Digital image analysis and artificial intelligence in pathology diagnostics—the Swiss view

• Type of Material: Article
• Authors: Sabina Berezowska, Centre Hospitalier Universitaire Vaudois; Gieri Cathomas, University of Bern; Rainer Grobholz, University of Zurich; Maurice Henkel, University Hospital Basel; Wolfram Jochum, Cantonal Hospital St. Gallen; Viktor H. Koelzer, University Hospital of Zurich; Mario Kreutzfeldt, University of Geneva; Kirsten D. Mertz, Cantonal Hospital Baselland; Matthias Rossle, Luzerner Kantonsspital; Davide Soldini, Pathologie Zentrum Zürich medica; Inti Zlobec, University of Bern; Andrew R. Janowczyk, Emory University
• Language: English
• Date: 2023-11-21
• Publisher: Springer
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2023
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): https://doi.org/10.1007/s00292-023-01262-w
• Title of Journal or Parent Work: Pathologie
• Volume: 44
• Issue: Supplement 3
• Start Page: 222
• End Page: 224
• Grant/Funding Information: Open access funding provided by University of Lausanne
• Keywords: Artificial intelligence; Delphi process; Digitalization; Pathology; Image analysis; best-practice recommendations
• Research Categories: Health Sciences, Pathology; Artificial Intelligence

Abstract

Digital pathology (DP) is increasingly entering routine clinical pathology diagnostics. As digitization of the routine caseload advances, implementation of digital image analysis algorithms and artificial intelligence tools becomes not only attainable, but also desirable in daily sign out. The Swiss Digital Pathology Consortium (SDiPath) has initiated a Delphi process to generate best-practice recommendations for various phases of the process of digitization in pathology for the local Swiss environment, encompassing the following four topics: i) scanners, quality assurance, and validation of scans; ii) integration of scanners and systems into the pathology laboratory information system; iii) the digital workflow; and iv) digital image analysis (DIA)/artificial intelligence (AI). The current article focuses on the DIA-/AI-related recommendations generated and agreed upon by the working group and further verified by the Delphi process among the members of SDiPath. Importantly, they include the view and the currently perceived needs of practicing pathologists from multiple academic and cantonal hospitals as well as private practices.