The long-term goal of this research is to develop and validate novel imaging and biomechanical modeling techniques to identify factors that contribute to joint injury and disease in individual patients.
The first aim of this research is to develop and validate a system to quantify joint kinematics in vivo using real-time magnetic resonance imaging (MRI). Real-time (MRI) provides a unique imaging modality to investigate the motion of healthy and pathological joints.
The second aim i s to develop an image-based modeling pipeline to estimate cartilage stress in vivo under physiological loading conditions. Finally, we will use this modeling framework to investigate the etiology of a common musculoskeletal disorder, patellofemoral (PF) pain. To achieve these aims, we will first improve the spatial and temporal resolution of the real-time MRI for musculoskeletal imaging. A rigid-body tracking technique will then be used to extract three-dimensional motion of bones from the real-time images. The accuracy of this system will be tested by tracking the motion of an MR-compatible dynamic phantom. An image-based finite element (FE) modeling pipeline will then be developed to incorporate patient-specific cartilage material properties obtained from MRI. A cadaver study will be carried out to correlate T1 and T2 relaxation times of cartilage from MRI with cartilage stiffness. Muscle forces for the FE model will be estimated using a musculoskeletal model that takes into account patient-specific muscle activation patterns. Finally, these imaging and modeling tools will be used to evaluate the mechanical etiology of PF pain. We will test a common clinical hypothesis, that PF pain is related to increased cartilage stress. We will estimate in vivo cartilage stress in a group of PF pain patients (n=40) and a group of pain-free controls (n=20) during static and dynamic squatting tasks. We will investigate a number of factors that may influence the cartilage stress, including: PF joint maltracking, contact area, joint contact forces, altered cartilage stiffness, and cartilage thickness. Musculoskeletal injuries and diseases are serious public health issues. The knee joint is particularly susceptible to injuries, which can lead to prolonged periods of inactivity, accelerated onset and progression of osteoarthritis and other health problems. The novel imaging and biomechanical modeling techniques developed in this research will be used to improve the diagnosis and treatment of a range of musculoskeletal disorders.
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