AI SOFTWARE could cut NHS waiting lists by spotting prostate cancer earlier and more accurately, a charity claims.
The Pi medical platform, designed by Cambridge University scientists, can detect the disease and avoid unnecessary biopsies, according to Macmillan Cancer Support.
PAAI could cut NHS waiting lists by spotting prostate cancer earlier and more accurately[/caption]
The charity is investing £350,100 in the tech, which analyses MRI scans and has been shown to be as accurate as an expert radiologist.
Professor Richard Simcock, of Macmillan, said: “It has the potential to avoid thousands of unnecessary biopsies, alleviating pressure on the NHS workforce and budgets.
“For patients this would mean avoiding anxiety, unpleasant treatments and occasionally dangerous side-effects.”
Prostate cancer is the most common form of the disease in British men, with 52,300 new cases spotted and 12,000 deaths a year.
Symptoms usually do not appear until the prostate has become so large it affects the bladder, leading to needing to pee more regularly or straining when you do so.
There is no screening programme in the UK but patients with symptoms are encouraged to go to their GP.
TRANSFORM DIAGNOSIS
They may perform a digital rectal examination or offer a prostate-specific antigen (PSA) blood test, although these are controversial because they can be unreliable.
If either of these tests pick up signs of the disease, an MRI scan is usually performed before patients are given biopsies to confirm the cancer.
The Pi platform, developed by Lucida Medical, works by analysing scans to determine if a patient is at risk of the disease.
Tanya Humphreys, director of innovation at Macmillan, said Pi “has the potential to transform the diagnosis of prostate cancer”.
Professor Evis Sala, of Lucida Medical, said: “We seek to give every radiologist technology that can precisely identify significant cancers.
“The accuracy of Pi could help reduce the numbers of prostate cancer-free men who undergo painful, potentially avoidable investigations.
“This would save the NHS costs, help address the shortage of radiologists, and cut waiting lists.”
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