Hip dysplasia is a condition which arises during early childhood, involving a sub-optimally shaped interaction between the proximal femur and the acetabulum. If undiagnosed or untreated, hip dysplasia is associated with joint pain, stiffness and an increased likelihood of the need for a total hip replacement. There are two types of hip dysplasia; unstable and stable. Intervention is always necessary to treat unstable hip dysplasia, but treatment strategies for stable hip dysplasia are much less definitive. Untreated stable hip dysplasia is associated with an increased risk of a THR in the fifth decade of life, but there is currently no established way to quantify the risk of future joint disease in a child with stable hip dysplasia. There is also no established definition of what constitutes a “normal” or “abnormal” paediatric hip joint shape, a challenge which is compounded by the dramatic changes in hip shape which occur over childhood. There is no established or accepted way to decide on whether or not surgery should be performed on a child diagnosed with stable hip dysplasia in order to reduce their future risk of needing a hip replacement in midlife, a major gap which is addressed by the proposed research.
80% of total hip replacement across all ages can be attributed to conditions which affect hip morphology during childhood or adolescence. However, the quantifiable correlation between hip morphology variation and osteoarthritis risk is unknown. We will use an automated system of analysis and a novel 2D reference system for the hip joint to characterise identify hip joint shape features linked with the need for a joint replacement. We have already developed an artificial intelligence model and training has reached a first stage. Refinement needs to follow, and we plan to the analysis upwards of 100,000 images. This will be the largest such study ever completed. We will correlate radiological markers of morphology that led to osteoarthritis and total hip replacement. We will then use this to identify treatable morphologies in paediatric and young adult patients using AI. This information will give doctors and patients information on the chances of hip replacement in the future and help with decisions on who will benefit from preservation surgery.