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Computational fluid dynamics for the assessment of upper airway response to oral appliance treatment in obstructive sleep apnea
Computational fluid dynamics for the assessment of upper airway response to oral appliance treatment in obstructive sleep apnea
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Computational fluid dynamics for the assessment of upper airway response to oral appliance treatment in obstructive sleep apnea
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Computational fluid dynamics for the assessment of upper airway response to oral appliance treatment in obstructive sleep apnea
Computational fluid dynamics for the assessment of upper airway response to oral appliance treatment in obstructive sleep apnea
Journal Article

Computational fluid dynamics for the assessment of upper airway response to oral appliance treatment in obstructive sleep apnea

2013
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Overview
Mandibular advancement splints (MAS), which protrude the lower jaw during sleep, are recognized as an effective treatment for obstructive sleep apnea (OSA) through their action of enlarging the airway space and preventing upper airway collapse. However a clinical challenge remains in preselecting patients who will respond to this form of therapy. We aimed to use computational fluid dynamics (CFD) in conjunction with patient upper airway scans to understand the upper airway response to treatment. Seven OSA patients were selected based on their varied treatment response (assessed by the apnea–hypopnoea index (AHI) on overnight polysomnography). Anatomically-accurate upper airway computational models were reconstructed from magnetic resonance images with and without MAS. CFD simulations of airflow were performed at the maximum flow rate during inspiration. A physical airway model of one patient was fabricated and the CFD method was validated against the pressure profile on the physical model. The CFD analysis clearly demonstrated effects of MAS treatment on the patient's UA airflow patterns. The CFD results indicated the lowest pressure often occurs close to the soft palate and the base of the tongue. Percentage change in the square root of airway pressure gradient with MAS (ΔΔPMax%) was found to have the strongest relationship with treatment response (ΔAHI%) in correlation analysis (r=0.976, p=0.000167). Changes in upper airway geometry alone did not significantly correlate with treatment response. We provide further support of CFD as a potential tool for prediction of treatment outcome with MAS in OSA patients without requiring patient specific flow rates.