The infrapatellar fat pad (IPFP) plays an important role in the incidence of knee osteoarthritis (OA). However, whether the IPFP can serve as an independent biomarker for OA development is yet unknown. Radiomics is a powerful tool that can extract high-dimensional quantitative features for clinical outcomes. In this work, we proposed a prediction model for incident radiographic knee OA (iROA), using radiomic features of the IPFP, one year prior to diagnosis. The prediction performance was assessed, and our results from 604 knees demonstrated that MR-based radiomic features from the IPFP are predictive of iROA.
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