Introduction: AI test that detects heart disease in just 20 seconds.
An AI test that detects heart disease in just 20 seconds, with a much higher degree of accuracy than existing methods, will be rolled out on the NHS, UK after a successful pilot.
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The tool analyzes heart MRI scans as they are made, rather than having to wait 13 minutes for a doctor to check them manually.
Radiologists using the AI tool will continue to double-check the results and write up the report themselves – but the diagnosis will be completed much faster because the underlying analysis has already been completed.
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Radiologists will be able to get to the results sooner, reducing the typical two- to four-week wait time by about a third, according to project leader Dr Rhodri Davies, of University College London and St Bartholomew’s Hospital.
We may see the waiting time speeding up even more in the next five to ten years, since human input may be dropped altogether in favor of AI-only analysis.
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“Our new AI reads complex heart scans in record speed, analyzing the structure and function of a patient’s heart with more precision than ever before. The beauty of the technology is that it replaces the need for a doctor to spend countless hours analyzing the scans by hand,” Dr Davies said.
Around 120,000 heart MRI scans are performed in the UK each year. The AI will help healthcare staff free up valuable time – saving around 3,000 “clinician days” every year – so that they can see more patients on NHS waiting lists, helping to reduce the backlog in vital heart care.
Heart failure, hypertrophic cardiomyopathy (HCM) – where the heart muscle thickens – and dilated cardiomyopathy (DCM) – where the heart muscle walls become stretched and thin – are all conditions that are diagnosed using the tool. The heart has a difficult time pumping properly because of all of these factors.
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Additionally, it is more accurate than human radiologists at reading scans, which means that the number of misclassifications under the new system could be about half that of the present system – so more patients could receive proper treatment, Dr. Davies said.
For example – Nearly one in seven patients with hypertrophic cardiomyopathy (HCM) – a condition for which many use a defibrillator – are misclassified.
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Some 6.8 per cent of them are likely to have benefitted from a defibrillator but were not recommended one under the existing system, while 8.7 per cent had one fitted that probably did not need it, Dr Davies said.
He added that the new system could reduce these errors by half.
University College London Hospital, St Bartholomew’s Hospital, and Royal Free Hospital are using the AI tool.
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It will be rolled out to another 40 hospitals and clinics in the UK, the US and Europe from the summer – and in the next few years Dr Davies hopes it will be introduced much more widely across the NHS.
Dr Rhodri Davies, who led the work, said: “Our new AI reads complex heart scans in record speed, analysing the structure and function of a patient’s heart with more precision than ever before.
“The beauty of the technology is that it replaces the need for a doctor to spend countless hours analysing the scans by hand.
“We are continually pushing the technology to ensure it’s the best it can be, so that it can work for any patient with any heart disease.
“After this initial rollout on the NHS, we’ll collect the data, and further train and refine the AI so it can be accessible to more heart patients in the UK and across the world.”
Dr Sonya Babu-Narayan, associate medical director at the British Heart Foundation, which funded the research, said: “This is a huge advance for doctors and patients, which is revolutionizing the way we can analyze a person’s heart MRI images to determine if they have heart disease at greater speed.”
“The pandemic has resulted in a backlog of hundreds of thousands of people waiting for vital heart scans, treatment and care. It’s heartening to see innovations like this, which together could help fast-track heart diagnoses and ease workload so that in future we can give more NHS heart patients the best possible care much sooner.”