ArticleFrontiers in bioengineering and biotechnology2022
A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis.
Article in Frontiers in bioengineering and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Optimising Fronto-Orbital Distraction for Management of Unicoronal Craniosynostosis.Annals of biomedical engineering · 2026Article
- Article
- Functional adaptation of the infant craniofacial system to mechanical loadings arising from masticatory forces.Proceedings. Biological sciences · 2024Article
- Understanding the influence of surgical parameters on craniofacial surgery outcomes: a computational study.Royal Society open science · 2024Article
- Spring-Assisted Surgery of Unilambdoid Craniosynostosis.The Journal of craniofacial surgery · 2024Article
- Normal human craniofacial growth and development from 0 to 4 years.Scientific reports · 2023Article
- Multisuture craniosynostosis: a case report of unusual presentation of chromosome 14q32 deletion.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2023Article
- A preliminary analysis of replicating the biomechanics of helmet therapy for sagittal craniosynostosis.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2023Article
- Biomechanical evaluation of a novel intervertebral disc repair technique for large box-shaped ruptures.Frontiers in bioengineering and biotechnology · 2023Article
- Isolated Effects of Bone, Spring and Surgical Parameters on the Surgical Outcome in Spring-Assisted Sagittal Synostosis Correction.Healthcare technology lettersArticle
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Authors and funding
9 authors.
Funding
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Abstract
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.
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