Literature DB >> 30765419

Digital immunohistochemistry implementation, training and validation: experience and technical notes from a large clinical laboratory.

Bethany Jill Williams1,2, Dharshana Jayewardene2, Darren Treanor3,2.   

Abstract

AIMS: To consider the value proposition of digitisation of clinical immunohistochemistry services, and to develop an approach to digital immunohistochemistry implementation and validation in a large clinical laboratory.
METHODS: A methodology for slide scanning in the laboratory was developed, in addition to a novel validation exercise, to allow pathologists to identify the strengths and weaknesses of digital immunohistochemistry reporting, and train in digital immunohistochemistry slide assessment.
RESULTS: A total of 1480 digital immunohistochemistry slides were assessed by 24 consultant pathologists, with complete clinical concordance between the digital and the glass slide assessment observed. Certain stains were identified as being difficult/time consuming to assess using ×20 digital slides. These stains were rescanned at ×40, which improved the confidence of the pathologists to make a digital assessment. Full digitisation of immunohistochemistry slides was achieved, introducing six new steps into the pre-existing laboratory workflow.
CONCLUSIONS: While initially encountering challenges in terms of workflow, our experience showed that a well-designed, adequately resourced and well-managed scanning process can minimise the delay in slides being made available for review. Our approach to validation highlighted the need for careful assessment of a digital pathology system and scanning protocols before pathologists are expected to transfer from the light microscope to the digital microscope for routine immunohistochemistry assessment. © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.

Keywords:  digital pathology; immunohistochemistry; laboratory management

Mesh:

Year:  2019        PMID: 30765419     DOI: 10.1136/jclinpath-2018-205628

Source DB:  PubMed          Journal:  J Clin Pathol        ISSN: 0021-9746            Impact factor:   3.411


  5 in total

Review 1.  Validation of digital microscopy: Review of validation methods and sources of bias.

Authors:  Christof A Bertram; Nikolas Stathonikos; Taryn A Donovan; Alexander Bartel; Andrea Fuchs-Baumgartinger; Karoline Lipnik; Paul J van Diest; Federico Bonsembiante; Robert Klopfleisch
Journal:  Vet Pathol       Date:  2021-08-26       Impact factor: 2.221

Review 2.  Current Developments of Artificial Intelligence in Digital Pathology and Its Future Clinical Applications in Gastrointestinal Cancers.

Authors:  Alex Ngai Nick Wong; Zebang He; Ka Long Leung; Curtis Chun Kit To; Chun Yin Wong; Sze Chuen Cesar Wong; Jung Sun Yoo; Cheong Kin Ronald Chan; Angela Zaneta Chan; Maribel D Lacambra; Martin Ho Yin Yeung
Journal:  Cancers (Basel)       Date:  2022-08-03       Impact factor: 6.575

Review 3.  Digital pathology - Rising to the challenge.

Authors:  Heather Dawson
Journal:  Front Med (Lausanne)       Date:  2022-07-22

4.  Dissecting the Business Case for Adoption and Implementation of Digital Pathology: A White Paper from the Digital Pathology Association.

Authors:  Giovanni Lujan; Jennifer C Quigley; Douglas Hartman; Anil Parwani; Brian Roehmholdt; Bryan Van Meter; Orly Ardon; Matthew G Hanna; Dan Kelly; Chelsea Sowards; Michael Montalto; Marilyn Bui; Mark D Zarella; Victoria LaRosa; Gerard Slootweg; Juan Antonio Retamero; Mark C Lloyd; James Madory; Doug Bowman
Journal:  J Pathol Inform       Date:  2021-04-07

Review 5.  Quality Assessment Across Disciplines in Head and Neck Cancer Treatment Diagnostic Pathology in HNSCC.

Authors:  Philip Sloan; Max Robinson
Journal:  Front Oncol       Date:  2020-03-24       Impact factor: 6.244

  5 in total

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