Breast cancer affects one in every eight women in the UK. In this fight, early detection is crucial to giving people the best chance of overcoming the disease. New research from Google, Imperial College London and the UK’s National Health Service (NHS), published as a pair of studies in Nature Cancer today, marks a turning point in screening technology and reveals how AI can strengthen early detection efforts.
Our experimental research AI system identified 25% of the “interval cancers” that were previously missed — the cases that typically slip through traditional screenings and only surface after symptoms appear, when they become more challenging to treat. But this research goes beyond the accuracy of the scans. It offers a first-of-its kind, large-scale look at how radiologists react when AI challenges or confirms their diagnosis in a clinical setting.
Confronting a growing challenge
In the UK’s NHS, the frontline of breast cancer screening relies on a rigorous “double-reading” process: Two specialists must agree on every mammogram, with an arbitration panel deciding any disputes. It is a vital safety net, but one that’s stretched to its limit. Each specialist must review roughly 5,000 scans annually, with just four hours of dedicated time per week, all amidst a global shortage of radiologists. We set out to determine how AI could help to tackle this challenge.
Validating accuracy at scale
The first step was comparing the accuracy of AI-based mammography interpretation to that of expert radiologists. We tested this by using AI to review the mammograms of 125,000 women, and the results were definitive: The AI-based screening detected 25% of the total interval cancers (cancers detected between scans) previously missed. AI also identified more invasive cancers and more cancers overall than the expert radiologists, and identified fewer false positives for women having their first-time scan.
