Computational study on obstructive Sleep Apnea Syndrome using patient - Specific models

Abstract

Obstructive Sleep Apnea Syndrome (OSAS) is a common sleep disorder. It is characterized by repeated occlusion of upper airway and discontinuation of sleep. The breathing pauses and starts again with a loud snort. There may even be an abrupt interruption of sleep to maintain the patency of the airway. The pressure drop along the pharyngeal pathway should be a good indicator to show the severity of the pathological airways. Computational Fluid Dynamics (CFD) has become an important tool in investigating the internal flow dynamics of the respiratory system, especially for the upper airway. It provides a non-invasive environment for the analysis of the biological flow. Employing such technology, this study will provide insight for a male patient with severe OSAS. This patient also underwent surgical procedures to improve the size of the airway. The pre-operative and post-operative CT scans were reconstructed and converted to two patient-specific, three- dimensional models suitable for numerical simulations. The inhalation process was simulated using a constant volume flow rate, 0.3 liter per second (L s -1), at the nostrils for both cases. An index, the 'resistance of the airway', was defined as the pressure drop per unit flow rate to estimate the tendency of airway collapse. The pressure distribution from the velopharynx to hypopharynx was investigated. The pressure drops were 12.1 Pascal (Pa) and 7.3 Pascal before and after surgical treatment respectively. The resistance of airway changed from 40 Pa s L -1 to 24 Pa s L -1, a 40% reduction. The results showed that the pressure drop along the upper airway was reduced significantly after the surgical procedure. This decreased the collapsibility of the airway and consequently improved the sleep quality.