Predicting outcomes after transplantation of deceased donor kidneys of marginal quality within the Eurotransplant service area.

INTRODUCTION: Kidneys of marginal quality are increasingly being used to overcome the shortage of donor organs. However, accurate prediction of outcome is needed to optimise the use of these kidneys. We aimed to test the performance of a recently proposed score consisting of delayed graft function (DGF), renal function recovery (RFR), and glomerular filtration rate (GFR) <30 ml/min per 1.73 m2 90 days after transplantation for risk assessment of patient and graft survival. MATERIAL AND METHODS: A total of 221 adult brain death donors with marginal kidneys, transplanted into 223 recipients within Eurotransplant were included in the analysis. Multivariable Cox proportional hazards models were constructed to assess death-censored and all-cause censored graft failure and recipient mortality at one and three years. RESULTS: Recipients with DGF had a higher risk of death-censored graft loss (HR, 95%CIs: 3.058 (1.195 - 7.825)). Recipients with a GFR <30ml/min/1.73m² at 90 days after transplantation had a higher risk of death censored and all-cause graft failure (HR, 95%CIs: 2.122 (1.129-3.990 and 2.122 (1.129 - 3.990)). None of the three components of the proposed score was associated with a higher risk of mortality. CONCLUSION: DGF and eGFR <30 ml/min/1.73m² but not RFR at 90 days predicted graft failure after transplantation of marginal kidneys. However, no combination of these factors was able to predict short-term patient and graft survival.

Clinical and histopathological characteristics of acute kidney injury in a cohort of brain death donors with procurement biopsies.

BACKGROUND: Kidney biopsies are routinely used for diagnostic and prognostic purposes but their utility in the intensive care unit (ICU) setting is limited. We investigated the associations of clinical and histopathological risk factors with ICU-acute kidney injury (AKI) in donors with brain death (DBD) with kidneys of lower quality and procurement biopsies. METHODS: Overall, 221 donors with brain death, 239 biopsies and 197 recipients were included. The biopsies were reread and scored according to the Banff recommendations. Clinical and histopathological data were compared between donors with and without AKI defined by serum creatinine and by urine output. Logistic regression analysis was applied to identify independent clinical and histopathological risk factors for both phenotypes. Lastly, the impact of each AKI phenotype on outcome was explored. AKI was diagnosed based on the RIFLE (Risk, Injury, Failure, Loss of function, End-stage kidney disease) AKIN (Acute Kidney Injury Network) or KDIGO (Kidney Disease Improving Global Outcomes) criteria. RESULTS: Acute kidney injury occurred in 65% of donors based both upon serum creatinine and by urine output. Serum creatinine was able to better discriminate AKI. Multiorgan failure and severe AKI were captured by serum creatinine, and hemodynamic instability by urine output. Donors with serum creatinine-AKI showed lower chronic macrovascular scores, while donors with urine output-AKI had higher chronic microvascular and tubulointerstitial scores. Tubular injury was similar between the subgroups. Except for delayed graft function and one-year death-censored graft survival, the other short-term recipient outcomes were similar for both AKI phenotypes. CONCLUSION: Serum creatinine is more suitable than urine output for defining AKI in donors with brain death. There are distinct clinical risk factors for each AKI-ICU phenotype. Donor AKI phenotype does not predict the recipient´s prognosis. Kidney biopsies do not seem to confer any tangible benefit in defining AKI in donors with brain death.

2-Step-Scores with optional nephropathology for the prediction of adverse outcomes for brain-dead donor kidneys in Eurotransplant.

BACKGROUND AND HYPOTHESIS: The decision for acceptance or discard of the increasingly rare and marginal brain-dead donor kidneys in Eurotransplant (ET) countries has to be made without solid evidence. Thus, we developed and validated flexible clinicopathological scores called 2-Step Scores for the prognosis of delayed graft function (DGF) and one-year death-censored transplant loss (1y-tl) reflecting the current practice of six ET countries including Croatia and Belgium. METHODS: The training set was n=620 for DGF and n=711 for 1y-tl, with validation sets n=158 and n=162. In step 1, stepwise logistic regression models including only clinical predictors were used to estimate the risks. In step 2, risk estimates were updated for statistically relevant intermediate risk percentiles with nephropathology. RESULTS: Step 1 revealed an increased risk of DGF with increased cold ischaemia time, donor and recipient BMI, dialysis vintage, number of HLA-DR mismatches or recipient CMV IgG positivity. On the training and validation set, c-statistics were 0.672 and 0.704, respectively. At a range between 18% and 36%, accuracy of DGF-prognostication improved with nephropathology including number of glomeruli and Banff cv (updated overall c statistics of 0.696 and 0.701, respectively).Risk of 1y-tl increased in recipients with cold ischaemia time, sum of HLA-A. -B, -DR mismatches and donor age. On training and validation sets, c-statistics were 0.700 and 0.769, respectively. Accuracy of 1y-tl prediction improved (c-statistics = 0.706 and 0.765) with Banff ct. Overall, calibration was good on the training, but moderate on the validation set; discrimination was at least as good as established scores when applied to the validation set. CONCLUSION: Our flexible 2-Step Scores with optional inclusion of time-consuming and often unavailable nephropathology should yield good results for clinical practice in ET, and may be superior to established scores. Our scores are adaptable to donation after cardiac death and perfusion pump use.

Early progression of chronic histologic lesions in kidney transplant biopsies is not associated with HLA histocompatibility.

BACKGROUND: Early progression of chronic histologic lesions in kidney allografts represents the main finding in graft attrition. The objective of this retrospective cohort study was to elucidate whether HLA histocompatibility is associated with progression of chronic histologic lesions in the first year post-transplant. Established associations of de novo donor-specific antibody (dnDSA) formation with HLA mismatch and microvascular inflammation (MVI) were calculated to allow for comparability with other study cohorts. METHODS: We included 117 adult kidney transplant recipients, transplanted between 2016 and 2020 from predominantly deceased donors, who had surveillance biopsies at three and twelve months. Histologic lesion scores were assessed according to the Banff classification. HLA mismatch scores (i.e. eplet, predicted indirectly recognizable HLA-epitopes algorithm (PIRCHE-II), HLA epitope mismatch algorithm (HLA-EMMA), HLA whole antigen A/B/DR) were calculated for all transplant pairs. Formation of dnDSAs was quantified by single antigen beads. RESULTS: More than one third of patients exhibited a progression of chronic lesion scores by at least one Banff grade in tubular atrophy (ct), interstitial fibrosis (ci), arteriolar hyalinosis (ah) and inflammation in the area of interstitial fibrosis and tubular atrophy (i-IFTA) from the three to the twelve-month biopsy. Multivariable proportional odds logistic regression models revealed no association of HLA mismatch scores with progression of histologic lesions, except for ah and especially HLA-EMMA DRB1 (OR = 1.10, 95%-CI: 1.03-1.18). Furthermore, the established associations of dnDSA formation with HLA mismatch and MVI (OR = 5.31, 95-% CI: 1.19-22.57) could be confirmed in our cohort. CONCLUSIONS: These data support the association of HLA mismatch and alloimmune response, while suggesting that other factors contribute to early progression of chronic histologic lesions.

Performance of Scores Predicting Adverse Outcomes in Procurement Kidney Biopsies From Deceased Donors With Organs of Lower-Than-Average Quality.

Several scores have been devised for providing a prognosis of outcomes after kidney transplantation. This study is a comprehensive test of these scores in a cohort of deceased donors with kidneys of lower-than-average quality and procurement biopsies. In total, 15 scores were tested on a retrospective cohort consisting of 221 donors, 223 procurement biopsies, and 223 recipient records for performance on delayed graft function, graft function, or death-censored graft loss. The best-performing score for DGF was the purely clinical Chapal score (AUC 0.709), followed by the Irish score (AUC 0.684); for graft function, the Nyberg score; and for transplant loss, the Snoeijs score (AUC 0.630) and the Leuven scores (AUCs 0.637 and 0.620). The only score with an acceptable performance was the Chapal score. Its disadvantage is that knowledge of the cold ischemia time is required, which is not known at allocation. None of the other scores performed acceptably. The scores fared better in discarded kidneys than in transplanted kidneys. Our study shows an unmet need for practical prognostic scores useful at the time of a decision about discarding or accepting deceased donor kidneys of lower-than-average quality in the Eurotransplant consortium.

Histological and clinical evaluation of discarded kidneys in a European cohort of deceased brain death donor kidneys of marginal quality.

BACKGROUND: Despite organ shortages, the discard rate of deceased donor kidneys is high. Risk factors for this trend warrant further study. METHODS: We investigated reasons for discard in a cohort of brain death donors with marginal kidneys and procurement biopsies. Paraffin embedded procurement biopsies were systematically reevaluated and graded for the purpose of the study. Assessment included percentage of global glomerulosclerosis, Banff Lesion scores and tubular epithelial damage. Donor-, transplant process-, perfusion quality-, histopathology-, and recipient-related parameters were compared between discarded and transplanted organs. RESULTS: Although most clinical characteristics were similar between donors whose kidneys were transplanted and those whose kidneys were procured but discarded, discarded kidneys were more likely to be from donors with hepatitis C, to have undergone wedge biopsies, to show changes of acute and chronic injury and to be deemed poor quality. Except for obvious anatomic abnormalities, kidneys were often discarded due to the findings of procurement biopsies. Donors of kidneys discarded for histologic reasons more often had hypertension, coronary artery disease, stroke, and increased serum creatinine. The reason for discard was unknown in 20% of cases. Discarded kidneys came from donors who appeared to be clinically similar to donors whose kidneys were utilized for transplant. CONCLUSION: A considerable proportion of discarded kidneys were of acceptable quality. The analysis of the outcome of every recovered organ could help to overcome this problem. Procurement biopsies more often lead to discard than to transplantation of recovered organs. Proper handling during allocation has to be determined.

Feasibility and Potential of Transcriptomic Analysis Using the NanoString nCounter Technology to Aid the Classification of Rejection in Kidney Transplant Biopsies.

BACKGROUND: Transcriptome analysis could be an additional diagnostic parameter in diagnosing kidney transplant (KTx) rejection. Here, we assessed feasibility and potential of NanoString nCounter analysis of KTx biopsies to aid the classification of rejection in clinical practice using both the Banff-Human Organ Transplant (B-HOT) panel and a customized antibody-mediated rejection (AMR)-specific NanoString nCounter Elements (Elements) panel. Additionally, we explored the potential for the classification of KTx rejection building and testing a classifier within our dataset. METHODS: Ninety-six formalin-fixed paraffin-embedded KTx biopsies were retrieved from the archives of the ErasmusMC Rotterdam and the University Hospital Cologne. Biopsies with AMR, borderline or T cell-mediated rejections (BLorTCMR), and no rejection were compared using the B-HOT and Elements panels. RESULTS: High correlation between gene expression levels was found when comparing the 2 chemistries pairwise (r = 0.76-0.88). Differential gene expression (false discovery rate; P < 0.05) was identified in biopsies diagnosed with AMR (B-HOT: 294; Elements: 76) and BLorTCMR (B-HOT: 353; Elements: 57) compared with no rejection. Using the most predictive genes from the B-HOT analysis and the Element analysis, 2 least absolute shrinkage and selection operators-based regression models to classify biopsies as AMR versus no AMR (BLorTCMR or no rejection) were developed achieving an receiver-operating-characteristic curve of 0.994 and 0.894, sensitivity of 0.821 and 0.480, and specificity of 1.00 and 0.979, respectively, during cross-validation. CONCLUSIONS: Transcriptomic analysis is feasible on KTx biopsies previously used for diagnostic purposes. The B-HOT panel has the potential to differentiate AMR from BLorTCMR or no rejection and could prove valuable in aiding kidney transplant rejection classification.

Short-term outcomes after transplantation of deceased donor kidneys with acute kidney injury: a retrospective analysis of a multicenter cohort of marginal donor kidneys with post-explantation biopsies.

BACKGROUND: Deceased donor kidneys with acute kidney injury (AKI) are often discarded because of concerns about inferior transplant outcomes. A means of grading the quality of such kidneys is the performance of procurement biopsies. METHODS: This is a retrospective study of 221 brain death donors with marginal kidneys transplanted in 223 recipients in Germany. Marginal kidneys were defined as kidneys with procurement biopsies done exceptionally to assess suitability for transplantation in otherwise potentially discarded organs. The impact of deceased donor AKI on patient survival and death-censored graft survival at 1, 3 and 5 years and graft function at 1 and 3 years after transplantation was investigated. RESULTS: Recipients of kidneys with stage 3 AKI had a greater incidence of delayed graft function [DGF; ORStage 1: 1.435 (95% CI 0.438-0.702), ORStage 2: 2.463 (95% CI 0.656-9.245), ORStage 3: 4.784 (95% CI 1.421-16.101)] but a similar graft and patient survival compared to recipients of donors without AKI and with AKI stage 1 and 2 as well. The coexistence of recipient DGF and donor AKI was associated with the lowest graft survival and function rates. CONCLUSION: The transplantation of deceased donor marginal kidneys with AKI confers a higher risk for DGF but is associated with acceptable graft and patient outcomes, which do not differ in comparison with marginal donor kidneys without AKI. Graft prognosis is especially poor if donor AKI and recipient DGF concur. Donor AKI was a risk factor independent of the histological lesions of procurement biopsies.

Gasdermin D-deficient mice are hypersensitive to acute kidney injury.

Signaling pathways of regulated necrosis, such as necroptosis and ferroptosis, contribute to acute kidney injury (AKI), but the role of pyroptosis is unclear. Pyroptosis is mediated by the pore-forming protein gasdermin D (GSDMD). Here, we report a specific pattern of GSDMD-protein expression in the peritubular compartment of mice that underwent bilateral ischemia and reperfusion injury (IRI). Along similar lines, the GSDMD-protein expression in whole kidney lysates increased during the first 84 h following cisplatin-induced AKI. Importantly, unlike whole kidney lysates, no GSDMD-protein expression was detectable in isolated kidney tubules. In IRI and cisplatin-induced AKI, GSDMD-deficient mice exhibited hypersensitivity to injury as assessed by tubular damage, elevated markers of serum urea, and serum creatinine. This hypersensitivity was reversed by a combined deficiency of GSDMD and the necroptosis mediator mixed lineage kinase domain-like (MLKL). In conclusion, we demonstrate a non-cell autonomous role for GSDMD in protecting the tubular compartment from necroptosis-mediated damage in IRI.

A user-friendly tool for cloud-based whole slide image segmentation with examples from renal histopathology.

Background: Image-based machine learning tools hold great promise for clinical applications in pathology research. However, the ideal end-users of these computational tools (e.g., pathologists and biological scientists) often lack the programming experience required for the setup and use of these tools which often rely on the use of command line interfaces. Methods: We have developed Histo-Cloud, a tool for segmentation of whole slide images (WSIs) that has an easy-to-use graphical user interface. This tool runs a state-of-the-art convolutional neural network (CNN) for segmentation of WSIs in the cloud and allows the extraction of features from segmented regions for further analysis. Results: By segmenting glomeruli, interstitial fibrosis and tubular atrophy, and vascular structures from renal and non-renal WSIs, we demonstrate the scalability, best practices for transfer learning, and effects of dataset variability. Finally, we demonstrate an application for animal model research, analyzing glomerular features in three murine models. Conclusions: Histo-Cloud is open source, accessible over the internet, and adaptable for segmentation of any histological structure regardless of stain.

Effect of creatinine metrics on outcome after transplantation of marginal donor kidneys.

INTRODUCTION: Predicting outcome after transplantation of marginal kidneys is a challenging task. Donor creatinine or estimated glomerular filtration rate (eGFR) are integral components of the respective risk scores. However, there is uncertainty on which of their values obtained successively during procurement is the most suitable. MATERIAL AND METHODS: This is a retrospective study of 221 adult brain death donors with marginal kidneys, transplanted in 223 recipients. We applied logistic regression analysis to investigate the association between initial (at hospital admission), nadir (lowest), zenith (highest) and terminal (at recovery) donor eGFR with primary non-function (PNF), delayed graft function (DGF), 3- and 12-month graft function and 1- and 3-year patient- and death-censored graft survival. RESULTS: In the multivariate analysis, admission, terminal, and the lowest donor eGFR could most accurately predict DGF. The respective ORs [95% CI] were: 0.875 [0.771-0.993], 0.818 [95% CI: 0.726-0.922] and 0.793 [0.689-0.900]. Although not being significant for DGF (OR 0.931 [95% CI: 0.817-1.106]), the highest eGFR was the best predictor of 3-month graft function (adjusted b coefficient 1.161 [95% CI: 0.355-1.968]). Analysis of primary nonfunction showed that determination of initial and the highest eGFR proved to be the best predictors. The respective ORs [95% CI] were: 0.804 [0.667-0.968] and 0.750 [0.611-0.919]. There were no differences in the risk associations of each of the four eGFR recordings with patient- and graft survival. CONCLUSION: The various eGFR recordings determined during the procurement process of marginal donors can predict PNF, DGF and 3- and 12-month graft function. Regarding short-term patient- and graft survival, there appears to be impacted by recipient factors rather than donor kidney function.

A tool for federated training of segmentation models on whole slide images.

The largest bottleneck to the development of convolutional neural network (CNN) models in the computational pathology domain is the collection and curation of diverse training datasets. Training CNNs requires large cohorts of image data, and model generalizability is dependent on training data heterogeneity. Including data from multiple centers enhances the generalizability of CNN-based models, but this is hindered by the logistical challenges of sharing medical data. In this paper, we explore the feasibility of training our recently developed cloud-based segmentation tool (Histo-Cloud) using federated learning. Using a dataset of renal tissue biopsies we show that federated training to segment interstitial fibrosis and tubular atrophy (IFTA) using datasets from three institutions is not found to be different from a training by pooling the data on one server when tested on a fourth (holdout) institution's data. Further, training a model to segment glomeruli for a federated dataset (split by staining) demonstrates similar performance.

A cloud-based tool for federated segmentation of whole slide images.

It is commonly known that diverse datasets of WSIs are beneficial when training convolutional neural networks, however sharing medical data between institutions is often hindered by regulatory concerns. We have developed a cloud-based tool for federated WSI segmentation, allowing collaboration between institutions without the need to directly share data. To show the feasibility of federated learning on pathology data in the real world, We demonstrate this tool by segmenting IFTA from three institutions and show that keeping the three datasets separate does not hinder segmentation performance. This pipeline is deployed in the cloud for easy access for data viewing and annotation by each site's respective constituents.

Cholesterol Embolization Syndrome After Kidney Transplantation: A Case Series and Systematic Review.

BACKGROUND: Cholesterol embolization syndrome (CES) is an uncommon but well-known cause of renal failure in native kidneys, but little is known about CES in kidney transplant recipients. The aim of this study was to determine the incidence, clinical characteristics, histopathology, and prognosis of CES after kidney transplantation. METHODS: CES cases in both transplanted and native kidneys (control group) were identified by searching the databases of the divisions of Nephrology and Pathology of our institution. Clinical data were retrospectively collected. Biopsies were classified according to the latest Banff 2019 Update. Second, a systematic literature search was performed (December 01, 2020) of Ovid MEDLINE, EMBASE, the Cochrane Central Register of controlled trials, Google Scholar, and Web of Science. RESULTS: CES was observed in for-cause biopsies of 11 out of 2350 (0.47%) kidney transplant recipients transplanted between January 1, 2006, and December 31, 2018 (0.0009 cases per person-year). All patients had ≥1 cardiovascular risk factor, and 9 donors were expanded criteria donors. Graft loss occurred in 27.3% of the patients diagnosed with CES. Eight transplant biopsies with CES were also classified as biopsy-proven acute rejection. Transplant biopsies showed signs of inflammation (arteritis, n = 7; interstitial inflammation, n = 5; tubulitis, n = 7). One patient with CES in a native kidney was identified. The biopsy of the native kidney only showed arteritis and classified as an isolated "v" lesion. The literature search resulted in 188 unique articles of which 20 were included. A total of 47 cases of CES after kidney transplantation was reported. Cholesterol emboli were found in <1% of all kidney transplant biopsies. In 57.8% of the kidney transplant biopsies with CES described in literature, concomitant inflammation was present. CONCLUSIONS: CES is an uncommon cause of kidney transplant failure, although the incidence of CES may be underestimated. CES may mimic rejection as it can be accompanied by arteritis.

PodoSighter: A Cloud-Based Tool for Label-Free Podocyte Detection in Kidney Whole-Slide Images.

BACKGROUND: Podocyte depletion precedes progressive glomerular damage in several kidney diseases. However, the current standard of visual detection and quantification of podocyte nuclei from brightfield microscopy images is laborious and imprecise. METHODS: We have developed PodoSighter, an online cloud-based tool, to automatically identify and quantify podocyte nuclei from giga-pixel brightfield whole-slide images (WSIs) using deep learning. Ground-truth to train the tool used immunohistochemically or immunofluorescence-labeled images from a multi-institutional cohort of 122 histologic sections from mouse, rat, and human kidneys. To demonstrate the generalizability of our tool in investigating podocyte loss in clinically relevant samples, we tested it in rodent models of glomerular diseases, including diabetic kidney disease, crescentic GN, and dose-dependent direct podocyte toxicity and depletion, and in human biopsies from steroid-resistant nephrotic syndrome and from human autopsy tissues. RESULTS: The optimal model yielded high sensitivity/specificity of 0.80/0.80, 0.81/0.86, and 0.80/0.91, in mouse, rat, and human images, respectively, from periodic acid-Schiff-stained WSIs. Furthermore, the podocyte nuclear morphometrics extracted using PodoSighter were informative in identifying diseased glomeruli. We have made PodoSighter freely available to the general public as turnkey plugins in a cloud-based web application for end users. CONCLUSIONS: Our study demonstrates an automated computational approach to detect and quantify podocyte nuclei in standard histologically stained WSIs, facilitating podocyte research, and enabling possible future clinical applications.

Differential expression of microRNA miR-150-5p in IgA nephropathy as a potential mediator and marker of disease progression.

Understanding why certain patients with IgA nephropathy progress to kidney failure while others maintain normal kidney function remains a major unanswered question. To help answer this, we performed miRNome profiling by next generation sequencing of kidney biopsies in order to identify microRNAs specifically associated with the risk of IgA nephropathy progression. Following sequencing and validation in independent cohorts, four microRNAs (-150-5p, -155-5p, -146b-5p, -135a-5p) were found to be differentially expressed in IgA nephropathy progressors compared to non-progressors, and patients with thin membrane nephropathy, lupus nephritis and membranous nephropathy, and correlated with estimated glomerular filtration rate, proteinuria, and the Oxford MEST-C scores (five histological features that are independent predictors of clinical outcome). Each individual microRNA increased the discrimination score of the International IgAN Prediction Tool, although due to the small number of samples the results did not reach statistical significance. miR-150-5p exhibited the largest amplitude of expression between cohorts and displayed the best discrimination between IgA nephropathy progressors and non-progressors by receiver operating curve analysis (AUC: 0.8). However, expression was similarly upregulated in kidneys with established fibrosis and low estimated glomerular filtration rates at the time of biopsy. Consistent with a more generic role in kidney fibrosis, in situ hybridization revealed that miR-150-5p was found in lymphoid infiltrates, and areas of proliferation and fibrosis consistent with the known drivers of progression. Thus, miR-150-5p may be a potential functional mediator of kidney fibrosis that may add value in predicting risk of progression in IgA nephropathy and other kidney diseases.

Artificial intelligence and machine learning in nephropathology.

Artificial intelligence (AI) for the purpose of this review is an umbrella term for technologies emulating a nephropathologist's ability to extract information on diagnosis, prognosis, and therapy responsiveness from native or transplant kidney biopsies. Although AI can be used to analyze a wide variety of biopsy-related data, this review focuses on whole slide images traditionally used in nephropathology. AI applications in nephropathology have recently become available through several advancing technologies, including (i) widespread introduction of glass slide scanners, (ii) data servers in pathology departments worldwide, and (iii) through greatly improved computer hardware to enable AI training. In this review, we explain how AI can enhance the reproducibility of nephropathology results for certain parameters in the context of precision medicine using advanced architectures, such as convolutional neural networks, that are currently the state of the art in machine learning software for this task. Because AI applications in nephropathology are still in their infancy, we show the power and potential of AI applications mostly in the example of oncopathology. Moreover, we discuss the technological obstacles as well as the current stakeholder and regulatory concerns about developing AI applications in nephropathology from the perspective of nephropathologists and the wider nephrology community. We expect the gradual introduction of these technologies into routine diagnostics and research for selective tasks, suggesting that this technology will enhance the performance of nephropathologists rather than making them redundant.

The Banff 2019 Kidney Meeting Report (I): Updates on and clarification of criteria for T cell- and antibody-mediated rejection.

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.

Molecular Analysis of Renal Allograft Biopsies: Where Do We Stand and Where Are We Going?

A renal core biopsy for histological evaluation is the gold standard for diagnosing renal transplant pathology. However, renal biopsy interpretation is subjective and can render insufficient precision, making it difficult to apply a targeted therapeutic regimen for the individual patient. This warrants a need for additional methods assessing disease state in the renal transplant. Significant research activity has been focused on the role of molecular analysis in the diagnosis of renal allograft rejection. The identification of specific molecular expression patterns in allograft biopsies related to different types of allograft injury could provide valuable information about the processes underlying renal transplant dysfunction and can be used for the development of molecular classifier scores, which could improve our diagnostic and prognostic ability and could guide treatment. Molecular profiling has the potential to be more precise and objective than histological evaluation and may identify injury even before it becomes visible on histology, making it possible to start treatment at the earliest time possible. Combining conventional diagnostics (histology, serology, and clinical data) and molecular evaluation will most likely offer the best diagnostic approach. We believe that the use of state-of-the-art molecular analysis will have a significant impact in diagnostics after renal transplantation. In this review, we elaborate on the molecular phenotype of both acute and chronic T cell-mediated rejection and antibody-mediated rejection and discuss the additive value of molecular profiling in the setting of diagnosing renal allograft rejection and how this will improve transplant patient care.