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New algorithm for semiautomatic segmentation of nasal cavity and pharyngeal airway in comparison with manual
Noura A Alsufyani1, Andy Hess2, Michelle Noga3
1Assistant professor, Department of Dentistry, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada; assistant professor, College of Dentistry, King Saud University, Riyadh, Saudi Arabia.
Introduction:
Our objectives were to assess reliability, validity, and time efficiency of semiautomatic segmentation using Segura software of the nasal and pharyngeal airways, against manual segmentation with point-based analysis with color mapping.
Methods:
Pharyngeal and nasal airways from 10 cone-beam computed tomography image sets were segmented manually and semiautomatically using Segura (University of Alberta, Edmonton, Alberta, Canada). To test intraexaminer and interexaminer reliabilities, semiautomatic segmentation was repeated 3 times by 1 examiner and then by 3 examiners. In addition to volume and surface area, point-based analysis was completed to assess the reconstructed 3-dimensional models from Segura against manual segmentation. The times of both methods of segmentation were also recorded to assess time efficiency.
Results:
The reliability and validity of Segura were excellent (intraclass correlation coefficient, >0.9 for volume and surface area). Part analysis showed small differences between the Segura and manually segmented 3-dimensional models (greatest difference did not exceed 4.3 mm). Time of segmentation using Segura was significantly shorter than that for manual segmentation, 49 ± 11.0 vs 109 ± 9.4 minutes (P <0.001).
Conclusions:
Semiautomatic segmentation of the pharyngeal and nasal airways using Segura was found to be reliable, valid, and time efficient. Part analysis with color mapping was the key to explaining differences in upper airway volume and provides meaningful and clinically relevant analysis of 3-dimensional changes.
