Osteoarthritis is a progressive degenerative joint disease which causes pain, inflammation, and eventual loss of joint function. This debilitating disease affects approximately 3% of U.S. adults over 30 years old, with direct medical costs of over $100 billion each year. Post-traumatic osteoarthritis is a sub-set of osteoarthritis initiated by injuries such as a fracture of the joint surface. When a surgeon reconstructs a fractured joint, there are often residual incongruities on the surface, which can lead to elevated contact stresses. Increased cartilage contact stress has been shown to be a major risk factor for developing post-traumatic osteoarthritis. Computational modeling offers a method of detecting elevated contact stresses and thereby assessing the associated risk of a patient developing post-traumatic osteoarthritis. Discrete element analysis (DEA) is a computational method capable of fast and reliable contact stress predictions that has been used successfully to predict knee and ankle osteoarthritis. The purpose of this study was to validate the accuracy of DEA models of both intact and fractured hips by directly comparing experimentally measured intra-articular contact stresses in human cadaveric hips to corresponding DEA predictions. Overall correlation was greater than 90% for both intact and fractured hips. The validated DEA algorithm was then applied to a series of 3 patients with a hip fracture and another series of 19 patients with surgical hip re-alignment. As anticipated, changes in contact stress correlated well with pain and function (p < 0.05). This validated DEA model appears to be a clinically useful tool for identifying patients who are at higher risk for developing osteoarthritis as a result of elevated joint contact stresses.

Acetabular dysplasia, a deformity characterized by the presence of a shallow acetabulum inadequately covering the femoral head, alters force transfer through a joint, causing early-onset hip pain and degeneration. Dysplasia is often treated surgically with a periacetabular osteotomy (PAO), which permits multiplanar acetabular reorientation to stabilize the joint and alleviate pain. PAO alters joint mechanics, including contact stress, which can be assessed via computational methods. This work sought to enhance a discrete element analysis (DEA) model for assessment of the dysplastic hip. The primary focus was on understanding how the gait parameters used to load a DEA model affect the computed contact stress. Several additional studies focused on understanding specific anatomic and demographic factors contributing to the contact stress evaluation were also performed. Implementation of a dysplastic gait pattern to load the DEA models resulted in more cases with improved contact stress and clinical measures after PAO, which concurred with clinical findings. Patient demographics and acetabular and femoral geometry all affected the computed contact stress distributions, emphasizing the importance of proper cohort categorization prior to interpretation of DEA-calculated contact stress. These results indicate that accurate modeling of the particular deformity in this cohort likely requires evaluation of both functional and anatomic differences. These studies improve the ability to realistically model and characterize dysplastic hip contact mechanics. DEA is a valuable tool for assessing contact stress in dysplastic joints, which has the potential to improve patient outcomes by guiding clinicians in non-operative treatment, pre-operative PAO planning, and evaluating intraoperative success.

Osteoarthritis (OA) is the most common type of arthritis, a disease in which inflammation and stiffness of the joints occur. This debilitating disease of the joints currently reigns as the most prevalent among the world's populations. Of particular interest to our group is the study of the biomechanical factors relating to knee OA. Studies have shown that knee OA is related to multiple biomechanical factors, all of which are complexly interrelated. These factors have been seen to produce varied effects on the structures of the knee. This work examines validation of a computational model implementing discrete element analysis, and discusses the potential for large-scale, subject-specific modeling of the knee. In particular, contact stress can be estimated using this technique, and these estimates can potentially be related to OA onset in subjects.