The apnea-hypopnea index is widely regarded as a measure of the severity of obstructive sleep apnea (OSA), a condition characterized by recurrent episodes of apnea or hypopnea during sleep that induce airway collapse. OSA is a catastrophic problem due to the wide range of health issues it can cause, including cardiovascular disease and memory loss. This review was conducted to clarify the roles of various imaging modalities, particularly conebeam computed tomography (CBCT), in the diagnosis of and preoperative planning for OSA. Unfortunately, 2-dimensional imaging techniques yield insufficient data for a comprehensive diagnosis, given the complex anatomy of the airway. Three-dimensional (3D) imaging is favored as it more accurately represents the patient’s airway structure. Although computed tomography and magnetic resonance imaging can depict the actual 3D airway architecture, their use is limited by factors such as high radiation dose and noise associated with the scans. This review indicates that CBCT is a low-radiation imaging technique that can be used to incidentally identify patients with OSA, thereby facilitating early referral and ultimately enhancing the accuracy of surgical outcome predictions.

Purpose: The aim of this study was to explore the correlations of cone-beam computed tomographic findings with the apnea-hypopnea index in patients with obstructive sleep apnea. Materials and Methods: Forty patients with obstructive sleep apnea were selected from the ear-nose-throat (ENT) outpatient clinic, Faculty of Medicine, Mansoura University. Cone-beam computed tomography was performed for each patient at the end of both inspiration and expiration. Polysomnography was carried out, and the apneahypopnea index was obtained. Linear measurements, including cross-sectional area and the SNA and SNB angles, were obtained. Four oral and maxillofacial radiologists categorized pharyngeal and retropalatal airway morphology and calculated the airway length and volume. Continuous data were tested for normality using the KolmogorovSmirnov test and reported as the mean and standard deviation or as the median and range. Categorical data were presented as numbers and percentages, and the significance level was set at P<0.05. Results: The minimal value of the cross-sectional area, SNB angle, and airway morphology at the end of inspiration demonstrated a statistically significant association (P<0.05) with the apnea-hypopnea index, with excellent agreement. No statistically significant difference was found in the airway volume, other linear measurements, or retropalatal airway morphology. Conclusion Cone-beam computed tomographic measurements in obstructive sleep apnea patients may be used as a supplement to a novel radiographic classification corresponding to the established clinical apnea-hypopnea index classification.