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

In terms of pathophysiology, an anatomically narrow airway is a predisposing factor for obstruction of the upper respiratory tract. The correlation between the nasopharyngeal airway and the craniofacial structures is discussed in this context. Thus a mutual interaction between the pharynx and the mandibular position was demonstrated, whereby the transverse dimension of the nasopharynx was significantly larger in patients with prognathism than in patients with retrognathism. The influence of chronic obstruction of the nasal airway on craniofacial development was also discussed. The form-and-function interaction, which ought to explain the causal relationship between nasal obstruction and craniofacial growth, appears to be of a multifactorial rather than a one-dimensional, linear nature. It is not disputed, however, that expanding the maxilla improves not only nasal volume and nasal flow, but also the subjective sensation of patients, although it is not possible to make a prognostic statement about the extent of this improvement because of the differing reactions of individuals. Orthodontic appliances for advancing the mandible can also be successfully used in the treatment of mild obstructive sleep apnea syndrome. This treatment method should be considered particularly for patients who are unwilling to undergo or cannot tolerate CPAP (continuous positive airway pressure) treatment

Artificial intelligence in orthodontics

Purpose The aim of this investigation was to create an automated cephalometric X-ray analysis using a specialized artificial intelligence (AI) algorithm. We compared the accuracy of this analysis to the current gold standard (analyses performed by human experts) to evaluate precision and clinical application of such an approach in orthodontic routine. Methods For training of the network, 12 experienced examiners identified 18 landmarks on a total of 1792 cephalometric X-rays. To evaluate quality of the predictions of the AI, both AI and each examiner analyzed 12 commonly used orthodontic parameters on a basis of 50 cephalometric X-rays that were not part of the training data for the AI. Median values of the 12 examiners for each parameter were defined as humans' gold standard and compared to the AI's predictions. Results There were almost no statistically significant differences between humans' gold standard and the AI's predictions. Differences between the two analyses do not seem to be clinically relevant. Conclusions We created an AI algorithm able to analyze unknown cephalometric X-rays at almost the same quality level as experienced human examiners (current gold standard). This study is one of the first to successfully enable implementation of AI into dentistry, in particular orthodontics, satisfying medical requirements