A systematic approach to predicting spring force for sagittal craniosynostosis surgery

Guangming Zhang, Hua Tan, Xiaohua Qian, Jian Zhang, King Li, Lisa R. David, Xiaobo Zhou

Research output: Contribution to journalArticlepeer-review


Spring-assisted surgery (SAS) can effectively treat scaphocephaly by reshaping crania with the appropriate spring force. However, it is difficult to accurately estimate spring force without considering biomechanical properties of tissues. This study presents and validates a reliable system to accurately predict the spring force for sagittal craniosynostosis surgery. The authors randomly chose 23 patients who underwent SAS and had been followed for at least 2 years. An elastic model was designed to characterize the biomechanical behavior of calvarial bone tissue for each individual. After simulating the contact force on accurate position of the skull strip with the springs, the finite element method was applied to calculating the stress of each tissue node based on the elastic model. A support vector regression approach was then used to model the relationships between biomechanical properties generated from spring force, bone thickness, and the change of cephalic index after surgery. Therefore, for a new patient, the optimal spring force can be predicted based on the learned model with virtual spring simulation and dynamic programming approach prior to SAS. Leave-one-out cross-validation was implemented to assess the accuracy of our prediction. As a result, the mean prediction accuracy of this model was 93.35%, demonstrating the great potential of this model as a useful adjunct for preoperative planning tool.

Original languageEnglish (US)
Pages (from-to)636-643
Number of pages8
JournalJournal of Craniofacial Surgery
Issue number3
StatePublished - 2016
Externally publishedYes


  • Biomechanical properties
  • Cephalic index
  • Finite element method
  • Sagittal craniosynostosis
  • Spring-assisted surgery

ASJC Scopus subject areas

  • Surgery
  • Otorhinolaryngology

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