Development of Automated Techniques for Modelling Cartilage Morphology and Mechanics

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PROPOSAL MOTIVATION: Our research group develops subject-specific finite element models of bone, soft tissue and joints. These models employ clinical imaging tools (like CT and MRI) to define tissue geometry and material properties. Using these tools, we recently observed marked differences in bone stress between people affected with knee osteoarthritis, a debilitating joint disease, and individuals with healthy knees. These findings led to a collaboration with researchers from the Multicenter Osteoarthritis Study (MOST) to study bone stress and strain in 2100 volunteers (4200 knees) longitudinally evaluated with CT and MRI at different stages of osteoarthritis disease progression (healthy, early disease stage, late disease stage). Our models accurately predict bone mechanical behavior. It is unclear how well they predict cartilage mechanical behavior. OBJECTIVES: The proposed research program aims to advance our finite element modeling technique by addressing the following short term research objectives, with a focus on the patellofemoral joint (region under kneecap): [OBJECTIVE 1] Develop valid representations of cartilage thickness, volume and area, as well as contact area, within our finite element model; [OBJECTIVE 2] Validate non-invasive predictions of cartilage stiffness and contact stress offered by the finite element model; [OBJECTIVE 3] Characterize measurement errors for non-invasive estimates of contact stress as well as cartilage thickness, volume, surface area and contact area. Developments arising from this research will support long-term objectives focused on developing a complete finite element model of the knee incorporating bone, cartilage and all supportive structures (menisci, ligaments). IMPACT: This research will enable large scale finite element modelling of bone, cartilage and articulating joints, thereby advancing subject-specific finite modelling closer to clinical application and practice. This research will train highly qualified personnel to pursue careers in natural science and engineering research and industry where developed technical skills are highly sought. In addition, we will collaborate with clinical researchers to apply the developed techniques to further understanding of the role of mechanics in etiology, prognosis and prevention of degenerative joint disease. These techniques, and related knowledge, can provide bases for developing new diagnostic tools for early disease detection.