AI Algorithm Identifies Coronary Artery Calcium Buildup on Echocardiograms

A coronary artery calcium study, published in the Journal of the American Society of Echocardiography, shows for the first time that an ultrasound image of the heart can be “read” by an artificial intelligence algorithm to accurately identify whether a patient has a large amount of buildup in their coronary arteries.

Traditionally, coronary artery calcium buildup is diagnosed using CT scans, which are not available at every center, expose patients to radiation, and are costly. On the other hand, heart ultrasounds—also called echocardiograms—can be done in a clinic or doctor’s office, do not produce radiation, and tend to be much less expensive.

“We show that echocardiograms, when interpreted with our AI software, can predict coronary artery calcium and predict heart attack risk nearly as well as CT scans,” said senior author David Ouyang, MD, a cardiologist in the Department of Cardiology in the Smidt Heart Institute at Cedars-Sinai and a researcher in the Division of Artificial Intelligence in Medicine. “This proved true even in cases where the naked eye of an expert reader sees the ultrasound image of the heart as appearing fairly normal.”

Using a dataset of 2,881 echocardiogram images, investigators trained a video-based artificial intelligence tool to predict coronary artery calcium scores. Scores range from zero—representing a “perfect” score with no indication of coronary artery calcium buildup—to more than 2,000, a poor prognosis for individuals, representing high risk of heart attack and coronary artery disease.

The video-based deep learning model successfully predicted scores of zero in patients with good health as well as high coronary calcium scores, likely foreshadowing a worse future prognosis.

Dr Ouyang and team hope this efficient technology—inclusive of a coronary artery calcium score for each patient—may be used in all echocardiogram laboratories. This type of resource, Dr Ouyang says, “will allow for faster, potentially more frequent, and generally more cost-effective imaging that provides clinically valuable, predictive information.”