Shoulder disorders account for the second largest number of musculoskeletal cases in the United States with a large health care burden. The current standard for diagnosis of shoulder disorders is a clinical exam, visual motion assessment and in some cases, costly magnetic resonance (MR) imaging. However, specific tissue pathologies are not always accurately identified, and often not directly linked to the magnitude of dysfunction. There is a need for categorizing or sub-grouping patients based on the underlying movement dysfunctions with which they present. Video fluoroscopy is a common clinical tool that can improve the accuracy of motion analysis. The investigators are using 2-D fluoroscopy, combined with 3-D MR imaging to measure shoulder motion. From the motion analysis we can predict areas of potential soft tissue disease, and compare these to disease locations from MR imaging. The investigators hypotheses is that our motion based predicted disease locations will be significantly associated with disease locations from MR imaging.
