Improving Cranial Vault Remodeling for Unilateral Coronal Craniosynostosis - Introducing Automated Surgical Planning

  • Author / Creator
    Robertson, Emilie
  • Background

    Craniosynostosis is a condition that occurs in about one in 1000 infants. Unicoronal craniosynostosis (UCS) is a common subtype of craniosynostosis that results in an abnormal head shape, and can lead to brain growth impairment, visual problems, and psychosocial disturbance. Surgery is the mainstay of treatment for UCS and involves removing the abnormal skull bones and reshaping them. Cranial vault remodeling (CVR) is an invasive and often lengthy procedure that can result in significant blood loss. It also involves surgeon guesswork in an effort to create a normal appearing skull. Virtual surgical planning (VSP) is becoming popular as a method to reduce the subjectivity of these procedures and potentially improve outcomes for patients. There is limited data comparing conventionally planned and virtually planned CVR surgeries. The lack of a reliable, easy to use, and objective method to measure the deformity in UCS may contribute to this paucity.


    The goal of the research presented in this thesis was to improve surgical planning for UCS by developing a deformity index measure, investigating perceptions of the deformity in UCS, and developing a virtual surgical procedure that could be used to develop an automated VSP algorithm for CVR in UCS. These goals were addressed in three studies.


    3D Slicer, Geomagic FreeformPlus, Geomagic Control, and KeyShot were the software programs used. The deformity index in the first study was assessed using test-retest reliability. Chi-squared analysis and mixed methods regression model were used to analyze the perceptual data in the second study. Hausdorff surface distances were used to assess the virtual workflows in the third study.


    A novel, user-friendly deformity index was developed that was highly reliable (ICC = 0.93). Members of the general public were good at distinguishing between normal and abnormal skulls (χ2 (1) = 281.97, p < 0.001), and laypersons’ responses were predicted by the deformity index in the perception study (b = -0.10, z = -2.6, p = 0.010, CI: [-0.18, -0.02]). In the third study, two virtual fronto-orbital advancement workflows were developed that required varying degrees of surgeon participation. In both workflows, reconstruction skull models were created that were closer in shape to a normal skull than the preoperative skull.


    Several tools were developed that can be used by surgical teams to improve planning for CVR procedures for patients with UCS. A deformity index can be used to assess the severity of skull dysmorphology and quantify reconstruction outcomes. New data regarding the general public’s perception of UCS deformity assists in developing a meaningful reconstruction target for surgical planning. Finally, virtual workflows can be a useful tool for surgical teams to prepare for complex operations and introducing automation into the surgical planning can reduce the subjectivity of CVR even further. Future work in this area will focus on using the partially automated surgical planning framework to develop a fully automatic computer algorithm to further enhance the planning procedure for this complex problem.

  • Subjects / Keywords
  • Graduation date
    Fall 2020
  • Type of Item
  • Degree
    Master of Science
  • DOI
  • License
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