AI Detects Hidden Heart Attack Risks – Better Than Human!
Image Credit: Jair Lázaro | Unsplash
A groundbreaking AI model developed by Caristo Diagnostics is being hailed as transformative in the field of cardiology. This technology can identify people at risk of heart attacks within the next decade, detecting inflammation in the heart that traditional CT scans miss. Supported by NHS England, this pilot project is running at five hospital trusts across the UK. A decision on its wider use within the NHS is expected soon, with potential applications in stroke and diabetes prevention. The technology's ability to see the unseen makes it a true game changer in healthcare.
How the AI Model Works
The AI model, called CaRi-Heart, analyzes routine CT scans of patients suffering from chest pain to detect coronary inflammation and plaque. These scans, combined with sophisticated algorithms, reveal biological processes invisible to the human eye. The findings are then assessed by trained operators to ensure accuracy. Research has shown that increased inflammation is linked to a higher risk of cardiovascular disease and fatal heart attacks. This innovative approach allows for earlier and more precise detection of heart disease risks.
Impact on the UK Healthcare System
The British Heart Foundation (BHF) estimates that around 7.6 million people in the UK live with heart disease, costing the NHS in England approximately £7.4 billion annually. With about 350,000 cardiac CT scans performed each year in the UK, the AI technology has significant potential to reduce these costs. By identifying patients at higher risk, the technology can prompt earlier interventions and personalized treatment plans. This could drastically reduce the incidence of heart attacks and related fatalities. The potential healthcare savings and improved patient outcomes are substantial.
The Orfan Study: Key Findings
The Orfan study, involving 40,000 patients and published in The Lancet, highlighted the critical importance of detecting coronary inflammation. The study found that 80% of patients were sent back to primary care without a defined prevention or treatment plan. Among those with detected inflammation, there was a 20 to 30 times higher risk of dying from a cardiac event over the next 10 years. Utilizing the AI technology, 45% of these high-risk patients were prescribed medication or encouraged to make lifestyle changes. This proactive approach could significantly reduce heart attack rates.
Real-Life Impact: Ian Pickard’s Story
Ian Pickard, a 58-year-old from Leicestershire, experienced persistent chest pain and was referred for a CT scan in November 2023. Enrolled in the Orfan study, the AI analysis revealed he was at risk of a heart attack. Consequently, he was prescribed statins, advised to quit smoking, and told to increase his exercise. Pickard describes this as a "huge wake-up call" that motivated him to make necessary lifestyle changes. His story exemplifies the life-saving potential of this AI technology.
Expert Opinions on AI Technology
Leading experts, including Prof Keith Channon and Prof Charalambos Antoniades from the University of Oxford, have praised the technology. They emphasize that traditional risk calculators only assess general factors like diabetes, smoking, and obesity. In contrast, the AI model identifies disease activity in arteries before the disease has fully developed. This early detection allows for timely interventions, potentially stopping the disease in its tracks. Such advancements represent a significant leap forward in preventive cardiology.
Future Prospects and Wider Adoption
The National Institute for Health and Care Excellence (NICE) is currently assessing whether this AI technology should be implemented across the NHS. It is also under review in the US and has already been approved for use in Europe and Australia. If adopted widely, this technology could revolutionize the way cardiovascular diseases are managed globally. The ability to detect and treat heart disease before it manifests could save countless lives and reduce healthcare costs dramatically. The future of cardiology may very well hinge on the successful integration of AI.
