RESUMO
Novel biomarkers of upper airway biomechanics may improve diagnosis of obstructive sleep apnea syndrome (OSAS). Upper airway effective compliance (EC), the slope of cross-sectional area versus pressure estimated using computational fluid dynamics (CFD), correlates with apnea-hypopnea index (AHI) and critical closing pressure (Pcrit). The study objectives are to develop a fast, simplified method for estimating EC using dynamic MRI and physiological measurements and to explore the hypothesis that OSAS severity correlates with mechanical compliance during wakefulness and sleep. Five obese children with OSAS and five control subjects with obesity aged 12-17 yr underwent anterior rhinomanometry, polysomnography, and dynamic MRI with synchronized airflow measurement during wakefulness and sleep. Airway cross section in retropalatal and retroglossal section images was segmented using a novel semiautomated method that uses optimized singular value decomposition (SVD) image filtering and k-means clustering combined with morphological operations. Pressure was estimated using rhinomanometry Rohrer's coefficients and flow rate, and EC was calculated from the area-pressure slope during five normal breaths. Correlations between apnea-hypopnea index (AHI), EC, and cross-sectional area (CSA) change were calculated using Spearman's rank correlation. The semiautomated method efficiently segmented the airway with average Dice Coefficient above 89% compared with expert manual segmentation. AHI correlated positively with EC at the retroglossal site during sleep (rs = 0.74, P = 0.014) and with change of EC from wake to sleep at the retroglossal site (rs = 0.77, P = 0.01). CSA change alone did not correlate significantly with AHI. EC, a mechanical biomarker which includes both CSA change and pressure variation, is a potential diagnostic biomarker for studying and managing OSAS.NEW & NOTEWORTHY This study investigated the dynamics of the upper airway at retropalatal and retroglossal sites during wakefulness and sleep by evaluating the effective compliance (EC) of each site and its correlation with apnea-hypopnea index (AHI) using novel semiautomated image processing. AHI correlated significantly with retroglossal EC during sleep and change of retroglossal EC from wake to sleep. The results suggest EC as a promising noninvasive diagnostic marker for estimating the mechanical properties of various upper airway regions in patients with OSAS.