Can MDCT Measures of Upper Airway Dimensions and Central Obesity Indices Predict the Severity of Obstructive Sleep Apnea (OSA)?
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- Category: Vol. 88, June 2020
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Can MDCT Measures of Upper Airway Dimensions and Central Obesity Indices Predict the Severity of Obstructive Sleep Apnea (OSA)?, BASMA GADELHAK, MONA EL-BESHBISHI, EMAN EL-NADY and MOHAMED EL-GAMAL
Abstract
Background: Comparative evaluation of the CT measures of upper air way, tongue adiposity and central obesity in a group of obstructive sleep apnea (OSA) patients and in a control group, and their potential role in grading of OSA severity. Aim of Study: The objective of the present study was to comparatively evaluate the different the upper air way, tongue adiposity and central obesity measures by CT scan in patients with obstructive sleep apnea syndrome (OSA) and in a control group, and their potential role in grading of OSA severity. Material and Methods: This prospective case control study was carried out on 17 OSA patients diagnosed by PSG and 16 control subjects. Non contrast MDCT scan of the upper airway and mid abdomen was performed on Philips 128 detector scanner, 1mm slice collimation during quite breathing. Axial and Sagittal reformatted images were assessed. Man-dibular plane hyoid distance (MPH), upper airway length (UAL), minimum cross-sectional area (MCA), transverse and antero-posterior diameters of the airway (TDA, APD), length and thickness of uvula and soft palate (LUV,TUV), tongue area and tongue base density (TA, TD) were measured. Image J program was used for quantification of neck and visceral adipose tissue (NAT, VAT). Results: Statistically significant difference was found in most CT measures between the OSA and control groups, the highest significant values were found with MCA, TDA, TUV and TA (p<0.005). MCA and TA had the best diagnostic performance for OSA diagnosis. Statistically significant difference was found in MPH, UAL, MCA, TDA, TA, TD and NAT between the severe OSA and mild/moderate grades, The highest significant values was found with UAL and MCA (p=0.001, 0.002). For identifying severe OSA MCA, TDA and TA offered high diagnostic performances. Binary logistic regression found that TA and MPH were the significant predictors for severe OSA with overall % predicted=88.2%. Conclusion: Our results indicate that CT offers added value in OSA diagnosis and prediction of severity, multiple CT measures varied significantly between OSA and control group as well as between different OSA grades.