A large study using NHS breast screening data suggests that artificial intelligence could detect a quarter of breast cancers that human specialists initially miss on mammograms, 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
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
The findings, published in Nature Cancer, 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