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Updated: Oct 27, 2025
Author Spotlight: Development of a Novel Finite Element Analysis Model for Improved Orthognathic Surgical Techniques
Published on: October 20, 2023
Validation of an in-silico modelling platform for outcome prediction in spring assisted posterior vault expansion
Lara Deliège1, Karan Ramdat Misier1, Selim Bozkurt1
1UCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London WC1N 1EH, UK.
Insights
Finite Element Modelling accurately predicts outcomes for spring-assisted posterior vault expansion in syndromic craniosynostosis. This computational approach aids in planning surgeries to normalize head shape and increase intracranial volume.
Area of Science:
- Biomedical Engineering
- Computational Biology
- Neurosurgery
Background:
- Syndromic craniosynostosis causes increased intracranial pressure due to premature skull suture fusion.
- Spring-Assisted Posterior Vault Expansion (SPVE) is used to normalize head shape and augment intracranial volume.
- Accurate preoperative planning is crucial for optimizing SPVE outcomes.
Purpose of the Study:
- To develop and validate a 3D numerical model for predicting SPVE outcomes.
- To assess the model's suitability for clinical adoption in surgical planning.
- To improve patient-specific treatment strategies for syndromic craniosynostosis.
Main Methods:
- A Finite Element Model (FEM) was created using pre-operative CT data from 14 patients.
- Skull viscoelastic properties were tuned using retrospective spring expansion data from 50 patients.
- The FEM predicted post-operative skull shape and intracranial volume were compared to actual patient data.
Main Results:
- The FEM demonstrated good shape matching between simulated and actual post-operative calvaria.
- The model accurately predicted post-operative intracranial volume (R² = 0.92, p < 0.0001).
- High correlation indicates the model's reliability for outcome prediction.
Conclusions:
- Finite Element Modelling shows significant potential for predicting SPVE outcomes.
- The validated model can aid in preoperative surgical planning for syndromic craniosynostosis.
- Further optimization will facilitate clinical deployment of this predictive tool.
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.
