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<\/p>\nAn NHS patient has described feeling \u201cincredibly lucky\u201d after her breast cancer was detected by artificial intelligence, when the tumour had initially been missed by human experts.<\/p>\n
Yvonne Cook\u2019s cancer was so small it was not identified by clinicians. But she was called back for further testing after an experimental AI system flagged a potential abnormality. A follow-up mammogram in May 2023 confirmed that she had lobular breast cancer, the second most common form of the disease.<\/p>\n
Her overwhelming reaction was, she said, gratitude that the cancer had been caught early. \u201cYou would expect a negative and emotional reaction \u2014 \u2018Oh my goodness, I have cancer\u2019 \u2014 but overwhelmingly I just felt incredibly lucky that I was part of the research programme and that it had been picked up at this early stage,\u201d she said.<\/p>\n
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Yvonne Cook underwent surgery in December 2023<\/p>\n
YVONNE COOK\/PA<\/p>\n
Her cancer was identified during a trial that found detection rates increased by 10 per cent when AI was used alongside human specialists to review mammograms. The study, led by the University of Aberdeen, assessed the performance of an AI screening tool called Mia, which was used to support routine breast screening for 10,889 women in the Grampian NHS region.<\/p>\n
After her diagnosis, Cook underwent surgery in December 2023. She later required a second operation in January 2024 to remove additional breast tissue and ensure clear margins. Her treatment concluded with a week of low-dose radiotherapy in May 2024.<\/p>\n
The Aberdeen trial was one of several published in the latest edition of Nature Cancer. The journal also includes a separate large study that suggested AI could detect a quarter of breast cancers that human specialists initially miss on mammograms \u2014 a breakthrough researchers say could mark a turning point in the battle against the disease.<\/p>\n
Scientists say the technology could also make breast screening doctors roughly twice as effective by dramatically reducing the number of scans they need to review, potentially helping address chronic staff shortages in the NHS.<\/p>\n
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A mammogram is displayed on a digital screen alongside the machine that took the image<\/p>\n
GETTY MAGES<\/p>\n
Breast cancer is the most common cancer in women, affecting about one in eight during their lifetime. Early detection is crucial: tumours found through screening are typically easier to treat, and survival rates are far higher when the disease is caught before it spreads.<\/p>\n
\u2022 Why cancer rates are soaring \u2014 for women under 50<\/a><\/p>\n The AI findings come from a large study analysing mammograms from about 150,000 women in the NHS breast-screening programme. In the UK system, every scan is normally reviewed independently by two trained specialists, with disputed cases referred to senior clinicians for arbitration.<\/p>\n Researchers examined what would happen if one of the two human readers were replaced by an AI system trained to analyse mammograms for subtle signs of cancer.<\/p>\n One of the most striking findings was the system\u2019s ability to identify \u201cinterval cancers\u201d \u2014 tumours that are not detected during screening but are diagnosed later, before the next routine mammogram after three years. In retrospective analysis, the AI flagged about a quarter of these cancers on earlier scans, where they had initially been missed.<\/p>\n In the analysis, the AI system detected 9.3 cancers per 1,000 women screened, compared with 7.5 detected by a single human reader, about a 24 per cent improvement.<\/p>\n \u2022 One in four breast cancer deaths linked to lifestyle factors such as diet<\/a><\/p>\n \u201cThese cancers are very subtle,\u201d said Susan Thomas, a researcher at Google Health, who worked on the study. \u201cIf we can increase the chances of detecting them earlier, that has the potential to make a real difference for patients.\u201d<\/p>\n The technology also performed particularly well among women attending screening for the first time, detecting cancers more sensitively while recalling fewer women for further testing \u2014 an outcome that could reduce unnecessary anxiety for patients.<\/p>\n Thomas said the study highlighted how AI could strengthen screening programmes while supporting overstretched clinicians. \u201cDetecting cancers on mammograms is a very nuanced task,\u201d she said. \u201cThe reason we have two readers and arbitration is that the signs can be extremely subtle.\u201d<\/p>\n Using AI as a second reader could significantly reduce the workload involved in screening programmes. Because each scan requires two specialists to review it, replacing one reader with AI could cut the number of scans doctors must examine by about 40 per cent.<\/p>\n That would not necessarily mean doctors working fewer hours, Thomas said, but could allow scans to be read more quickly and patients to receive results sooner. \u201cRadiologists are not suddenly going to be sitting around with nothing to do,\u201d she said. \u201cBut it could help scans be read faster and cancers identified more quickly.\u201d<\/p>\n