Osteoarthritis (OA) is a degenerative joint disease, affecting more than 27 million people in the United States alone. This large affected population and the severe consequent debility of OA lead to significant expenses to the health care system. OA is characterized by biochemical, structural and morphologic degradation of components of the extracellular matrix (ECM) of articular cartilage. The ECM is composed of primarily two groups of macromolecules including proteoglycan (PG) and collagen fibers. Early diagnosis of cartilage degeneration would require the ability to non-invasively detect changes in PG concentration and collagen integrity before morphological changes occur. T1, T2 and T1? relaxation times are affected by these pathological processes and are the most widely used biochemical cartilage MRI sequences worldwide. The overarching goal of this proposal is to develop, optimize, and translate the magnetic resonance fingerprinting (MRF) framework, which allows for simultaneous, morphological, volumetric, and quantitative multiparametric mapping [T1, T2, T1?, B1+ and proton density (PD)] to the knee joint in a much shorter time (?10 minutes) than conventional individual parametric mapping on a standard 3T clinical scanner. The proposed MRF-based multiparametric mapping approach can be easily incorporated into routine research/clinical protocols for multi- tissue assessment of the knee joint without exogenous contrast agents and could serve as future imaging biomarkers for disease modifying therapies for OA.
The current proposal will establish a powerful non-invasive imaging biomarker based on development of rapid, simultaneous multiparametric relaxation mapping of knee joint with magnetic resonance fingerprinting (MRF).
