In a major advancement for cardiovascular health, a new artificial intelligence (AI) technology is being hailed as a revolutionary tool for detecting hidden heart attack risks. Developed by Caristo Diagnostics, an Oxford University spinout, this cutting-edge AI model analyzes coronary inflammation that is not visible through traditional CT scans. The technology, known as CaRi-Heart, has been described as “transformative” by experts and is currently being piloted at five hospital trusts across the UK.
The CaRi-Heart AI platform works by scrutinizing CT scan images for signs of inflammation and plaque build-up in the coronary arteries, which are precursors to serious heart conditions such as heart attacks and strokes. Unlike conventional methods that only provide a general risk assessment, this AI model can detect underlying biological processes that precede the development of artery blockages, offering a more precise evaluation of cardiovascular health.
Professor Keith Channon from the University of Oxford, who is leading the research, emphasized the groundbreaking nature of this technology. “For the first time, we can visualize biological processes that were previously invisible,” he said. “This allows us to identify patients at high risk of heart disease much earlier and intervene before the condition progresses.”
The pilot project, supported by NHS England, is currently being conducted in Oxford, Milton Keynes, Leicester, Liverpool, and Wolverhampton. Initial findings from the Orfan study, which involved 40,000 patients and was published in The Lancet, revealed that patients showing signs of inflammation had a 20 to 30 times higher risk of a cardiac event within the next decade. The study found that using CaRi-Heart, 45% of patients identified with coronary inflammation were prescribed preventive medications or advised to make significant lifestyle changes.
Ian Pickford, a 58-year-old participant from Barwell, Leicestershire, experienced a significant health wake-up call after his CT scan revealed an elevated risk of heart attack. “It’s a huge wake-up call,” Pickford said. “Seeing it on paper makes the seriousness of the situation hit home. It’s a daily reminder to take action.”
The British Heart Foundation (BHF) estimates that around 7.6 million people in the UK live with heart disease, costing the NHS approximately £7.4 billion annually. The introduction of this AI technology could potentially reduce these costs and improve patient outcomes by facilitating early intervention.
Prof Charalambos Antoniades, lead researcher of the Orfan study, highlighted the limitations of traditional risk calculators. “Previous tools were rudimentary, focusing only on general risk factors,” Antoniades explained. “With this AI technology, we can pinpoint exactly which patients have active disease processes in their arteries, allowing us to treat and prevent heart attacks more effectively.”
The National Institute for Health and Care Excellence (NICE) is currently evaluating the technology for potential NHS rollout. Meanwhile, it is already approved for use in Europe and Australia and is under review in the US.
As the healthcare community awaits further decisions on widespread adoption, this AI technology represents a significant leap forward in the fight against cardiovascular disease, offering hope for earlier detection and more effective prevention strategies.
