Banff Digital Pathology Working Group: Image bank, artificial intelligence algorithm, and challenge trial developments Editorial


Authors: Farris, A. B.; Alexander, M. P.; Balis, U. G. J.; Barisoni, L.; Boor, P.; Bülow, R. D.; Cornell, L. D.; Demetris, A. J.; Farkash, E.; Hermsen, M.; Hogan, J.; Kain, R.; Kers, J.; Kong, J.; Levenson, R. M.; Loupy, A.; Naesens, M.; Sarder, P.; Tomaszewski, J. E.; van der Laak, J.; van Midden, D.; Yagi, Y.; Solez, K.
Title: Banff Digital Pathology Working Group: Image bank, artificial intelligence algorithm, and challenge trial developments
Abstract: The Banff Digital Pathology Working Group (DPWG) was established with the goal to establish a digital pathology repository; develop, validate, and share models for image analysis; and foster collaborations using regular videoconferencing. During the calls, a variety of artificial intelligence (AI)-based support systems for transplantation pathology were presented. Potential collaborations in a competition/trial on AI applied to kidney transplant specimens, including the DIAGGRAFT challenge (staining of biopsies at multiple institutions, pathologists’ visual assessment, and development and validation of new and pre-existing Banff scoring algorithms), were also discussed. To determine the next steps, a survey was conducted, primarily focusing on the feasibility of establishing a digital pathology repository and identifying potential hosts. Sixteen of the 35 respondents (46%) had access to a server hosting a digital pathology repository, with 2 respondents that could serve as a potential host at no cost to the DPWG. The 16 digital pathology repositories collected specimens from various organs, with the largest constituent being kidney (n = 12,870 specimens). A DPWG pilot digital pathology repository was established, and there are plans for a competition/trial with the DIAGGRAFT project. Utilizing existing resources and previously established models, the Banff DPWG is establishing new resources for the Banff community. Copyright © 2023 Farris, Alexander, Balis, Barisoni, Boor, Bülow, Cornell, Demetris, Farkash, Hermsen, Hogan, Kain, Kers, Kong, Levenson, Loupy, Naesens, Sarder, Tomaszewski, van der Laak, van Midden, Yagi and Solez.
Keywords: adult; controlled study; human tissue; major clinical study; validation process; image analysis; clinical assessment; pathology; algorithms; feasibility study; kidney; algorithm; artificial intelligence; pathologist; competition; human experiment; kidney transplantation; digital pathology; kidney graft; machine learning; humans; human; male; female; article; videoconferencing; banff
Journal Title: Transplant International
Volume: 36
ISSN: 0934-0874
Publisher: Wiley Blackwell  
Date Published: 2023-10-01
Start Page: 11783
Language: English
DOI: 10.3389/ti.2023.11783
PUBMED: 37908675
PROVIDER: scopus
PMCID: PMC10614670
DOI/URL:
Notes: Article -- Source: Scopus
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  1. Yukako Yagi
    74 Yagi