A feasibility study of template-based subject-specific modelling and simulation of upper-airway complex

The upper-airway complex is involved in a number of life-sustaining functions, such as swallowing, speech, breathing and chewing. Disorders associated with these functions can dramatically reduce the life quality of the suffers. Biomechanical modelling is a useful tool that can bridge the gap between the human knowledge and medical data.When tailored to individual patients, biomechanical models can augment the imaging data, to enable computer-assisted diagnosis and treatment planning. This thesis introduces a model-registration framework for creating subject-specific models of the upper-airway complex based on 3D medical images.Our framework adapts a state-of-art comprehensive biomechanical model of head and neck, which represents the generic upper-airway anatomy and function. By morphing this functional template to subject-specific data, we create upper-airway models for particular individuals. In order to preserve the functionality of the comprehensive model, we introduce a multi-structure registration technique, which can maintain the spatial relationship between the template components, and preserve the regularity of the underlying mesh structures. The functional information, such as the muscle attachment positions, joint positions and biomechanical properties, is updated to stay relevant to the subject-specific model geometry. We demonstrate the functionality of our subject-specific models in the biomechanical simulations. Two illustrative case studies are presented. First, we apply our modelling methods to simulating the normal swallowing motion of a particular subject based on the kinematics (of the airway boundary, jaw and hyoid) extracted from dynamic 3D CT images. The results suggest that our model tracks the oropharyngeal motion well, but has limited ability to reproduce the hyolaryngeal movements of normal swallowing. Second, we create two speaker-specific models based on 3D MR images, and perform personalized speech simulations of the utterance ageese. The models reproduce the speech motion of the tongue and jaw recorded in tagged and cine MRI data with sub-voxel tracking error, predict the muscular coordinating patterns of the speech motion. This study demonstrates the feasibility of using template-based subject-specific modelling methods to facilitate personalized analysis of upper-airway functions. The proposed model-registration framework provides a foundation for developing a systematic and advanced subject-specific modelling platform.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat