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Updated: Jul 9, 2025

Author Spotlight: Development of a Novel Finite Element Analysis Model for Improved Orthognathic Surgical Techniques
Published on: October 20, 2023
Spring-assisted posterior vault expansion: a parametric study to improve the intracranial volume increase prediction
Lara Deliège1, Karan Ramdat Misier2, Dulanka Silva3
1University College London, London, UK. sejjlie@ucl.ac.uk.
Insights
This study developed a patient-specific model to predict intracranial volume (ICV) increase from spring-assisted posterior vault expansion for syndromic craniosynostosis. The model optimizes surgical parameters for improved ICV outcomes.
Area of Science:
- Biomedical Engineering
- Pediatric Neurosurgery
- Craniofacial Surgery
Background:
- Syndromic craniosynostosis causes raised intracranial pressure due to premature skull suture fusion.
- Spring-assisted posterior vault expansion is used to increase intracranial volume (ICV).
Purpose of the Study:
- To develop and validate a patient-specific model for predicting ICV increase after spring-assisted posterior vault expansion.
- To investigate the impact of surgical parameters on ICV outcomes through a parametric study.
Main Methods:
- Utilized pre- and post-operative CT data from 18 patients.
- Developed a finite element model to simulate spring expansion and predict ICV.
- Performed a parametric study varying osteotomy location to assess sensitivity and optimize surgical cuts.
Main Results:
- The finite element model accurately predicted post-operative ICV.
- The parametric study identified key surgical parameters influencing ICV increase.
- Optimization of surgical cuts was enabled by the validated model.
Conclusions:
- The patient-specific model effectively predicts ICV changes in spring-assisted posterior vault expansion.
- The study provides guidance for optimizing surgical strategies to maximize ICV increase.
- This approach aids in tailoring procedures for better outcomes in syndromic craniosynostosis treatment.
Abstract:
Spring-assisted posterior vault expansion has been adopted at the London Great Ormond Street Hospital for Children to treat raised intracranial pressure in patients affected by syndromic craniosynostosis, a congenital calvarial anomaly causing the premature fusion of skull sutures. This procedure involves elastic distractors used to dynamically reshape the skull and increase the intracranial volume (ICV). In this study, we developed and validated a patient-specific model able to predict the ICV increase and carried out a parametric study to investigate the effect of surgical parameters on that final volume. Pre- and post-operative computed tomography data relative to 18 patients were processed to extract simplified patient-specific skull shape, replicate surgical cuts, and simulate spring expansion. A parametric study was performed to quantify each parameter's impact on the surgical outcome: for each patient, the osteotomy location was varied in a pre-defined range; local sensitivity of the predicted ICV to each parameter was analysed and compared. Results showed that the finite element model performed well in terms of post-operative ICV prediction and allowed for parametric optimization of surgical cuts. The study indicates how to optimize the ICV increase according to the type of procedure and provides indication on the most robust surgical strategy.
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