Cedars-Sinai develops AI tool to better predict heart attacks
This is especially important in a value-based care framework, since provider reimbursement is linked to clinical quality.
Photo: kaosod/Getty Images
Los Angeles-based Cedars Sinai investigators have developed an artificial intelligence technology that's expected to make it easier to predict whether a person will have a heart attack, the system said this week.
The tool, described in The Lancet Digital Health, accurately predicted which patients would experience a heart attack in five years based on the amount and composition of plaque in arteries that supply blood to the heart.
Coronary plaque buildup can cause arteries to narrow, which makes it difficult for blood to get to the heart, increasing the likelihood of a heart attack. A medical test called a coronary computed tomography angiography (CTA) takes 3D images of the heart and arteries, and can give doctors an estimate of how much a patient's arteries have narrowed.
Until now, though, there hasn't been a simple, automated and rapid way to measure the plaque visible in the CTA images. Because of that, coronary plaque often is not measured at all. When it is measured, it can be time-consuming – 25 to 30 minutes in most cases.
The AI tool, by comparison, can analyze CTA images and quantity plaque buildup in about five or six seconds.
WHAT'S THE IMPACT?
If the tool proves successful, the technology may spread to other health systems – facilitating a much faster and more accurate prediction model for coronary plaque buildup, and increasing the likelihood of improved clinical outcomes.
That's especially important in a value-based care framework, as provider reimbursement is increasingly linked to clinical quality.
Early results from the analysis of the AI tool have been encouraging.
The Lancet article's researchers analyzed CTA images from 1,196 people who underwent a coronary CTA at 11 sites in Australia, Germany, Japan, Scotland and the U.S. The investigators trained the AI algorithm to measure plaque by having it learn from coronary CTA images from 921 people that had already been analyzed by trained doctors.
The algorithm works by first outlining the coronary arteries in 3D images, then identifying the blood and plaque deposits within those arteries. Investigators found the tool's measurements corresponded with plaque amounts seen in coronary CTAs. They also matched results with images taken by two invasive tests considered to be highly accurate in assessing coronary artery plaque and narrowing: intravascular ultrasound and catheter-based coronary angiography.
Finally, the investigators discovered that measurements made by the AI algorithm from CTA images accurately predicted heart attack risk within five years for 1,611 people who were part of a multicenter trial called the SCOT-HEART trial.
More research is needed before the tool expands into widespread use, investigators said.
THE LARGER TREND
Heart health was a main area of focus during a push by biotechnology company AstraZeneca in 2021 to create patient-centric digital health solutions, in a collaboration with Massachusetts General Hospital.
The company's AMAZE disease-management platform utilizes remote monitoring technology to study heart failure in an effort to improve care and lower healthcare costs.
A 2019 study in the American Journal of Cardiology found that heart attack patients treated at hospitals with low care scores are at greater risk for another heart attack and/or death due to cardiovascular causes.
Twitter: @JELagasse
Email the writer: jeff.lagasse@himssmedia.com
