Spring-assisted posterior vault expansion: a parametric study to improve the intracranial volume increase prediction

Deliège, Lara; Ramdat Misier, Karan; Silva, Dulanka; James, Gregory; Ong, Juling; Dunaway, David; Jeelani, Noor Ul Owase; Schievano, Silvia; Borghi, Alessandro

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.

Citation

Deliège, L., Ramdat Misier, K., Silva, D., James, G., Ong, J., Dunaway, D., …Borghi, A. (2023). Spring-assisted posterior vault expansion: a parametric study to improve the intracranial volume increase prediction. Scientific Reports, 13(1), Article 21371. https://doi.org/10.1038/s41598-023-48143-z

• Journal Article Type: Article
• Acceptance Date: Nov 22, 2023
• Online Publication Date: Dec 4, 2023
• Publication Date: 2023
• Deposit Date: Dec 7, 2023
• Publicly Available Date: Dec 7, 2023
• Journal: Scientific Reports
• Publisher: Nature Research
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Issue: 1
• Article Number: 21371
• DOI: https://doi.org/10.1038/s41598-023-48143-z
• Public URL: https://durham-repository.worktribe.com/output/1984203