Computational Modeling of Upper Airway Before and After Adenotonsillectomy for Obstructive Sleep Apnea

Abstract

Adenotonsillectomy, the first-line surgical treatment for obstructive sleep apnea (OSA) in children, is successful in only 50% of obese children. Computational fluid dynamics tools, which have been applied to differentiate OSA patients from those without OSA based on the airway flow characteristics, can be potentially used to identify patients likely to benefit from surgical intervention. We present computational modeling of the upper airway before and after adenotonsillectomy in an obese female adolescent with OSA. The subject underwent upper airway imaging on a 1.5 Tesla magnetic resonance imaging (MRI) scanner, and three-dimensional airway models were constructed using airway boundary coordinates from cross-sectional MRI scans. Our results using computational simulations indicate that, in an obese child, the resolution of OSA after adenotonsillectomy is associated with changes in flow characteristics that result in decreased pressure differentials across the airway walls and thus lower compressive forces that predispose to airway collapse. Application of such findings to an obese child seeking surgical treatment for OSA can potentially lead to selection of the surgical procedure most likely to result in OSA resolution. Effective intervention for OSA in this high-risk group will result in reduction in morbidity and the public health concerns associated with OSA.