Multi-resolution modeling of thin bone structures in the human skeleton

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Finite element (FE) analysis is a powerful tool that has been used successfully to predict the strength of healthy and pathologic bones. Patient specific FE modeling is able to represent bony structures, which are highly heterogeneous in their presentation and thus difficult to represent with other analytical or parametrically developed techniques. The objective of this research is to develop and validate robust automated methods for accurate modeling of complex thin bone structures in the human skeleton. In this work it is hypothesized that multi-resolution/modality information and mesh morphing and mapping methods can be used to develop robust highly automated algorithms to generate multiple complex FE models of thin bone structures that accurately describe their mechanical behaviour. Specifically this project aims to: (1) Quantify the impact of CT resolution on thin bone FE model generation (2) Optimize standard / cone beam CT based FE model generation to represent thin bone architecture; (3) Characterize and model load transmission through thin bone articulations; (4) Develop mesh morphing and mapping methods to generate and parametrically analyse multiple thin bone structures; and (5) Experimentally validate FE models of the pelvis and craniofacial skeleton generated using the developed methodologies, characterizing their behaviour intact, following fracture and post-stabilization. Accurate assessment of the structural integrity of thin bone structures is essential in understanding anatomical differences, pathological processes, traumatic injuries and the mechanical requirements necessary for successful clinical interventions. The interdisciplinary nature of this research and the advanced computational and experimental facilities provide an exceptional training ground in which students can develop truly marketable biomedical engineering skills. Automated techniques that can accurately represent the mechanical behaviour of thin bone structures will enhance the clinical potential of FE analysis and motivate its continued use in musculoskeletal biomedical research and design.