Computed Tomography Characterization and Comparison With Polysomnography for Obstructive Sleep Apnea Evaluation

• Main Authors: Apirakkittikul, N. (Author), Bhongmakapat, T. (Author), Chousangsuntorn, K. (Author), Laothamatas, J. (Author), Sungkarat, W. (Author), Supakul, N. (Author)
• Format: Article
• Language: English
• Published: W.B. Saunders 2018
• Subjects: adult; Adult; airway obstruction; apnea; Article; body mass; Body Mass Index; clinical trial; collapse; comparative study; computer assisted tomography; confidence interval; controlled study; Cross-Sectional Studies; cross-sectional study; diagnostic imaging; human; Humans; logistic regression analysis; major clinical study; multivariate analysis; neck circumference; nose; Nose; odds ratio; pathology; pathophysiology; pharynx; Pharynx; polysomnography; Polysomnography; Prospective Studies; prospective study; respiratory disturbance index; Sleep Apnea, Obstructive; sleep disordered breathing; Tomography, X-Ray Computed; univariate analysis; waist circumference; wakefulness; x-ray computed tomography
• Online Access: View Fulltext in Publisher

 Purpose: We hypothesized that computed tomography (CT) combined with portable polysomnography (PSG) might better visualize anatomic data related to obstructive sleep apnea (OSA). The present study evaluated the CT findings during OSA and assessed their associations with the PSG data and patient characteristics. Patients and Methods: We designed a prospective cross-sectional study of patients with OSA. The patients underwent scanning during the awake state and apneic episodes. Associations of the predictor variables (ie, PSG data, respiratory disturbance index [RDI]), patient characteristics (body mass index [BMI], neck circumference [NC], and waist circumference [WC]), and outcome variables (ie, CT findings during apneic episodes) were assessed using logistic regression analysis. The CT findings during apneic episodes were categorized regarding the level of obstruction, single level (retropalatal [RP] or retroglossal [RG]) or multilevel (mixed RP and RG), degree of obstruction (partial or complete), and pattern of collapse (complete concentric collapse [CCC] or other patterns). Results: A total of 58 adult patients with OSA were scanned. The mean ± standard deviation for the RDI, BMI, NC, and WC were 41.6 ± 28.55, 27.80 ± 5.43 kg/m 2 , 38.3 ± 4.3 cm, and 93.8 ± 13.6 cm, respectively. No variables distinguished between the presence of single- and multilevel airway obstruction in the present study. A high RDI (≥30) was associated with the presence of complete obstruction and CCC (odds ratio 6.33, 95% confidence interval 1.55 to 25.90; and odds ratio 3.77, 95% confidence interval 1.02 to 13.91, respectively) compared with those with a lesser RDI. Conclusions: An increased RDI appears to be an important variable for predicting the presence of complete obstruction and CCC during OSA. Scanning during apneic episodes, using low-dose volumetric CT combined with portable PSG provided better anatomic and pathologic findings of OSA than did scans performed during the awake state. © 2017 The Authors