Interaction between otorhinolaryngology and orthodontics: correlation between the nasopharyngeal airway and the craniofacial complex

AI-based automatic segmentation of craniomaxillofacial anatomy from CBCT scans for automatic detection of pharyngeal airway evaluations in OSA patients

This study aims to generate and also validate an automatic detection algorithm for pharyngeal airway on CBCT data using an AI software (Diagnocat) which will procure a measurement method. The second aim is to validate the newly developed artificial intelligence system in comparison to commercially available software for 3D CBCT evaluation. A Convolutional Neural Network-based machine learning algorithm was used for the segmentation of the pharyngeal airways in OSA and non-OSA patients. Radiologists used semi-automatic software to manually determine the airway and their measurements were compared with the AI. OSA patients were classified as minimal, mild, moderate, and severe groups, and the mean airway volumes of the groups were compared. The narrowest points of the airway (mm), the field of the airway (mm²), and volume of the airway (cc) of both OSA and non-OSA patients were also compared. There was no statistically significant difference between the manual technique and Diagnocat measurements in all groups (p > 0.05). Inter-class correlation coefficients were 0.954 for manual and automatic segmentation, 0.956 for Diagnocat and automatic segmentation, 0.972 for Diagnocat and manual segmentation. Although there was no statistically significant difference in total airway volume measurements between the manual measurements, automatic measurements, and DC measurements in non-OSA and OSA patients, we evaluated the output images to understand why the mean value for the total airway was higher in DC measurement. It was seen that the DC algorithm also measures the epiglottis volume and the posterior nasal aperture volume due to the low soft-tissue contrast in CBCT images and that leads to higher values in airway volume measurement.

Short-term pharyngeal airway changes after mandibular advancement surgery in adult Class II-Patients--a three-dimensional retrospective study

The purpose of this study was to investigate volume changes in posterior airway space (PAS) after bilateral mandibular advancement surgery. Measurements were taken based on three-dimensional (3D) records available for a large and homogeneous cohort of patients. Pre- and postoperative CBCT scans of 102 adult patients with Class II dysgnathia were visualized and analyzed using 3D software (Mimics® Innovation Suite 14.1; Materialise, Leuven, Belgium). The PAS was divided into three segments by three planes parallel and one plane perpendicular to the Frankfort horizontal plane. Total volume, partial volumes, and cross-sectional areas were calculated from the pre- and postoperative scans. Dahlberg coefficients were obtained to verify each parameter for the measurements' reliability. The statistical significance of the changes observed was analyzed by Wilcoxon's rank-sum test. Highly significant (p=0.000) increases in total posterior airway volume (+32.0%) were noted as an effect of mandibular advancement surgery, amounting to 45.6% in the lower PAS third compared to 38.8% in the middle and 12.5% in the upper PAS third. We also obtained highly significant (p=0.000) increases in all the cross-sectional areas investigated, amounting to 48.5% on the soft-palate level compared to 21.6% on the level of the epiglottis tip, and 14.6% on the hard-palate level. These results demonstrate that bilateral mandibular advancement surgery in Class II-Patients leads to significant increases in PAS volume and significant widening of the narrower sites inside the pharynx.