Machine Learning Tool Advances Research on Rheumatoid and Osteoarthritis

A team led by investigators at the Hospital for Special Surgery (HSS) in New York City reports that their computer vision tool effectively distinguishes rheumatoid arthritis (RA) from osteoarthritis (OA) in joint tissue taken from patients who underwent total knee replacement (TKR). The results suggest the machine learning model will help improve research processes in the short term and optimize patient care in the future, according to the researchers who presented their findings at the European Alliance of Associations for Rheumatology (EULAR) Congress 2022 in Copenhagen, Denmark. TKR is often the only management option for patients with severe knee joint damage, the scientists said, who added that identifying which disease caused the joint damage is essential for guiding treatment plans, given that RA is a systemic, inflammatory disease that may also affect the eyes or lining around the heart, while OA affects just the joints. "We know there are many more immune cells present in the synovium, or joint tissue, of patients with RA compared to those with OA," said Bella Mehta, MBBS, rheumatologist at HSS. "But precisely how many more has not been clear." "Pathologists typically assess images of synovium to determine the extent of inflammation using a combination of approaches, including assigning the level of immune cell infiltration on a scale from 0 to 4," noted Dana Orange, MD, rheumatologist at HSS, and assistant professor at Rockefeller University.