Trial carried out by University of Oxford researchers. Findings reveal potential to improve treatment in 45% of patients and save thousands of lives at risk.
Researchers associated with the University of Oxford conducted the first global trial of an AI tool that can predict the 10-year risk of deadly heart attacks. The trial revealed that treatment could be improved in about 45% of patients with chest pain, and thousands of lives at risk for heart attacks could be saved.
The trial analysed data from over 40,000 people who underwent routine cardiac computed tomography scans at eight UK hospitals. Participants were followed up for a median of 2.7 years. The researchers discovered that in about 75% of people who undergo these scans, there is no clear sign of significant narrowings in the coronary arteries, so patients are often reassured and discharged. However, a large number of these people go on to have a heart attack because small, undetectable narrowings may break up if they are inflamed, blocking the arteries.
As part of the trial, the researchers used a new AI tool to predict the risk of cardiac events. The tool was trained using information on changes in the fat around inflamed arteries, narrowings of the arteries, and other clinical risk factors. Testing the AI tool on an additional 3,393 patients over 7.7 years revealed that it could independently and accurately predict the risk of cardiac events.
The researchers estimated that implementing the technology in the UK could lead to over 20% fewer heart attacks and 8% fewer cardiac deaths and strokes among those using it. This technology could benefit countries like India as well, where 63% of deaths are attributed to non-communicable diseases, and 27% of those are due to cardiovascular diseases.
Dr Jaideep Menon, an adult cardiologist at Amrita Hospital in Kochi, explained that various scores are tailored to races and populations to help calculate 10-year or lifetime risk. However, these scores often lack significant predictive value. A study on patients admitted for heart attacks revealed that retrospective analysis identified only about half of the victims as high risk.
“An AI-enabled CT coronary angiogram, with the potential to reduce heart attacks by 20 per cent and deaths by 8 per cent, therefore, is a promising development,” Menon said.
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It’s worth noting that a person dies due to a heart attack every 1.5 seconds worldwide. A new AI tool has been developed that could revolutionize cardiovascular treatments. The tool measures the coronary plaque burden on cardiac CT scans and predicts heart attacks, as explained by Dr. C. Sridevi, a consultant cardiologist at DPU Private Super Specialty Hospital in Pune.
“Plaque build-up (fat deposition) in coronary arteries causes the narrowing of arteries and increases the likelihood of a heart attack,” she said.
In a recent study, researchers have developed an AI algorithm that can quickly and accurately measure plaque burden in coronary computed tomography angiography (CTA) images. This is significant because while CTA can estimate the severity of coronary artery narrowing, there hasn’t been a simple and automated way to measure plaque burden in these images until now.
The researchers trained their AI algorithm to measure plaque burden based on previous analyses of coronary CTA images that had been studied by trained doctors. They analyzed CTA images from almost 2,000 people who had undergone a coronary CT angiography at 11 sites worldwide, and found that the measurements made by their AI algorithm accurately predicted heart attack risk within five years for most of the people who were part of their multi-center trial.
This new AI algorithm can quantify plaque burden in CTA images in just five to six seconds, a process that manually takes an expert 25-30 minutes. The researchers then analyzed data from 40,000 people undergoing routine cardiac CT scans at eight UK hospitals and used the new AI tool trained using the information on change in the fat around inflamed arteries, as well as information on the narrowing and plaque burden of arteries and other clinical risk factors.
“In a world-first pilot study, the team provided AI-generated risk scores to clinicians for 744 consecutive patients which resulted in changes in treatment plans by treating physicians. This could result in the prevention of heart attacks in high-risk patients,” Sridevi said.
Dr Komal Pawar, a consultant cardiologist at SRV Hospital in Mumbai, emphasized that early detection of potential heart issues enables targeted interventions, such as lifestyle changes or medication, which in turn reduce the risk of fatal heart attacks.
“As these AI tools continue to evolve, the potential to save lives on a global scale becomes increasingly tangible, marking a transformative era in cardiovascular health and preventive medicine,” she stressed.
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