Artificial intelligence has been a topic of intense research in radiology for years, but in 2023 and 2024 it moved from clinical trials into real-world NHS use. AI tools are now deployed at several NHS breast screening centres, reading mammograms alongside human radiologists. The question is no longer whether AI can analyse a mammogram — it clearly can — but whether it makes the screening programme better for patients.
What the SYMPLIFY and PROSE trials showed
The SYMPLIFY trial, published in The Lancet Oncology, tested AI as a triage tool for mammograms, prioritising the cases that most needed urgent human review. The PROSE trial went further, evaluating AI as a second reader — replacing the second radiologist who currently reads every NHS mammogram. Results showed that AI-assisted reading was non-inferior to double human reading in cancer detection rate, while significantly reducing radiologist workload. Crucially, the false-positive rate (unnecessary recall) did not increase.
What this means for the NHS screening programme
The NHS breast screening programme currently invites women aged 50–71 every three years. Every mammogram is read by two radiologists independently — a process designed to catch cancers one reader might miss. AI is being evaluated as a replacement for the second reader, which would release significant radiologist capacity. With radiologist shortages a known challenge for NHS radiology, this has real implications for waiting times and programme coverage.
What AI cannot yet do
- AI tools are currently validated for mammography only — not for MRI or ultrasound breast screening
- AI performance varies by breast density and by cancer subtype — it remains better at detecting some cancers than others
- Clinical decision-making (biopsy, referral, treatment) remains firmly with human clinicians
- AI tools require ongoing validation as the screening population and imaging technology evolves
- Regulatory approval and NHS-wide rollout are still in progress — AI is not yet standard across all NHS trusts
The global picture: AI in low-resource settings
For high-income countries, AI offers efficiency gains in an already-functioning system. The more transformative potential may be in low-income communities, where radiologist shortages mean mammograms are simply not read at all. Researchers are exploring whether AI could enable community screening programmes — operating with portable digital mammography units and cloud-based AI reading — in settings where a specialist radiologist is not available. This remains early-stage, but the direction is significant.