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

Berezowska, Sabina; Cathomas, Gieri; Grobholz, Rainer; Henkel, Maurice; Jochum, Wolfram; Koelzer, Viktor H; Kreutzfeldt, Mario; Mertz, Kirsten D; Rössle, Matthias; Soldini, Davide; Zlobec, Inti; Janowczyk, Andrew (2023). Digital image analysis and artificial intelligence in pathology diagnostics-the Swiss view. Pathologie, 44(Suppl 3), pp. 222-224. Springer 10.1007/s00292-023-01262-w

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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.

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