This archive report was first published on 24 September 2019.
Published on September 4, 2019, a team of researchers at the University of Oxford has made a groundbreaking discovery in the field of cardiology. Using artificial intelligence (AI), they have developed a technology that can predict heart attacks with unprecedented accuracy.
The innovation, known as the Fat Radiomic Profile (FRP), detects biological red flags in the perivascular space lining blood vessels that supply blood to the heart. It identifies inflammation, scarring, and changes to these blood vessels, all of which are indicators of a future heart attack.
Currently, there are no methods used routinely by doctors that can spot all of the underlying red flags for a future heart attack. However, the FRP has shown remarkable promise in identifying individuals at high risk of a fatal heart attack at least 5 years before it strikes.
Professor Charalambos Antoniades and his team used fat biopsies from 167 people undergoing cardiac surgery to develop the FRP. They analyzed the expression of genes associated with inflammation, scarring, and new blood vessel formation, and matched these to the CCTA scan images to determine which features best indicate changes to the fat surrounding the heart vessels.
The researchers then compared the CCTA scans of 101 people who went on to have a heart attack or cardiovascular death within 5 years of having a CCTA with matched controls who did not. Using machine learning, they developed the FRP fingerprint that captures the level of risk.
“Just because someone’s scan of their coronary artery shows there’s no narrowing, that does not mean they are safe from a heart attack,” said Prof Antoniades. “By harnessing the power of AI, we’ve developed a fingerprint to find ‘bad’ characteristics around people’s arteries. This has huge potential to detect the early signs of disease and to be able to take all preventative steps before a heart attack strikes, ultimately saving lives.”
