The Banff 2019 Kidney Meeting Report (I): Updates on and clarification of criteria for T cell– and antibody‐mediated rejection. Issue 9 (28th May 2020) - Loupy, Alexandre; Haas, Mark; Roufosse, Candice; Naesens, Maarten; Adam, Benjamin; Afrouzian, Marjan; Akalin, Enver; Alachkar, Nada; Bagnasco, Serena; Becker, Jan U.; Cornell, Lynn D.; Clahsen‐van Groningen, Marian C.; et al.
Abstract : The XV. Banff conference for allograft pathology was held in conjunction with the annual meeting of the American Society for Histocompatibility and Immunogenetics in Pittsburgh, PA (USA) and focused on refining recent updates to the classification, advances from the Banff working groups, and standardization of molecular diagnostics. This report on kidney transplant pathology details clarifications and refinements to the criteria for chronic active (CA) T cell–mediated rejection (TCMR), borderline, and antibody‐mediated rejection (ABMR). The main focus of kidney sessions was on how to address biopsies meeting criteria for CA TCMR plus borderline or acute TCMR. Recent studies on the clinical impact of borderline infiltrates were also presented to clarify whether the threshold for interstitial inflammation in diagnosis of borderline should be i0 or i1. Sessions on ABMR focused on biopsies showing microvascular inflammation in the absence of C4d staining or detectable donor‐specific antibodies; the potential value of molecular diagnostics in such cases and recommendations for use of the latter in the setting of solid organ transplantation are presented in the accompanying meeting report. Finally, several speakers discussed the capabilities of artificial intelligence and the potential for use of machine learning algorithms in diagnosis and personalized therapeutics in solid organ transplantation. Abstract : This report focuses on the clarification of the criteria for chronic active T cell–mediated rejection and antibody‐mediated rejection and the optimization of the inflammation threshold for the diagnosis of borderline for acute T cell–mediated rejection, and discusses the potential to use machine learning in diagnostics and personalized therapeutics in solid organ transplantation.