Validation of an in-silico modelling platform for outcome prediction in spring assisted posterior vault expansion

Lara Deliège, Karan Ramdat Misier, Selim Bozkurt, William Breakey, Greg James, Juling Ong, David Dunaway, N. U.Owase Jeelani, Silvia Schievano, Alessandro Borghi

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Spring-Assisted Posterior Vault Expansion has been adopted at Great Ormond Street Hospital for Children, London, UK to treat raised intracranial pressure in patients affected by syndromic craniosynostosis, a congenital calvarial anomaly which causes premature fusion of skull sutures. This procedure aims at normalising head shape and augmenting intracranial volume by means of metallic springs which expand the back portion of the skull. The aim of this study is to create and validate a 3D numerical model able to predict the outcome of spring cranioplasty in patients affected by syndromic craniosynostosis, suitable for clinical adoption for preoperative surgical planning. Methods: Retrospective spring expansion measurements retrieved from x-ray images of 50 patients were used to tune the skull viscoelastic properties for syndromic cases. Pre-operative computed tomography (CT) data relative to 14 patients were processed to extract patient-specific skull shape, replicate surgical cuts and simulate spring insertion. For each patient, the predicted finite element post-operative skull shape model was compared with the respective post-operative 3D CT data. Findings: The comparison of the sagittal and transverse cross-sections of the simulated end-of-expansion calvaria and the post-operative skull shapes extracted from CT images showed a good shape matching for the whole population. The finite element model compared well in terms of post-operative intracranial volume prediction (R2 = 0.92, p < 0.0001). Interpretation: These preliminary results show that Finite Element Modelling has great potential for outcome prediction of spring assisted posterior vault expansion. Further optimisation will make it suitable for clinical deployment.

Original languageEnglish
Article number105424
Number of pages7
JournalClinical Biomechanics
Volume88
Early online date10 Jul 2021
DOIs
Publication statusPublished - 1 Aug 2021

Bibliographical note

Funding Information:
This work was supported by the Great Ormond Street Hospital Charity Clinical Research Starter Grant (award n. 17DD46) as well as the NIHR GOSH/UCL Biomedical Research Centre Advanced Therapies for Structural Malformations and Tissue Damage pump-prime funding call (grant n. 17DS18), the Engineering and Physical Sciences Research Council (EPSRC, grant n. EP/N02124X/1), and the European Research Council (ERC-2017-StG-757923). This report incorporates independent research from the National Institute for Health Research Biomedical Research Centre Funding Scheme. The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.

Funding Information:
This work was supported by the Great Ormond Street Hospital Charity Clinical Research Starter Grant (award n. 17DD46) as well as the NIHR GOSH/UCL Biomedical Research Centre Advanced Therapies for Structural Malformations and Tissue Damage pump-prime funding call (grant n. 17DS18 ), the Engineering and Physical Sciences Research Council (EPSRC, grant n. EP/N02124X/1 ), and the European Research Council ( ERC-2017-StG-757923 ). This report incorporates independent research from the National Institute for Health Research Biomedical Research Centre Funding Scheme . The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the National Institute for Health Research or the Department of Health.

Publisher Copyright:
© 2021 The Authors

Keywords

  • Craniosynostosis
  • Finite element modelling
  • Pre-operative planning
  • Spring assisted posterior vault expansion

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