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Evaluation of anatomic surgical outcomes in children with sleep disordered breathing symptoms using Cone beam Computed Tomography

  • Author / Creator
    Alsufyani, Noura, A
  • Aims: to utilize accurate and time-efficient methods to segment the upper airway, develop a registration method for longitudinal CBCT data specific for the upper airways, and correlate meaningful CBCT imaging parameters with surgical outcomes in pediatric cohort with SDB symptoms. Methods: 1) Reliability of several craniofacial landmarks to superimpose upper airway using CBCT images was tested along with impact of plane reorientation based on these landmarks on the upper airway in single and longitudinal CBCT images. 2) A semi-automatic segmentation program for the upper airway was developed and its reliability, validity and time efficiency were tested. 3) Using the previous tools, the upper airways of 10 children/adolescents with SDB symptoms and jaw disproportions were analyzed and correlated with the impact on quality of life survey OSA-18, before and after adenoidectomy or tonsillectomy. Results: 1) The landmarks chosen were reliable and coordinate transformation significantly reduced measurement errors in longitudinal CBCT data and highlighted large errors in the airways with large neck flexion or tongue malposition. 2) The developed semi-automatic segmentation program was reliable, accurate, and time-efficient. 3) Using point-based analyses, new airway measures were more explanatory than conventional global measures such as volume, strongly correlated with OSA-18 and better explained low scores after surgery. Conclusions: The semi-automatic segmentation program and registration technique of CBCT upper airways provided reliable tools to test the surgical outcomes in a cohort of children with SDB symptoms. New point-based analysis was complimentary to conventional measures of airway variables and better correlated with clinical measures

  • Subjects / Keywords
  • Graduation date
    Fall 2015
  • Type of Item
    Thesis
  • Degree
    Doctor of Philosophy
  • DOI
    https://doi.org/10.7939/R3Q815665
  • License
    This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
  • Language
    English
  • Institution
    University of Alberta
  • Degree level
    Doctoral
  • Department
  • Supervisor / co-supervisor and their department(s)
  • Examining committee members and their departments
    • Michelle Noga (Radiology and diagnostic imaging)
    • Manisha Witmans (Pediatric)
    • Irene Cheng (Computing Science)