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Towards a radiation free numerical modelling framework to predict spring assisted correction of scaphocephaly

Garate Andikoetxea, Begona; Ajami, Sara; Rodriguez-Florez, Naiara; Jeelani, N. U. Owase; Dunaway, David; Schievano, Silvia; Borghi, Alessandro

Towards a radiation free numerical modelling framework to predict spring assisted correction of scaphocephaly Thumbnail


Authors

Begona Garate Andikoetxea

Sara Ajami

Naiara Rodriguez-Florez

N. U. Owase Jeelani

David Dunaway

Silvia Schievano



Abstract

Sagittal Craniosynostosis (SC) is a congenital craniofacial malformation, involving premature sagittal suture ossification; spring-assisted cranioplasty (SAC) - insertion of metallic distractors for skull reshaping - is an established method for treating SC. Surgical outcomes are predictable using numerical modelling, however published methods rely on computed tomography (CT) scans availability, which are not routinely performed. We investigated a simplified method, based on radiation-free 3D stereophotogrammetry scans.Eight SAC patients (age 5.1 ± 0.4 months) with preoperative CT and 3D stereophotogrammetry scans were included. Information on osteotomies, spring model and post-operative spring opening were recorded. For each patient, two preoperative models (PREOP) were created: i) CT model and ii) S model, created by processing patient specific 3D surface scans using population averaged skin and skull thickness and suture locations. Each model was imported into ANSYS Mechanical (Analysis System Inc., Canonsburg, PA) to simulate spring expansion. Spring expansion and cranial index (CI - skull width over length) at times equivalent to immediate postop (POSTOP) and follow up (FU) were extracted and compared with in-vivo measurements.Overall expansion patterns were very similar for the 2 models at both POSTOP and FU. Both models had comparable outcomes when predicting spring expansion. Spring induced CI increase was similar, with a difference of 1.2%±0.8% for POSTOP and 1.6%±0.6% for FU.This work shows that a simplified model created from the head surface shape yields acceptable results in terms of spring expansion prediction. Further modelling refinements will allow the use of this predictive tool during preoperative planning.

Citation

Garate Andikoetxea, B., Ajami, S., Rodriguez-Florez, N., Jeelani, N. U. O., Dunaway, D., Schievano, S., & Borghi, A. (2023). Towards a radiation free numerical modelling framework to predict spring assisted correction of scaphocephaly. Computer Methods in Biomechanics and Biomedical Engineering, https://doi.org/10.1080/10255842.2023.2294262

Journal Article Type Article
Acceptance Date Dec 8, 2023
Online Publication Date Dec 18, 2023
Publication Date Dec 18, 2023
Deposit Date Dec 19, 2023
Publicly Available Date Jun 14, 2024
Journal Computer Methods in Biomechanics and Biomedical Engineering
Print ISSN 1025-5842
Electronic ISSN 1476-8259
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
DOI https://doi.org/10.1080/10255842.2023.2294262
Keywords Finite element modelling, craniosynostosis, spring cranioplasty
Public URL https://durham-repository.worktribe.com/output/2047992

Files

Published Journal Article (Advanced Online Version) (1.8 Mb)
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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.





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