Application of a novel atlas-based computational method to predict personalized knee osteoarthritis

An automated approach to predict personalized progression of knee osteoarthritis (OA) was developed and compared against 8-year follow-up data of 104 subjects. The developed approach was based on the subject information, subject-specific anatomical dimensions from MRI and finite element (FE) simulation. Based on the comparison between simulated and experimentally observed osteoarthritis grades, the developed approach was able to classify majority of the subjects into correct groups.