OMERACT validation of a deep learning algorithm for automated absolute quantification of knee joint effusion versus manual semi-quantitative assessment

Abstract

ObjectiveTo begin evaluating deep learning (DL)-automated quantification of knee joint effusion-synovitis via the OMERACT filter. MethodsA DL algorithm previously trained on Osteoarthritis Initiative (OAI) knee MRI automatically quantified effusion volume in MRI of 53 OAI subjects, which were also scored semi-quantitatively via KIMRISS and MOAKS by 2–6 readers. ResultsDL-measured knee effusion correlated significantly with experts’ assessments (Kendall's tau 0.34–0.43) ConclusionThe close correlation of automated DL knee joint effusion quantification to KIMRISS manual semi-quantitative scoring demonstrated its criterion validity. Further assessments of discrimination and truth vs. clinical outcomes are still needed to fully satisfy OMERACT filter requirements.