Technology developed using artificial intelligence (AI) by researchers at the University of Oxford could identify people at high risk of a fatal heart attack at least 5 years before it strikes.
The new biomarker called Fat Radiomic Profile (FRP) detects biological red flags in the perivascular space lining blood vessels that supply blood to the heart. It further identifies inflammation, scarring and changes to these blood vessels, which are all pointers to a future heart attack.
The innovation is being presented at the European Society of Cardiology (ESC) Congress in Paris and published in the European Heart Journal.
Currently, there are no methods used routinely by doctors that can spot all of the underlying red flags for a future heart attack.
In this recent research Professor Charalambos Antoniades and his team firstly used fat biopsies from 167 people undergoing cardiac surgery.
“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.
A biopsy is the removal of tissue from any part of the body to examine it for diseases.
The Research
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, called perivascular fat.
The researchers then compared the CCTA scans of the 101 people, from a pool of 5487 individuals, who went on to have a heart attack or cardiovascular death within 5 years of having a CCTA with matched controls who did not, to understand the changes in the perivascular space which indicate that someone is at higher risk of a heart attack.
Using machine learning, they developed the FRP fingerprint that captures the level of risk. The more heart scans that are added, the more accurate the predictions will become, and the more information that will become ‘core knowledge’.
They tested the performance of this perivascular fingerprint in 1,575 people. The findings showed that the FRP had a striking value in predicting heart attacks, above what can be achieved with any of the tools currently used in clinical practice.
“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. We genuinely believe this technology could be saving lives within the next year,” he added.
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