Artificial Intelligence Can Help Identify Patients at High Risk of Heart Attack
Caused by high cholesterol, diabetes, smoking, high blood pressure, and obesity, among others, plaque buildup can result in the narrowing of the arteries, which will make it difficult for blood to reach the heart, increasing the probability of a heart attack.
A medical test known as CTA – coronary computed tomography angiography – takes 3D images of the heart and arteries and can provide medical professionals with a rough estimate of how much the arteries have narrowed. So far, however, there has not been a simple, rapid way to measure the plaque visible in the CTA images, which is why the artificial intelligence tool might be revolutionary.
People who are at high risk of experiencing a fatal heart attack may now benefit from artificial intelligence, which can accomplish the following amazing things:
The Novel Artificial Intelligence Tool Could Save Lives
The researchers at Cedars-Sinai examined CTA images from 1,196 people who underwent a CTA at 11 sites in the United States, as well as in:
They instructed the artificial intelligence algorithm to measure plaque by having it learn from the CTA images of 921 people, which had already been analyzed by reputable doctors. Because there is not a fully automated way to do it, coronary plaque is usually not measured, which could be detrimental to the health of the patient, as their risk of heart disease will remain unknown. When coronary plaque can be measured, the procedure takes 25 to 30 minutes, but with the artificial intelligence program, doctors will be able to evaluate coronary plaque within 5 to 6 seconds.
The algorithm works by outlining the coronary arteries in 3D images and subsequently pinpointing the blood and plaque deposits along the coronary arteries. Researchers found that the measurements of the tool correspond with the plaque amounts seen in the CTAs. They also matched the results with the images taken by two invasive tests that are highly accurate in evaluating coronary artery plaque and narrowing:
“More studies are needed, but it’s possible we may be able to predict if and how soon a person is likely to have a heart attack based on the amount and composition of the plaque imaged with this standard test,” says Damini Dey, Ph.D., director of the quantitative image analysis lab in the Biomedical Imaging Research Institute at Cedars-Sinai and senior author of the study.
Lastly, the researchers at Cedars-Sinai found that the measurements of the artificial intelligence algorithm from CTA images accurately predicted the heart attack risk within five years for 1,611 people who partook in a multicenter trial known as SCOT-HEART. The study was funded by the National Heart, Lung, and Blood Institute. Dey, who is also a professor of Biomedical Sciences at Cedars-Sinai, and her colleagues will continue to study how well their artificial intelligence algorithm quantifies plaque deposits in people who undergo CTA.