Artificial Intelligence in Mammography Screening (AIMS)

  • Research type

    Research Study

  • Full title

    Clinical validation of an artificial intelligence system to improve the quality, efficiency and experience of breast cancer screening

  • IRAS ID

    303782

  • Contact name

    Ara Darzi

  • Contact email

    a.darzi@imperial.ac.uk

  • Sponsor organisation

    Imperial College London

  • Duration of Study in the UK

    1 years, 11 months, 31 days

  • Research summary

    This project aims to evaluate the potential for artificial intelligence (AI)-enabled NHS breast screening to increase accuracy, safety, cost-effectiveness, and clinician/patient experience, while demonstrating clinical feasibility.

    In the UK breast screening programme, two expert readers (radiologists) assess each mammogram (x-ray of the breast), with any disagreements in opinion reviewed by an arbitration panel of two further readers. However, a radiologist workforce crisis threatens the screening programme’s long-term sustainability. Google’s AI system identified cancer in mammograms with greater accuracy than specialists (Nature, 2020), suggesting potential to: reduce radiologist workload; increase service capacity; improve accuracy and outcomes, and reduce variability; and reduce time to results, improving patient experience. This project brings this initial research towards real world impact.

    Firstly in Part A, we will compare the Google AI system to radiologists in large historical populations at two NHS sites with diverse multicultural patient populations. This will allow detailed assessments of accuracy of the AI; ensure fair, equitable performance; and support modelling of workforce and economic impacts.

    Secondly in Part B, we will perform a large diagnostic study to re-read historical mammograms from approximately 10,000 women across two hospitals to explore how expert readers in arbitration panels interact with the AI when used as the second reader. This will explore complex human factors involved, measure overall accuracy of AI-enabled screening, and enable comprehensive assessments of NHS health economic impacts. Readers will only access anonymised data.

    Throughout the study, we will run PPIE workshops with diverse groups of up to 14 members of the public, with previous experience of breast cancer and/or screening mammography, co-facilitated by a lay partner. We will discuss patients’ ideas, concerns and expectations for the project, which will feed into project design. We have successfully run 4 patient and public workshops in 2021.

  • REC name

    East Midlands - Nottingham 1 Research Ethics Committee

  • REC reference

    22/EM/0038

  • Date of REC Opinion

    14 Feb 2022

  • REC opinion

    Favourable Opinion