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Updated: Aug 13, 2026

Non-invasive Imaging of Acute Allograft Rejection after Rat Renal Transplantation Using 18F-FDG PET
Published on: April 28, 2013
Real-time monitoring of acute liver-allograft rejection using the Banff schema
A J Demetris1, K Ruppert, I Dvorchik
1Department of Pathology, Division of Transplantation, University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA. demetrisaj@msx.upmc.edu.
Background:
The Banff schema is the internationally accepted standard for grading acute liver-allograft rejection, but it has not been prospectively tested.
Methods:
Complete Banff grading was prospectively applied to 2,038 liver-allograft biopsies from 901 adult tacrolimus-treated primary hepatic allograft recipients between August 1995 and September 2001. Histopathologic data was melded with demographic, clinical, and laboratory data into a database on an ongoing basis using locally developed software.
Results:
Acute rejection developed in 575 of 901 (64%) patients and the worst grade was mild in 422 of 575 (73%). At least one episode of moderate or severe acute rejection developed in 153 of 901 (17%) patients and most episodes, irrespective of severity, occurred within the first year after transplantation. Patients with moderate or severe acute rejection showed higher alanine aminotransferase (P =0.007) and aspartate aminotransferase ( P=0.07) levels and were more likely to develop perivenular fibrosis on follow-up biopsies (P =0.001) and graft failure from acute or chronic rejection ( P=0.004) than those with mild rejection. Regardless of severity, 80% of patients with acute rejection did not develop significant fibrosis in follow-up biopsies, and graft failure from acute or chronic rejection occurred in only 11 of 901 (1%) allografts.
Conclusions:
Most acute-rejection episodes are mild and do not lead to clinically significant architectural sequelae. When tested prospectively under real-life and -time conditions, the Banff schema can be used to identify those few patients who are potentially at risk for more significant problems. Creation, capture, and integration of non-free text, or "digital," pathology data can be used to prospectively conduct outcomes-based research in transplantation.
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