Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Cross, Connor, Khonsari, Roman H., Patermoster, Giovanna, Arnaud, Eric, Larysz, Dawid, Kölby, Lars, Johnson, David, Ventikos, Yiannis, Moazen, Mehran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170984/
https://www.ncbi.nlm.nih.gov/pubmed/35685092
http://dx.doi.org/10.3389/fbioe.2022.913190
_version_ 1784721558192783360
author Cross, Connor
Khonsari, Roman H.
Patermoster, Giovanna
Arnaud, Eric
Larysz, Dawid
Kölby, Lars
Johnson, David
Ventikos, Yiannis
Moazen, Mehran
author_facet Cross, Connor
Khonsari, Roman H.
Patermoster, Giovanna
Arnaud, Eric
Larysz, Dawid
Kölby, Lars
Johnson, David
Ventikos, Yiannis
Moazen, Mehran
author_sort Cross, Connor
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9170984
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-91709842022-06-08 A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis Cross, Connor Khonsari, Roman H. Patermoster, Giovanna Arnaud, Eric Larysz, Dawid Kölby, Lars Johnson, David Ventikos, Yiannis Moazen, Mehran Front Bioeng Biotechnol Bioengineering and Biotechnology 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. Frontiers Media S.A. 2022-05-24 /pmc/articles/PMC9170984/ /pubmed/35685092 http://dx.doi.org/10.3389/fbioe.2022.913190 Text en Copyright © 2022 Cross, Khonsari, Patermoster, Arnaud, Larysz, Kölby, Johnson, Ventikos and Moazen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Bioengineering and Biotechnology
Cross, Connor
Khonsari, Roman H.
Patermoster, Giovanna
Arnaud, Eric
Larysz, Dawid
Kölby, Lars
Johnson, David
Ventikos, Yiannis
Moazen, Mehran
A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis
title A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis
title_full A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis
title_fullStr A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis
title_full_unstemmed A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis
title_short A Computational Framework to Predict Calvarial Growth: Optimising Management of Sagittal Craniosynostosis
title_sort computational framework to predict calvarial growth: optimising management of sagittal craniosynostosis
topic Bioengineering and Biotechnology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170984/
https://www.ncbi.nlm.nih.gov/pubmed/35685092
http://dx.doi.org/10.3389/fbioe.2022.913190
work_keys_str_mv AT crossconnor acomputationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT khonsariromanh acomputationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT patermostergiovanna acomputationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT arnauderic acomputationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT laryszdawid acomputationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT kolbylars acomputationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT johnsondavid acomputationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT ventikosyiannis acomputationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT moazenmehran acomputationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT crossconnor computationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT khonsariromanh computationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT patermostergiovanna computationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT arnauderic computationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT laryszdawid computationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT kolbylars computationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT johnsondavid computationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT ventikosyiannis computationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis
AT moazenmehran computationalframeworktopredictcalvarialgrowthoptimisingmanagementofsagittalcraniosynostosis