2018 Volume 64 Issue 8 Pages 456-463
Obstructive sleep apnea (OSA) is a social problem that can lead to cardiovascular disease, traffic accidents resulting from daytime sleepiness, and other effects due to sleep breathing disorders. Polysomnography (PSG) testing is necessary for the diagnosis of OSA at a professional medical facility but not all medical facilities can perform PSG testing. However, Japan has the highest number of computed tomographic (CT) scanners per capita, and the frequency of CT imaging is high. Therefore, CT imaging was studied to determine whether it can predict the severity of OSA and might be useful for understanding the anatomical pathophysiology of OSA.
We enrolled 326 consecutive male patients with OSA who were younger than 65 years of age, given a diagnosis of PSG, and consented to CT imaging from April 2014 through March 2015 at the Ota Memorial Sleep Center (Kanagawa). We measured the details of the maxillofacial structure of each OSA patient by three-dimensionally constructing their CT data. All measurements, clinical findings, and patient backgrounds were evaluated by multiple regression analysis. Further, the results were evaluated in OSA patients divided into 2 groups according to their level of obesity.
The group of non-obese (BMI <25kg/m2) OSA patients included 159 patients. Independent predictors of OSA were the hyoid position, the airway volume of the pharynx, the size of the tonsils, age, the anteroposterior length of the cranium, and the length of the tongue (R2=0.374). The group of obese (BMI ≥25 kg/m2) OSA patients comprised 167 patients. Selected independent predictors were the hyoid position, the BMI, and the anteroposterior length of the mandibular body (R2=0.393).
A prediction equation created from the maxillofacial CT data can be used to predict the severity of OSA. In the future, we will develop standards for the CT analysis of these data to predict the severity of OSA.