A Three Dimensional Imaging-based Framework for Planning Maxillomandibular Advancement Surgery for the Treatment of Obstructive Sleep Apnoea

Abstract

Obstructive Sleep Apnoea (OSA), a sleeping disorder, is a serious health issue with significant public health implications. Due to the interrupted sleep, OSA patients suffer with excessive day-time sleepiness, fatigue and other health complexities that lead to on-road and work-related accidents and incur billions of dollars per year. Traditionally, treatment of OSA begins with nasal continuous positive airway pressure (CPAP). Alternatively, Mandibular Repositioning Appliances or surgical interventions can be used. Although Maxillomandibular Advancement (MMA) surgery is often advised as the last line of treatment due to the expense and significant changes in the facial appearance, it is the only permanent solution to OSA with a definitive outcome especially for the patients with significant facial deformation or anomalies. In this article, three dimensional (3D) image-guided predictive algorithms are proposed to improve the treatment planning and overall outcome of the MMA surgery. 3D analysis of the facial surface data and Computational Biomechanics-based 3D modelling of airway segmented from Cone Beam Computed Tomography (CBCT) data are proposed to predict the required physiological changes to ensure optimal air-flow through the airway. Moreover, 3D Computer Graphics-based techniques are proposed to visualise and demonstrate the expected facial outcomes to inform patients and surgeons prior to this non-reversible surgery.