There are several disease conditions such as obesity, Polycystic Ovary Syndrome, and Downs Syndrome that are associated with upper airway restrictive disorders which often lead to Obstructive Sleep Apnea Syndrome (OSAS). If pediatric OSAS is not properly treated, its sequelae may include mood, behavioral, and learning difficulties, together with co-morbidities such as increased risk for heart disease, stroke, glucose intolerance, and hypertension. In the understanding of these conditions and in studying their treatment effects, it is important to take into account the dynamic nature of the upper airway in the natural human breathing state. As such, dynamic imaging protocols have been investigated in the study of the upper airway including MRI, CT, and Optical CT (OCT). While OCT offers high spatial and temporal resolution, it is intrusive, has poor depth of penetration, and has shadowing effects. CT affords good spatial and reasonable temporal resolution but has poor contrast resolution for soft tissue structures and has radiation concerns especially in the dynamic mode and in imaging children. Currently, therefore, dynamic MRI is the modality of choice in studying these diseases.
We have been studying pediatric OSAS for over 10 years via 3D and 4D MR image analysis for deriving image-based quantitative biomarkers. In this connection, we have developed 3D MRI segmentation methods based on AAR, minimally interactive 4D MRI segmentation methods, and quantitative image analytics. Some examples appear in the following figures. In the first figure, renditions of the upper airway structure segmented from a patient 4D image covering 10 phases (from top left to bottom right) over a respiratory period are displayed. The second figure shows heat maps illustrating differences in the relationships among the shape lengths of 14 objects in the vicinity of the upper airway for obese children without (left) and with (right) OSAS.