The UK pathomics digital learning library.

  • Research type

    Research Study

  • Full title

    The UK pathomics digital learning library (Pathomics DLL): Next generation morphological evaluation of biopsy samples.

  • IRAS ID

    341625

  • Contact name

    Louise Oni

  • Contact email

    lw1@liverpool.ac.uk

  • Sponsor organisation

    University of Liverpool

  • Duration of Study in the UK

    2 years, 11 months, 28 days

  • Research summary

    Chronic kidney disease (CKD) is a long-term condition where the kidneys do not work as well as they should. About 1000 children in the United Kingdom (UK) have severe CKD due to various conditions, requiring kidney replacement therapy with dialysis and/or transplantation. The kidney biopsy is used to diagnose some kidney diseases. Current technology uses artificial intelligence (AI) in a technique called "pathomics", a new way to look at biopsy tests that have been changed into medical images. It aims to find patterns that we might not be able to see normally by using powerful computer programmes to view lots of digital images. This study aims to scan kidney biopsy tests that have been collected and stored in two Paediatric Hospitals (Alder Hey Children's Hospital and Great Ormond Street Hospital for Children) and create medical images, also known as whole slide images (WSI). This study aims to create a library of digital images and use deep learning to identify patterns from kidney biopsies taken in patients with kidney disease to learn how to stop CKD. Eligible kidney biopsy samples will be identified by each site's histopathology department and will include samples from children and adults. Clinical data will be collected by the research team while scanning the samples and will be stored pseudo-anonymously on a secure online database (REDCap). The anonymized images will be sent to a team of researchers in Rheinisch-Westfälische Technische Hochschule (RWTH) Aachen University, Germany, who will use AI to perform "pathomics" analysis. This study aims to reveal important variations in kidney morphology in patients across the ages and identify those at greatest risk of CKD. This study is expected to run three years in total. This study does not include direct research on human tissue.

  • REC name

    South Central - Berkshire Research Ethics Committee

  • REC reference

    24/SC/0182

  • Date of REC Opinion

    21 Jun 2024

  • REC opinion

    Favourable Opinion