Premature fusion of sutures is a medical condition known as craniosynostosis. Sagittal synostosis, caused by premature fusion of the sagittal suture, is the most common form of this condition. The optimum management of this condition is an ongoing debate in the craniofacial community while aspects of the biomechanics and mechanobiology are not well understood. Here, we describe a computational framework that enables us to predict and compare the calvarial growth following different reconstruction techniques for the management of sagittal synostosis. Our results demonstrate how different reconstruction techniques interact with the increasing intracranial volume. The framework proposed here can be used to inform optimum management of different forms of craniosynostosis, minimising the risk of functional consequences and secondary surgery.
ISSN:2296-4185