RESUMEN
Computational fluid dynamics (CFD) modelling has made significant contributions to the analysis and treatment of obstructive sleep apnoea (OSA). While several investigations have considered the flow field within the airway and its effect on airway collapse, the effect of breathing on the pharynx region is still poorly understood. We address this gap via a combined experimental and numerical study of the flow field within the pharynx and its impacts upon airway collapse. Two 3D experimental models of the upper airway were constructed based upon computerised tomography scans of a specific patient diagnosed with severe OSA; (i) a transparent, rigid model for flow visualisation, and (ii) a semi-flexible model for understanding the effect of flow on pharynx collapse. Validated simulation results for this geometry indicate that during inhalation, negative pressure (with respect to atmospheric pressure) caused by vortices drives significant narrowing of the pharynx. This narrowing is strongly dependent upon whether inhalation occurs through the nostrils. Thus, the methodology presented here can be used to improve OSA treatment by improving the design methodology for personalised, mandibular advancement splints (MAS) that minimise OSA during sleep.
Asunto(s)
Apnea Obstructiva del Sueño , Simulación por Computador , Humanos , Hidrodinámica , Orofaringe/diagnóstico por imagen , Faringe/diagnóstico por imagenRESUMEN
Accurate prediction of deformation and collapse of the upper airway during breathing is required for effective and personalised treatment of obstructive sleep apnoea (OSA). While numerical modelling techniques such as fluid-structure interaction (FSI) are promising, an outstanding challenge is to accurately predict the deformation of the airway during breathing and thus the occurrence of OSA. These difficulties arise because the effective stiffness of the soft tissue in the human upper airway varies due to neuromuscular effects on the stiffness of the underlying muscles. In addition, both the elasticity and anisotropy of the soft tissues along the upper airway are poorly characterised. Finally, gravitational effects on anatomic features are yet to be considered. In this study, a validated FSI technique is introduced that allows prediction of the extent and position of the major deformation in the upper airway. This technique is used to analyse the behaviour of the upper airway in the two most common sleeping positions and for a range of effective tissue stiffnesses. The results demonstrate that sleeping position, gravity and soft tissue stiffness (used here as a proxy for neuromuscular effects) are the main factors that affect upper airway collapse. Therefore, this study provides new insights into the mechanisms of OSA and a new methodology that significantly advances the patient-specific treatment of OSA.