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Original research
Practical guide to training and validation for primary diagnosis with digital pathology
  1. Bethany Jill Williams1,2,
  2. Darren Treanor1,2
  1. 1 Department of Histopathology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
  2. 2 Faculty of Medicine and Health, University of Leeds, Leeds, UK
  1. Correspondence to Dr Bethany Jill Williams, Department of Histopathology, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, UK; bethany.williams2{at}nhs.net

Abstract

Numerous clinical pathology departments are deploying or planning to deploy digital pathology systems for all or part of their diagnostic output. Digital pathology is an evolving technology, and it is important that departments uphold or improve on current standards. Leeds Teaching Hospitals NHS Trust has been scanning 100% of histology slides since September 2018. In this practical paper, we will share our approach to training and validation, which has been incorporated into the Royal College of Pathologists’ guidance for digital pathology implementation. We will offer an overview of the Royal College endorsed training and validation protocol and the evidence base on which it is based. We will provide practical advice on implementation of the protocol and highlight areas of digital reporting that can prove difficult for the novice digital pathologist. In addition, we will share a detailed topographical list of types of diagnostic tasks and features which should form the basis of digital slide training sets.

  • digital pathology
  • education
  • safety

https://doi.org/10.1136/jclinpath-2019-206319

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    Footnotes

    • Handling editor Runjan Chetty.

    • Contributors BJW and DT designed the validation protocol described in the manuscript. BJW drafted the article, with feedback and review from DT.

    • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

    • Competing interests Leeds Teaching Hospitals NHS Trust has a collaborative partnership with Leica Biosystems for a research digital pathology deployment. Both authors are part of the Northern Pathology Imaging Co-Operative.

    • Patient consent for publication Not required.

    • Provenance and peer review Not commissioned; internally peer reviewed.

    • Data availability statement Data sharing not applicable as no datasets generated and/or analysed for this study. No data are available.