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Abstract #2947

Deriving a Cartilage Signature to Predict Joint Replacement in Osteoarthritis

Edward Peake1,2,3, Stefan Pszczolkowski1,2,3, Christoph Arthofer2,3,4, and Dorothee P Auer1,2,3
1NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, United Kingdom, 2Radiological Sciences, Division of Clinical Neuroscience, University of Nottingham, Nottingham, United Kingdom, 3Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, United Kingdom, 4Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom

Prediction of future knee replacement in osteoarthritis may support tailored decision making, and provide a surrogate outcome marker for clinical trials of diseases modifying osteoarthritis drugs. Fully automated cartilage segmentation is generated from knee MRI, and feature are extraction to create a radiomic signature for the prediction of knee replacement within 5 -years. The radiomic signature using univariate cox regression predicted surgery with a HR of 7.5 (p = 2e-28, 95% CI 7.1 – 7.9) which was higher than established clinico-demographic multivariate prediction model with HR 5.9 (p = 2e-28, 95%CI 5.6 – 6.2).

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