Assessing the efficiency of a Mandibular Advancement Device to treat obstructive Sleep Apnea using Computational Fluid Dynamics

Abstract

Obstructive Sleep Apnea (OSA) is a condition in which the patient repeatedly stops breathing during sleep due to the collapse of the upper airway. The upper airway collapse is caused by a relaxation of the upper airway muscles, combined with a decrease in intraluminal pressure and hence an increase in external pressure from the surrounding tissue. A possible treatment that is becoming more and more popular, due to its reversibility, is the oral intervention like a Mandibular Advancement Device. This device brings the mandibula forward in order to increase the upper airway volume and prevent total upper airway collapse during sleep. The patient only uses the device during the night. However the efficiency of the MAD can vary significantly from patient to patient. The use of Computational Fluid Dynamics allows for a prediction of the outcome of a treatment with an MAD. This makes it possible to compare upper airway volume and to determine the upper airway resistance (UAR) through finite volume flow simulations for both cases. Boundary conditions for the model are obtained from the patient during a sleep study. Therefore the flow modelling is based on patient specific geometry and patient specific boundary conditions. A mesh dependency and turbulence dependency study was performed. Whenever the simulations showed a decrease in upper airway resistance, also a clinical improvement was observed. Clinical improvements are measured by looking at the apnea-hypopnea index (AHI) which indicates the number of events (upper airway closures or near closures) per hour and the snoring index quantifying the degree of snoring. In conclusion, one can say that the combination of advanced imaging and functional analysis shows a large potential for future medical treatments.