WASHIGTON DC, 19th January, 2024 (WAM) -- Artificial intelligence (AI) has the potential to detect rheumatic heart disease (RHD) with the same accuracy as a cardiologist, according to new research demonstrating how sophisticated deep learning technology can be applied to this disease of inequity.
The work could prevent hundreds of thousands of unnecessary deaths around the world annually.
Developed at Children's National Hospital and detailed in the latest edition of the Journal of the American Heart Association, the new AI system combines the power of novel ultrasound probes with portable electronic devices installed with algorithms capable of diagnosing RHD on echocardiogram.
Distributing these devices could allow healthcare workers without specialised medical degrees to carry technology that could detect RHD in regions where it remains endemic.
RHD is caused by the body's reaction to repeated Strep A bacterial infections and can cause permanent heart damage. If detected early, the condition is treatable with penicillin, a widely available antibiotic. In the United States and other high-income nations, RHD has been almost entirely eradicated. However, in low- and middle-income countries, it impacts the lives of 40 million people, causing nearly 400,000 deaths a year.
"This technology has the potential to extend the reach of a cardiologist to anywhere in the world," said Kelsey Brown, M.D., a cardiology fellow at Children's National and co-lead author on the manuscript with Staff Scientist Pooneh Roshanitabrizi, Ph.D. "In one minute, anyone trained to use our system can screen a child to find out if their heart is demonstrating signs of RHD. This will lead them to more specialised care and a simple antibiotic to prevent this degenerative disease from critically damaging their hearts."
According to the new research, the AI algorithm developed at Children's National identified mitral regurgitation in up to 90% of children with RHD. This tell-tale sign of the disease causes the mitral valve flaps to close improperly, leading to backward blood flow in the heart.
To devise the best approach, two Children's National experts in AI tested a variety of modalities in machine learning, which mimics human intelligence, and deep learning, which goes beyond the human capacity to learn. They combined the power of both approaches to optimise the novel algorithm, which is trained to interpret ultrasound images of the heart to detect RHD.
Already, the AI algorithm has analysed 39 features of hearts with RHD that cardiologists cannot detect or measure with the naked eye.