Overall, the algorithm predicted osteoarthritis with 78% accuracy from MRIs performed three years before symptom onset, picking up signs of the disease that are too subtle to register in radiologists’ eyes.
Currently, there are no drugs that prevent presymptomatic osteoarthritis from developing into full-blown joint deterioration, but drugs that can prevent patients from developing a related condition—rheumatoid arthritis—do exist.
In a news release, the researchers say a current goal is to more easily develop the same types of drugs for osteoarthritis, in turn reducing the need for more invasive osteoarthritis treatment.
“Instead of recruiting 10,000 people and following them for 10 years, we can just enroll 50 people whom we know are going to be getting osteoarthritis in two or five years,” adds study co-author Kenneth Urish, MD, Ph.D., associate medical director of the bone and joint center at the University of Pittsburgh Medical Center (UPMC) Magee-Women’s Hospital. “Then we can give them the experimental drug and see whether it stops the disease from developing.”
Source: https://www.healthimaging.com/topics/artificial-intelligence/osteoarthritis-early-diagnosis-machine-learning
