Banff Digital Pathology Working Group: Going digital in transplant pathology

• Published in: American journal of transplantation Vol. 20; no. 9; pp. 2392 - 2399
• Main Authors: Farris, Alton B., Moghe, Ishita, Wu, Simon, Hogan, Julien, Cornell, Lynn D., Alexander, Mariam P., Kers, Jesper, Demetris, Anthony J., Levenson, Richard M., Tomaszewski, John, Barisoni, Laura, Yagi, Yukako, Solez, Kim
• Format: Journal Article
• Language: English
• Published: United States Elsevier Limited 01.09.2020; John Wiley and Sons Inc
• Subjects: Algorithms; Artificial Intelligence; Atrophy; basic (laboratory) research/science; Biopsy; Classification; classification systems: Banff classification; clinical research/practice; Fibrosis; Graft Rejection; Histocompatibility; Humans; informatics; Kidney Diseases; Kidney Transplantation; Learning algorithms; Machine learning; organ transplantation in general; Original; ORIGINAL ARTICLES; Pathology; pathology/histopathology; Pennsylvania; rejection; Standardization; Working groups; Pennsylvania; pathology/histopathology; classification systems: Banff classification; organ transplantation in general; clinical research/practice; biopsy; informatics; rejection; basic (laboratory) research/science
• ISSN: 1600-6135; 1600-6143; 1600-6143
• DOI: 10.1111/ajt.15850

The Banff Digital Pathology Working Group (DPWG) was formed in the time leading up to and during the joint American Society for Histocompatibility and Immunogenetics/Banff Meeting, September 23‐27, 2019, held in Pittsburgh, Pennsylvania. At the meeting, the 14th Banff Conference, presentations directly and peripherally related to the topic of “digital pathology” were presented; and discussions before, during, and after the meeting have resulted in a list of issues to address for the DPWG. Included are practice standardization, integrative approaches for study classification, scoring of histologic parameters (eg, interstitial fibrosis and tubular atrophy and inflammation), algorithm classification, and precision diagnosis (eg, molecular pathways and therapeutics). Since the meeting, a survey with international participation of mostly pathologists (81%) was conducted, showing that whole slide imaging is available at the majority of centers (71%) but that artificial intelligence (AI)/machine learning was only used in ≈12% of centers, with a wide variety of programs/algorithms employed. Digitalization is not just an end in itself. It also is a necessary precondition for AI and other approaches. Discussions at the meeting and the survey highlight the unmet need for a Banff DPWG and point the way toward future contributions that can be made. The Banff Digital Pathology Working Group assesses the current state of digital pathology and presents next steps for digital transplantation pathology, including utilization of whole slide imaging and artificial intelligence and other algorithm types.