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AI used to predict future flares of ulcerative colitis activity

Ulcerative colitis assessment could be improved after new research shows that an AI model could predict flare-ups and complications after reading biopsies.

3 March 2023
Computer generated illustration of small and large intestines in brown and red colours against a black background

Ulcerative colitis assessment could be improved after new research shows that an artificial intelligence model could predict flare-ups and complications after reading biopsies.

In a new paper published in Gastroenterology today (Friday 3 March), researchers supported by the National Institute for Health and Care Research Birmingham Biomedical Research Centre have trialled an AI diagnostic tool that can read digitised biopsies taken during colonoscopy.

The Computer-Aided Diagnostic model was able to predict the risk of flare-ups for ulcerative colitis, which is a relapsing-remitting condition and makes the prognosis for the disease uncertain. In the trial, the model was able to predict patients at risk of a flare in the disease as well as humans.

The system was trained on existing digitised biopsies and was able to detect activity related to ulcerative colitis with 89% accuracy for positive results. It was also able to identify markers of inflammation activity and healing in the same area as biopsies were taken with 80% accuracy, similar to human pathologists.

Ulcerative Colitis is a complex condition to predict, and developing machine learning-derived systems to make this diagnostic job quicker and more accurate could be a game changer

Marietta Iacucci

Professor Marietta Iacucci from the Institute of Immunology and Immunotherapy at the University of Birmingham and University College Cork in Ireland, and co-lead author of the paper said:

“The power of AI in healthcare is evident in trials like these, where a model can be used to standardize in real-time histological assessment of Ulcerative Colitis disease activity. But most importantly it provides analytical support and enables clinicians to support those at the greatest risk of relapsing symptoms and disease course.

“Ulcerative Colitis is a complex condition to predict, and developing machine learning-derived systems to make this diagnostic job quicker and more accurate could be a game changer. As models like this further develop, the predictive quality is likely to improve even more, and our paper demonstrates how beneficial such technology could be for clinicians and, crucially patients.”

Notes for editors

  • For media enquiries please contact Tim Mayo, Press Office, University of Birmingham, tel: +44 (0)7920 405040: email: 
  • The University of Birmingham is ranked amongst the world’s top 100 institutions. Its work brings people from across the world to Birmingham, including researchers, teachers and more than 6,500 international students from over 150 countries.
  • The University of Birmingham is a founding member of Birmingham Health Partners (BHP), a strategic alliance which transcends organisational boundaries to rapidly translate healthcare research findings into new diagnostics, drugs and devices for patients. Birmingham Health Partners is a strategic alliance between seven organisations who collaborate to bring healthcare innovations through to clinical application:
    • University of Birmingham
    • University Hospitals Birmingham NHS Foundation Trust
    • Birmingham Women's and Children's Hospitals NHS Foundation Trust
    • Aston University
    • The Royal Orthopaedic Hospital NHS Foundation Trust
    • Sandwell and West Birmingham Hospitals NHS Trust
    • West Midlands Academic Health Science Network

 

About the National Institute for Health and Care Research

  • The mission of the National Institute for Health and Care Research (NIHR) is to improve the health and wealth of the nation through research. We do this by:
    • Funding high quality, timely research that benefits the NHS, public health and social care;
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    • Funding applied global health research and training to meet the needs of the poorest people in low and middle income countries.
  • NIHR is funded by the Department of Health and Social Care. Its work in low and middle income countries is principally funded through UK Aid from the UK government.

Featured staff

  • Dr Marietta Iacucci

    Honorary Associate Professor in Gastroenterology

    Staff profile for Dr Marietta Iacucci, Reader in Gastroenterology, Institute of Translational of Medicine, Institute of Immunology & Immunotherapy, College of Medical and Dental Sciences, the University of Birmingham

    Phone: +44(0)121 371 8119
    Email: m.iacucci@bham.ac.uk

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