A patient's risk of a heart attack or stroke in the the next 10 years can be predicted from just one chest X-ray by a new computer system.
It combines AI (artificial intelligence) with a single chest X-ray to find patterns associated with hardening of the arteries.
The technique offers hope of vulnerable individuals being prescribed cholesterol-reducing drugs much sooner.
Lead author Dr. Jakob Weiss, of Massachusetts General Hospital, said: "Our deep learning model offers a potential solution for population-based opportunistic screening of cardiovascular disease risk using existing chest X-ray images.
"This type of screening could be used to identify individuals who would benefit from statin medication but are currently untreated."
Eating plenty of fish, fruit and vegetables and going for brisk walks or bike rides are also protective.
Deep learning is a complex series of algorithms that enable machines to make forecasts based on patterns in data.
The method presented at a Radiological Society of North America meeting in Chicago could revolutionize heart therapy.
Current guidelines recommend estimating ten year risk to establish who should get a statin for primary prevention.
This is based on the ASCVD (atherosclerotic cardiovascular disease) risk score which takes into account a host of factors.
They include age, sex, race, high blood pressure, smoking history, type 2 diabetes and blood tests. Those scoring 7.5 percent or more should be given statins.
Weiss said: "The variables necessary to calculate ASCVD risk are often not available, which makes approaches for population-based screening desirable.
"As chest X-rays are commonly available, our approach may help identify individuals at high risk."
The US team trained the model, known as CXR-CVD risk, to predict death from cardiovascular disease using 147,497 chest X-rays from 40,643 participants in a cancer screening trial.
Weiss said: "We have long recognized X-rays capture information beyond traditional diagnostic findings.
"But we haven't used this data because we haven't had robust, reliable methods. Advances in AI are making it possible now."
In tests it accurately predicted heart attacks and strokes in a group who had routine chest X-rays at Mass General Brigham, Boston.
About 10 percent of the 11,430 outpatients suffered a major cardiac event over the average follow-up of just over a decade.
The system also identified those who were eligible for potentially life-saving statin therapy.
Weiss said: "The beauty of this approach is you only need an X-ray, which is acquired millions of times a day across the world.
"Based on a single existing chest X-ray image, our deep learning model predicts future major adverse cardiovascular events with similar performance and incremental value to the established clinical standard."
If a controlled, randomized trial validates the results it could support doctors in making the right decisions for treatment.
Weiss said: "What we've shown is a chest X-ray is more than a chest X-ray. With an approach like this, we get a quantitative measure, which allows us to provide both diagnostic and prognostic information that helps the clinician and the patient."
Cardiovascular disease is the world's number one killer - claiming almost 18 million lives a year.
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