The overarching purpose of this proposal is to identify structural changes detectable by MRI (i.e., surrogate biomarkers) that precede the onset of radiographic knee osteoarthritis (ROA) and/or that predict the development of important clinical outcomes. Ultimately, this line of research will help to identify key risk factors for the development of osteoarthritis (OA) symptoms and OA structural disease progression. Specific Aim 1 will be to examine the relationship between features of joint morphology (i.e., joint structure and subchondral bone morphology) on MRI and progression (over Years 1 and 2) to important clinical outcomes over a 4-year follow-up period. This aim will be addressed through the evaluation of 1000 knees with symptomatic ROA from the OAI Progression cohort. Secondary clinical outcomes of interest include the progression of knee pain severity in individuals with ROA. Specific Aim 2 will be to identify the features of joint morphology (i.e., cartilage morphology, joint structure and subchondral bone morphology) on MRI that are associated with the development of ROA over 4 years of follow-up. This aim will be addressed using a nested case-control approach based on the OAI Incidence cohort. Features of joint morphology that will be examined include altered tibiofemoral cartilage morphology (i.e. subregional cartilage thickness), denuded bone area (dAB), altered joint structural determinants (i.e., large bone marrow lesions, full thickness cartilage defect, synovial effusion/synovitis, and/or meniscal abnormalities) and altered subchondral bone morphology (i.e., bone curvature and/or area of subchondral bone (tAB)). Important co-variates to be examined include age, gender, BMI, knee alignment, muscle quality and physical activity. The proposed study benefits from the ongoing collaborations and pooled intellectual resources of a multidisciplinary research team well experienced with the conduct of the OAI, collection of OAI data, processing of OAI radiographic and MR images, and analysis of and publication of OAI data. Since the investigators on this proposal have already been funded to perform some of the quantitative and semi-quantitative readings for OAI, we have built the funds requested in this proposal around existing or ongoing funded readings in order to maximize the efficiency of the analysis and extend the size of the datasets that will be analyzed by a given technique. Our plan also allows for direct comparison to and extension of the funded OAI MR readings and analyses that will be supplemented with our proposed MR readings and analyses.