By D.W.G. Kalani Tharanga, JadeTimes News
Revolutionizing Heart Disease Detection
Scientists have hailed a new artificial intelligence (AI) technology as "game changing" for its ability to identify individuals at risk of a heart attack within the next decade. Developed by Caristo Diagnostics, a spinout company from Oxford University, this innovative AI model can detect heart inflammation that remains invisible on traditional CT scans. Combining X rays and computer technology, CT scans are typically used to diagnose heart conditions, but the AI model's ability to spot inflammation significantly enhances early detection capabilities.
A pilot project, supported by NHS England, is currently underway at five hospital trusts in Oxford, Milton Keynes, Leicester, Liverpool, and Wolverhampton. The AI platform, named CaRi Heart, analyzes CT scans of patients referred for routine checks due to chest pain. An algorithm identifies coronary inflammation and plaque, and trained operators then verify the results. Research indicates that increased inflammation is strongly linked to a higher risk of cardiovascular disease and fatal heart attacks. Professor Keith Channon from the University of Oxford remarked, "This technology is transformative because it can detect biological processes that precede the development of narrowings and blockages within the heart."
Clinical Impact and Future Prospects
The potential impact of this AI technology on public health is profound. According to the British Heart Foundation (BHF), approximately 7.6 million people in the UK live with heart disease, costing the NHS in England around £7.4 billion annually. About 350,000 patients undergo cardiac CT scans each year in the UK. The Orfan study (Oxford Risk Factors and Non invasive imaging), involving 40,000 patients and published in The Lancet, found that 80% of individuals were sent back to primary care without a defined prevention or treatment plan. However, using the AI technology, researchers discovered that patients with inflammation in their coronary arteries faced a 20 to 30 times higher risk of dying from a cardiac event over the next decade.
A significant finding of the study was that 45% of these high risk patients were prescribed medication or advised to make lifestyle changes to mitigate the risk of future heart attacks. One such patient, Ian Pickard, a 58 year old from Barwell in Leicestershire, experienced persistent chest pain and was referred for a CT scan. Enrolled in the Orfan study, Mr. Pickard was prescribed statins, told to quit smoking, and encouraged to increase his exercise after the AI analysis indicated his risk of a heart attack. Reflecting on his diagnosis, Mr. Pickard said, "It's a huge wake up call. Seeing it on paper makes you realize how serious it is."
The AI model’s capability to measure cardiac inflammation based on fat around the arteries marks a significant advancement in heart disease prevention. Professor Charalambos Antoniades, the Orfan study lead, explained that traditional risk calculators could only assess general risk factors like diabetes, smoking, or obesity. In contrast, the new AI technology allows for early intervention by identifying disease activity in arteries before the disease has fully developed. This proactive approach aims to halt the disease process and prevent heart attacks.
The National Institute for Health and Care Excellence is currently evaluating whether to roll out this AI technology across the NHS. It is also under review in the US and has already been approved for use in Europe and Australia, indicating its potential for global adoption in the fight against heart disease.
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