AI detects osteoarthritis years before it develops

Researchers at the University of Pittsburgh School of Medicine and Carnegie Mellon University College of Engineering have created a machine learning algorithm that can detect subtle signs of osteoarthritis—too abstract to register in the eye of a trained radiologist—on an MRI scan taken years before symptoms even begin.

Photo
Kundu et al. (2020) PNAS.
Source: potting Subtle Patterns In Knee Cartilage: The cartilage in this MRI scan of a knee is colorized to show greater contrast between shades of gray.

For this study, the researchers looked at knee MRIs from the Osteoarthritis Initiative, which followed thousands of people for seven years to see how osteoarthritis of the knee develops. They focused on a subset of patients who had little evidence of cartilage damage at the beginning of the study.

In retrospect, we now know which of these participants went on to develop arthritis and which didn’t, and the computer can use that information to learn subtle patterns on the MRI scans of presymptomatic people that are predictive of their future osteoarthritis risk.

“When doctors look at these images of the cartilage, there isn’t a pattern that jumps out to the naked eye, but that doesn’t mean there’s not a pattern there. It just means you can’t see it using conventional tools,” said lead author Shinjini Kundu, M.D., Ph.D., who completed this project as part of her graduate training in the Pitt Medical Scientist Training Program and Carnegie Mellon Department of Biomedical Engineering.

To validate this approach, Kundu, who now is a resident physician and medical researcher at the Johns Hopkins Department of Radiology, trained the model on a subset of the knee MRI data and then tested it on patients it had never seen before. Kundu did this dozens of times, with different participants withheld each time, to test the machine learning algorithm on all the data.

Overall, the algorithm predicted osteoarthritis with 78% accuracy from MRIs performed three years before symptom onset. Currently, there are no drugs that prevent presymptomatic osteoarthritis from developing into full-blown joint deterioration, though there are a few highly effective drugs that can prevent patients from developing a related condition—rheumatoid arthritis.

The goal is to develop the same types of drugs for osteoarthritis. Several candidates already are in the preclinical pipeline. “Instead of recruiting 10,000 people and following them for 10 years, we can just enroll 50 people who we know are going to be getting osteoarthritis in two or five years,” Urish said. “Then we can give them the experimental drug and see whether it stops the disease from developing.”

The study was published this in PNAS.

Subscribe to our newsletter

Related articles

Machine learning algorithm detects early stages of Alzheimer's

Machine learning algorithm detects early stages of Alzheimer's

An artificial intelligence-based detects early stages of Alzheimer’s through functional magnetic resonance imaging.

Biomedical research: deep learning outperforms machine learning

Biomedical research: deep learning outperforms machine learning

Deep-learning methods have the potential to offer substantially better results, generating superior representations for characterizing the human brain.

AI accurately detects COVID-19 on chest x-rays

AI accurately detects COVID-19 on chest x-rays

Researchers have developed a new AI platform that detects COVID-19 by analyzing X-ray images of the lungs.

How AI can improve medical imaging

How AI can improve medical imaging

AI offers not only the possibility of better detection of a tumor, a skin lesion or some other indication but also can improve accuracy and efficiency for radiologists.

Self-learning algorithms analyze imaging data

Self-learning algorithms analyze imaging data

Artificial neural networks open up new possibilities in interpreting the time-consuming imaging ´data.

Deep learning-based image segmentation

Deep learning-based image segmentation

Scientists have presented a new method for configuring self-learning algorithms for a large number of different imaging datasets – without the need for specialist knowledge or very significant computing power.

Deep learning tool measures volume of cerebral ventricles

Deep learning tool measures volume of cerebral ventricles

Researchers have developed an AI tool that can measure the volume of cerebral ventricles on MRIs in children within about 25 minutes.

Deep learning enables screening for eye disease

Deep learning enables screening for eye disease

Researchers created a novel deep learning method that makes automated screenings for eye diseases such as diabetic retinopathy more efficient.

Deep learning platform accurately diagnoses dystonia

Deep learning platform accurately diagnoses dystonia

Researchers have developed a unique diagnostic tool that can detect dystonia from MRI scans, the first technology of its kind to provide an objective diagnosis of the disorder.

Popular articles