Grant: Undergraduate: Mobility, musculoskeletal health and arthritis - ICS

Mechanical behaviour of the Craniofacial Skeleton (CFS) under physiological loads is poorly understood. The complex structure of the CFS defies reduction to analogous or simpler components, and demands a complete characterization of its biomechanics to gain insight into its key structural components. High rates of morbidity and revision surgery in the CFS (up to 50%) due to an inability to accurately optimize bone healing and long-term stability are issues due to lack of knowledge of CFS biomechanics. The objective of this research is to characterize the mechanical behaviour of thin bone structures in the CFS under physiological loads based on morphologically accurate computational finite element (FE) models. This project involves the use of micro-level image analysis, development and analysis of experimentally validated FE models along with mechanical design, materials science and biomechanical testing. Additionally, a newly developed and validated automated deconvolution filter based algorithm will be used to locally correct intensity and geometry data from clinical CT scans; allowing for accurate segmentation and modeling of thin bone regions and articulations (sutures). The performance of the specimen specific FE models (n=6) is measured through a strain-based comparison to mechanical testing data under temporalis and masseter muscle loading. If the characterization of the mechanical patterns in CFS are successful, automated segmentation techniques optimized for thin bone structures can be implemented to rapidly generate FE models. These models will allow for accurate representations of strain patterns in the CFS. Ultimately, they can serve as a biomechanical framework for rational design of new treatments and practices for CFS injuries and pathologies. In addition, this project maybe significant to other orthopaedic applications with respect to understanding biomechanical behaviour such as preventing musculoskeletal injury and improving repair and regeneration.