New AI tool can detect hidden heart attack risks 'Game changer'

A pilot project by NHS England is underway at five hospital trusts

 A group from Caristo Diagnostics, an Oxford College spinout organization, has developed AI technology that can identify people at risk of a heart attack within the next ten years.

Described as "game-changing" by scientists, this model detects heart inflammation that is not visible on CT scans, which use a combination of X-rays and computer technology.

Supported by NHS England, a pilot project is underway at five hospitals in Oxford, Milton Keynes, Leicester, Liverpool, and Wolverhampton. A decision on its implementation within the NHS is expected soon.

The technology is also being adapted to prevent diabetes and strokes. Professor Keith Channon from the University of Oxford said: "This technology is groundbreaking and game-changing because, for the first time, we can identify the biological processes that are invisible to the naked eye, which precede the development of narrowings and blockages within the heart."

In the pilot, patients with chest pain referred for a routine CT scan have their scans analyzed by Caristo Diagnostics' CaRi-Heart AI platform. An algorithm that identifies coronary inflammation and plaque is then verified by trained operators.

Research has linked increased inflammation to a higher risk of cardiovascular disease and fatal heart attacks.

According to the British Heart Foundation (BHF), around 7.6 million people in the UK live with heart disease, costing the NHS in England £7.4 billion annually. Around 350,000 heart CT scans are performed every year in the UK.

The Orfan study (Oxford Risk Factors and Non-invasive Imaging), involving 40,000 patients and published in the Lancet, revealed that 80% of people were sent back to primary care without a defined prevention or treatment plan.

Researchers found that patients with inflammation in their coronary arteries had a 20 to 30 times higher risk of dying from a cardiovascular event over the next ten years. Using this AI technology, 45% of these patients were prescribed medication or encouraged to make lifestyle changes to prevent future heart attacks. 

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