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Background Proliferative glomerulonephritis with monoclonal IgG deposits (PGNMID) is a glomerular disease defined by non-organized glomerular deposits of heavy and light chain-restricted immunoglobulin and is rarely reported in children. Methods We characterized a series of nine pediatric patients from two academic centers with biopsy-proven PGNMID and additionally describe two patients with monotypic IgG in the setting of IgM deposition. Results Each patient presented with hematuria and/or proteinuria; however, only five had elevated serum creatinine. Prodromal or concurrent infection was identified in six patients, low C3 in five, and alternate complement pathway gene variants in two. No monoclonal serum proteins were identified in five tested patients. Seven patients had monotypic deposits composed of IgG3-[lambda], two showed IgG3-[kappa], and one each IgG1 and IgG3 with lambda dominance in the setting of IgM deposition. The glomerular pattern was predominantly mesangial proliferative or membranoproliferative glomerulonephritis (MPGN). Treatment and outcomes were variable; four patients have recent PGNMID diagnoses and therefore minimal follow up, one had relatively stable kidney function for over a decade, and six experienced kidney failure, with four receiving transplants. Recurrent deposits of the same isotype were identified in five of six transplanted kidneys, corresponding to three of four transplanted patients. One of these patients developed PGNMID recurrences in three separate kidney allografts over a 20-year disease course. Conclusions Our study emphasizes the need for upfront IgG subclass investigation in pediatric mesangial or MPGN with IgG deposition and monotypic or biased light-chain staining. Furthermore, this pediatric experience suggests expanded pathogenic considerations in PGNMID., Author(s): Paul Miller [sup.1] , Andrew Y. Xiao [sup.1] [sup.2] , Vanderlene L. Kung [sup.3] , Richard K. Sibley [sup.1] , John P. Higgins [sup.1] , Neeraja Kambham [sup.1] , [...]

Objectives: To explore the implications of cervical conization specimens lacking the targeted high-grade squamous intraepithelial lesions (negative cone).Methods: We studied 540 conization procedures: 400 positive cones and 140 negative cones. Clinicopathologic features and 2-year follow-up results were reported.Results: Negative cones comprised 22% of procedures triggered by CIN2 or higher biopsies. Procedures triggered by cytology produced much higher percentages of negative cones (37% high-grade squamous intraepithelial lesion [HSIL], 46% atypical squamous cells-cannot exclude high-grade squamous intraepithelial lesion [ASC-H], and 76% low-grade squamous intraepithelial lesion-cannot exclude high-grade squamous intraepithelial lesion [LSIL-H]). Upon reviewing negative excision-triggering biopsy and cytology, we downgraded 24 (24%) CIN2 biopsies, three (14%) HSIL, five (83%) ASC-H, and 12 (92%) LSIL-H. One-third of our negative cones can be attributed to overdiagnosis either on biopsy or cytology. Patients with negative cones were older and had smaller excisions, negative colposcopic findings, and negative/equivocal high-risk human papillomavirus (HR-HPV). Within 2 years, 35 (25%) women with negative cones experienced ASCUS or LSIL. Only one (0.7%) recurred as CIN3, a significantly lower percentage than women with positive cones (13%).Conclusions: We advocate careful review of all excision-triggering biopsy and cytology, especially in cases of LSIL-H. Patients with negative cones should be surveyed with cytology and HR-HPV testing. [ABSTRACT FROM AUTHOR]

Leukocyte chemotactic factor 2 amyloidosis (ALECT2) is a recently described form of systemic amyloidosis, which most commonly affects the kidney and liver. The LECT2 protein is produced during inflammatory processes, but its precise function in renal diseases in unclear. ALECT2, however, is known to be a relatively common form of renal amyloidosis, after amyloid light chain and serum amyloid A types and is most often seen in patients of Hispanic ethnicity. ALECT2 can occur de novo or as recurrent disease in kidney transplants. We present the first case, to our knowledge, of de novo ALECT2 in a pediatric kidney transplant patient, 15 years post‐transplant. [ABSTRACT FROM AUTHOR]

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., (Copyright © 2021 by the American Society of Nephrology.)

Background: Accurate staging of newly diagnosed or recurrent malignancy is essential for effective treatment. An important first step in staging involves the use of PET/CT to identify areas of FDG avidity. PET/CT however has limitations, including false positive FDG uptake from benign causes. In this paper we characterize an uncommon yet clinically important cause of false positive PET/CTs, that of benign anthracotic lymphadenitis (BAL). We examine the clinical, radiographic and histologic characteristics of BAL in patients referred for endobronchial ultrasound (EBUS) guided biopsies and discuss its context in relation to existing literature., Methods: We performed a retrospective observational case series of 20 patients who were referred for EBUS guided biopsies of PET positive mediastinal and hilar lymph nodes during the work-up or treatment of suspected malignancy., Results: To be included, all patients received PET imaging as well as an EBUS guided biopsy of FDG avid lymph nodes which demonstrated anthracotic pigment as the only histologic abnormality. The key findings were that 90% of patients in this cohort were born outside of the US, 90% had bilateral FDG avid lymph nodes with an average standardized uptake value (SUV) of 7.9±2.2. Most patients, based on their history, had a likely exposure to biomass fuel or urban pollution., Conclusions: BAL may be an underrecognized cause for PET positive lymph nodes in patients undergoing work-up for malignancy. These findings support the importance of sampling mediastinal and hilar lymph nodes even when SUVs are highly suggestive of malignancy., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://dx.doi.org/10.21037/jtd-21-142). The authors have no conflicts of interest to declare., (2021 Journal of Thoracic Disease. All rights reserved.)

Background: The vast majority of polyomavirus nephropathy (PVN) is due to BK virus, but rare cases result from JC virus reactivation. To date, only a handful of biopsy-proven JC-PVN cases have been reported. Here, we describe the clinical and pathologic findings in 7 patients with biopsy-proven JC-PVN., Methods: Search of the pathology archives at 2 institutions found 7 cases of JC-PVN. Clinical data were extracted from the electronic medical records, and the biopsies were reviewed., Results: Four cases were diagnosed at 6 y posttransplant or later. The remaining 3 cases presented within approximately 2 y posttransplant, of which 2 showed subclinical JC-PVN on surveillance biopsy. Two early presenting patients were treated for acute rejection just before acquiring JC-PVN. Late presenting patients had higher chronicity, which correlated to worse outcome. All but 1 biopsy showed nonspecific inflammation within areas of interstitial fibrosis without significant inflammation in unscarred cortex. The earliest presenting patient was the exception and showed active inflammation with tubulitis. Viral cytopathic changes were detected in all cases with moderate or high-histologic viral load (pvl), showing preference for the distal tubules and medulla. The 2 cases with low pvl did not demonstrate cytopathic changes but were SV40 positive., Conclusions: JC-PVN can be insidious in presentation, which may cause delayed or missed diagnosis. Unlike BK-PVN, which typically occurs early in the posttransplant period, JC-PVN can occur both early and late following transplant. Overreliance on negative plasma and urine BK viral loads to exclude PVN can be a pitfall., Competing Interests: The authors declare no funding or conflicts of interest., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Interstitial fibrosis, tubular atrophy (IFTA), and glomerulosclerosis are indicators of irrecoverable kidney injury. Modern machine learning (ML) tools have enabled robust, automated identification of image structures that can be comparable with analysis by human experts. ML algorithms were developed and tested for the ability to replicate the detection and quantification of IFTA and glomerulosclerosis that renal pathologists perform., Methods: A renal pathologist annotated renal biopsy specimens from 116 whole-slide images (WSIs) for IFTA and glomerulosclerosis. A total of 79 WSIs were used for training different configurations of a convolutional neural network (CNN), and 17 and 20 WSIs were used as internal and external testing cases, respectively. The best model was compared against the input of four renal pathologists on 20 new testing slides. Further, for 87 testing biopsy specimens, IFTA and glomerulosclerosis measurements made by pathologists and the CNN were correlated to patient outcome using classic statistical tools., Results: The best average performance across all image classes came from a DeepLab version 2 network trained at 40× magnification. IFTA and glomerulosclerosis percentages derived from this CNN achieved high levels of agreement with four renal pathologists. The pathologist- and CNN-based analyses of IFTA and glomerulosclerosis showed statistically significant and equivalent correlation with all patient-outcome variables., Conclusions: ML algorithms can be trained to replicate the IFTA and glomerulosclerosis assessment performed by renal pathologists. This suggests computational methods may be able to provide a standardized approach to evaluate the extent of chronic kidney injury in situations in which renal-pathologist time is restricted or unavailable., (Copyright © 2021 by the American Society of Nephrology.)

Histologic examination of interstitial fibrosis and tubular atrophy (IFTA) is critical to determine the extent of irreversible kidney injury in renal disease. The current clinical standard involves pathologist's visual assessment of IFTA, which is prone to inter-observer variability. To address this diagnostic variability, we designed two case studies (CSs), including seven pathologists, using HistomicsTK- a distributed system developed by Kitware Inc. (Clifton Park, NY). Twenty-five whole slide images (WSIs) were classified into a training set of 21 and a validation set of four. The training set was composed of seven unique subsets, each provided to an individual pathologist along with four common WSIs from the validation set. In CS 1, all pathologists individually annotated IFTA in their respective slides. These annotations were then used to train a deep learning algorithm to computationally segment IFTA. In CS 2, manual and computational annotations from CS 1 were first reviewed by the annotators to improve concordance of IFTA annotation. Both the manual and computational annotation processes were then repeated as in CS1. The inter-observer concordance in the validation set was measured by Krippendorff's alpha (KA). The KA for the seven pathologists in CS1 was 0.62 with CI [0.57, 0.67], and after reviewing each other's annotations in CS2, 0.66 with CI [0.60, 0.72]. The respective CS1 and CS2 KA were 0.58 with CI [0.52, 0.64] and 0.63 with CI [0.56, 0.69] when including the deep learner as an eighth annotator. These results suggest that our designed annotation framework refines agreement of spatial annotation of IFTA and demonstrates a human-AI approach to significantly improve the development of computational models.

Background: Pathologists use visual classification of glomerular lesions to assess samples from patients with diabetic nephropathy (DN). The results may vary among pathologists. Digital algorithms may reduce this variability and provide more consistent image structure interpretation., Methods: We developed a digital pipeline to classify renal biopsies from patients with DN. We combined traditional image analysis with modern machine learning to efficiently capture important structures, minimize manual effort and supervision, and enforce biologic prior information onto our model. To computationally quantify glomerular structure despite its complexity, we simplified it to three components consisting of nuclei, capillary lumina and Bowman spaces; and Periodic Acid-Schiff positive structures. We detected glomerular boundaries and nuclei from whole slide images using convolutional neural networks, and the remaining glomerular structures using an unsupervised technique developed expressly for this purpose. We defined a set of digital features which quantify the structural progression of DN, and a recurrent network architecture which processes these features into a classification., Results: Our digital classification agreed with a senior pathologist whose classifications were used as ground truth with moderate Cohen's kappa κ = 0.55 and 95% confidence interval [0.50, 0.60]. Two other renal pathologists agreed with the digital classification with κ 1 = 0.68, 95% interval [0.50, 0.86] and κ 2 = 0.48, 95% interval [0.32, 0.64]. Our results suggest computational approaches are comparable to human visual classification methods, and can offer improved precision in clinical decision workflows. We detected glomerular boundaries from whole slide images with 0.93±0.04 balanced accuracy, glomerular nuclei with 0.94 sensitivity and 0.93 specificity, and glomerular structural components with 0.95 sensitivity and 0.99 specificity., Conclusions: Computationally derived, histologic image features hold significant diagnostic information that may augment clinical diagnostics., (Copyright © 2019 by the American Society of Nephrology.)

At some tertiary breast care centers, where many patients are referred from other institutions, it is routine to repeat testing for estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2/neu) in excision specimens if these tests were performed on the preceding biopsy at the referring facility. The goal of this study is to assess the value of this practice. We documented results from ER, PR, and HER2 testing in 541 consecutive invasive breast cancers excised over a 2.5-year period and analyzed the subset (n=153) for which testing was performed on the excision specimen solely due to the fact that testing on the preceding biopsy was performed at an outside institution. The rates and directions of biopsy-to-excision change were as follows: ER [1.3% (2/153), 100% from (+) to (-)]; PR [4% (6/153), 83% from (+) to (-)]; HER2/neu assessed by immunohistochemistry [21% (29/137)]; HER2/neu assessed by fluorescence in situ hybridization [3.3% (2/61); 50% from amplified to nonamplified and 50% vice versa]. There were no ER(-) and PR(-) biopsy cases that became ER and/or PR(+) in the excision. By coordinate analysis for the hormone receptors [ie, ER and/or PR(+) being indicative of "hormone receptor" (HR) positivity], there were no cases that changed from HR(+) in the biopsy to HR(-) in the excision (or vice versa), which suggests that repeat testing for ER and PR in this setting is of limited value. In an analysis that incorporated both immunohistochemistry and in situ fluorescence hybridization results, there were 2 cases with a clinically significant biopsy-to-excision change in HER2/neu status in which that change was detected primarily because the excision was retested. These findings provide baseline data for formulating policies on whether repeat testing should routinely be performed in the described scenario.

Purpose: Checkpoint inhibitors demonstrate salutary anticancer effects, including long-term remissions. PD-L1 expression/amplification, high mutational burden, and mismatch repair deficiency correlate with response. We have, however, observed a subset of patients who appear to be "hyperprogressors," with a greatly accelerated rate of tumor growth and clinical deterioration compared with pretherapy, which was also recently reported by Institut Gustave Roussy. The current study investigated potential genomic markers associated with "hyperprogression" after immunotherapy. Experimental Design: Consecutive stage IV cancer patients who received immunotherapies (CTLA-4, PD-1/PD-L1 inhibitors or other [investigational] agents) and had their tumor evaluated by next-generation sequencing were analyzed ( N = 155). We defined hyperprogression as time-to-treatment failure (TTF) <2 months, >50% increase in tumor burden compared with preimmunotherapy imaging, and >2-fold increase in progression pace. Results: Amongst 155 patients, TTF <2 months was seen in all six individuals with MDM2/MDM4 amplification. After anti-PD1/PDL1 monotherapy, four of these patients showed remarkable increases in existing tumor size (55% to 258%), new large masses, and significantly accelerated progression pace (2.3-, 7.1-, 7.2- and 42.3-fold compared with the 2 months before immunotherapy). In multivariate analysis, MDM2/MDM4 and EGFR alterations correlated with TTF <2 months. Two of 10 patients with EGFR alterations were also hyperprogressors (53.6% and 125% increase in tumor size; 35.7- and 41.7-fold increase). Conclusions: Some patients with MDM2 family amplification or EGFR aberrations had poor clinical outcome and significantly increased rate of tumor growth after single-agent checkpoint (PD-1/PD-L1) inhibitors. Genomic profiles may help to identify patients at risk for hyperprogression on immunotherapy. Further investigation is urgently needed. Clin Cancer Res; 23(15); 4242-50. ©2017 AACR ., (©2017 American Association for Cancer Research.)