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DESCRIPTION (provided by applicant): Osteoarthritis (OA) affects over 50 million Americans and has a substantial impact on the US economy and the health care system. Currently, there is no cure for this debilitating disease and the effective treatment is, at best, focused on symptomatic relief. The conventional MR techniques have shown promise for the identification of more subtle morphologic alterations as determined by cartilage volume, or surface fibrillation. However, they even the more innovative of these conventional techniques have not been consistent in predicting the knee OA progression. Therefore, there is a high demand for reliable, objective, non-invasive and quantitative imaging markers that identifies the risk population at early stage. The long-term goal of this proposal is to develop, implement, and characterize novel fluid suppressed-3D-23Na-UTE- techniques for in- vivo knee applications on an ultra high field system (7T). High-resolution, 23Na-(aggrecan) and 1H-(morphology, collagen) imaging of cartilage, along with improved imaging pulse sequences, image reconstructions, and visualization methods on an ultra-high field system (7T) will significantly impact the objective assessment of OA pathology. Specifically, this proposal will establish a powerful non-invasive imaging biomarker that is clinically useful for staging OA disease severity, predicting risk for progression and possibly serving as a future imaging biomarker for disease modifying therapies for OA. We will acquire high resolution sodium and proton MRI of age-and gender matched OA subjects in a longitudinal fashion to determine whether baseline combined risk profile can predict risk population for severe knee OA progression over 24 months period. Finally we determine the role of combined sodium and proton-MRI (1H-morphology, T2 mapping, and clinical scorings) findings at baseline in OA subjects in the prediction of knee OA progression over 24 months period. Once developed, validated in human knee joint then the sodium methodology will be translated on to a clinically relevant 3T platform. We believe that these studies will profoundly affect not only to diagnose OA in its earliest stages but also possibly identifies the risk population at early stage. We plan to address these goals via an interdisciplinary collaboration between Chemistry, Radiology, and Rheumatology to identify a risk profile that will be clinically useful to predict those at risk for disease progression.
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Multiparametric Mapping of Knee Joint with Magnetic Resonance Fingerprinting
Multiparametric Mapping of Knee Joint with Magnetic Resonance Fingerprinting
Data-Driven Learning Framework for Fast Quantitative Knee Joint Mapping
Data-Driven Learning Framework for Fast Quantitative Knee Joint Mapping
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