Generating evidence to support the role of AI in diabetic eye screening: considerations from the UK National Screening Committee.

Journal: The Lancet. Digital health
Published Date: Apr 3, 2025

Abstract

Screening for diabetic retinopathy has been shown to reduce the risk of sight loss in people with diabetes, because of early detection and treatment of sight-threatening disease. There is long-standing interest in the possibility of automating parts of this process through artificial intelligence, commonly known as automated retinal imaging analysis software (ARIAS). A number of such products are now on the market. In the UK, Scotland has used a rules-based autograder since 2011, but the diabetic eye screening programmes in the rest of the UK rely solely on human graders. With more sophisticated machine learning-based ARIAS now available and greater challenges in terms of human grader capacity, in 2019 the UK's National Screening Committee (NSC) was asked to consider the modification of diabetic eye screening in England with ARIAS. Following up on a review of ARIAS research highlighting the strengths and limitations of existing evidence, the NSC here sets out their considerations for evaluating evidence to support the introduction of ARIAS into the diabetic eye screening programme.

Authors

  • Trystan MacDonald
    Institute of Inflammation and Ageing, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK.
  • Zhivko Zhelev
    Exeter Test Group, College of Medicine and Health, University of Exeter Medical School, Exeter, UK.
  • Xiaoxuan Liu
    Birmingham Health Partners Centre for Regulatory Science and Innovation University of Birmingham Birmingham Reino Unido Birmingham Health Partners Centre for Regulatory Science and Innovation, University of Birmingham, Birmingham, Reino Unido.
  • Christopher Hyde
    Exeter Test Group, College of Medicine and Health, University of Exeter Medical School, Exeter, UK.
  • Jiri Fajtl
    School of Computer Science and Mathematics, Kingston University, London, UK.
  • Catherine Egan
    NIHR Biomedical Research Centre at Moorfields Eye Hospital and UCL Institute of Ophthalmology, London, UK.
  • Adnan Tufail
    London, United Kingdom. Electronic address: Adnan.Tufail@moorfields.nhs.uk.
  • Alicja R Rudnicka
    Population Health Research Institute, St George's School of Health and Medical Sciences, City St George's, University of London, London, UK.
  • Bethany Shinkins
    University of Leeds, Leeds, UK.
  • Rosalind Given-Wilson
    St George's University Hospitals NHS Foundation Trust, London, UK.
  • J Kevin Dunbar
    Regional Head of Screening Quality Assurance Service (SQAS) - South, NHS England, England, UK.
  • Steve Halligan
    Centre for Medical Imaging, Division of Medicine, University College London, London, UK.
  • Peter Scanlon
    Gloucestershire Hospitals NHS Foundation Trust, Cheltenham, UK.
  • Anne Mackie
    UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.
  • Sian Taylor-Philips
    Warwick Medical School, University of Warwick, Coventry, UK; UK National Screening Committee, Office for Health Improvement and Disparities, Department of Health and Social Care, London, UK.
  • Alastair K Denniston
    Centre for Patient Reported Outcomes Research Institute of Applied Health Research University of Birmingham Birmingham Reino Unido Centre for Patient Reported Outcomes Research, Institute of Applied Health Research, University of Birmingham, Birmingham, Reino Unido.

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