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Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction
Lambdoid craniosynostosis (LC) is a rare non-syndromic craniosynostosis characterised by fusion of the lambdoid sutures at the back of the head. Surgical correction including the spring assisted cranioplasty is the only option to correct the asymmetry at the skull in LC. However, the aesthetic outco...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596227/ https://www.ncbi.nlm.nih.gov/pubmed/33122820 http://dx.doi.org/10.1038/s41598-020-75747-6 |
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author | Bozkurt, Selim Borghi, Alessandro van de Lande, Lara S. Jeelani, N. U. Owase Dunaway, David J. Schievano, Silvia |
author_facet | Bozkurt, Selim Borghi, Alessandro van de Lande, Lara S. Jeelani, N. U. Owase Dunaway, David J. Schievano, Silvia |
author_sort | Bozkurt, Selim |
collection | PubMed |
description | Lambdoid craniosynostosis (LC) is a rare non-syndromic craniosynostosis characterised by fusion of the lambdoid sutures at the back of the head. Surgical correction including the spring assisted cranioplasty is the only option to correct the asymmetry at the skull in LC. However, the aesthetic outcome from spring assisted cranioplasty may remain suboptimal. The aim of this study is to develop a parametric finite element (FE) model of the LC skulls that could be used in the future to optimise spring surgery. The skull geometries from three different LC patients who underwent spring correction were reconstructed from the pre-operative computed tomography (CT) in Simpleware ScanIP. Initially, the skull growth between the pre-operative CT imaging and surgical intervention was simulated using MSC Marc. The osteotomies and spring implantation were performed to simulate the skull expansion due to the spring forces and skull growth between surgery and post-operative CT imaging in MSC Marc. Surface deviation between the FE models and post-operative skull models reconstructed from CT images changed between ± 5 mm over the skull geometries. Replicating spring assisted cranioplasty in LC patients allow to tune the parameters for surgical planning, which may help to improve outcomes in LC surgeries in the future. |
format | Online Article Text |
id | pubmed-7596227 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75962272020-10-30 Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction Bozkurt, Selim Borghi, Alessandro van de Lande, Lara S. Jeelani, N. U. Owase Dunaway, David J. Schievano, Silvia Sci Rep Article Lambdoid craniosynostosis (LC) is a rare non-syndromic craniosynostosis characterised by fusion of the lambdoid sutures at the back of the head. Surgical correction including the spring assisted cranioplasty is the only option to correct the asymmetry at the skull in LC. However, the aesthetic outcome from spring assisted cranioplasty may remain suboptimal. The aim of this study is to develop a parametric finite element (FE) model of the LC skulls that could be used in the future to optimise spring surgery. The skull geometries from three different LC patients who underwent spring correction were reconstructed from the pre-operative computed tomography (CT) in Simpleware ScanIP. Initially, the skull growth between the pre-operative CT imaging and surgical intervention was simulated using MSC Marc. The osteotomies and spring implantation were performed to simulate the skull expansion due to the spring forces and skull growth between surgery and post-operative CT imaging in MSC Marc. Surface deviation between the FE models and post-operative skull models reconstructed from CT images changed between ± 5 mm over the skull geometries. Replicating spring assisted cranioplasty in LC patients allow to tune the parameters for surgical planning, which may help to improve outcomes in LC surgeries in the future. Nature Publishing Group UK 2020-10-29 /pmc/articles/PMC7596227/ /pubmed/33122820 http://dx.doi.org/10.1038/s41598-020-75747-6 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Bozkurt, Selim Borghi, Alessandro van de Lande, Lara S. Jeelani, N. U. Owase Dunaway, David J. Schievano, Silvia Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction |
title | Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction |
title_full | Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction |
title_fullStr | Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction |
title_full_unstemmed | Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction |
title_short | Computational modelling of patient specific spring assisted lambdoid craniosynostosis correction |
title_sort | computational modelling of patient specific spring assisted lambdoid craniosynostosis correction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596227/ https://www.ncbi.nlm.nih.gov/pubmed/33122820 http://dx.doi.org/10.1038/s41598-020-75747-6 |
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