Nephron number may be an important determinant of kidney health but has been difficult to study in living humans. We evaluated 1638 living kidney donors at Mayo Clinic (MN and AZ sites) and Cleveland Clinic. We obtained cortical volumes of both kidneys from predonation computed tomography scans. At the time of kidney transplant, we obtained and analyzed the sections of a biopsy specimen of the cortex to determine the density of both nonsclerotic and globally sclerotic glomeruli; the total number of glomeruli was estimated from cortical volume×glomerular density. Donors 18-29 years old had a mean 990,661 nonsclerotic glomeruli and 16,614 globally sclerotic glomeruli per kidney, which progressively decreased to 520,410 nonsclerotic glomeruli per kidney and increased to 141,714 globally sclerotic glomeruli per kidney in donors 70-75 years old. Between the youngest and oldest age groups, the number of nonsclerotic glomeruli decreased by 48%, whereas cortical volume decreased by only 16% and the proportion of globally sclerotic glomeruli on biopsy increased by only 15%. Clinical characteristics that independently associated with fewer nonsclerotic glomeruli were older age, shorter height, family history of ESRD, higher serum uric acid level, and lower measured GFR. The incomplete representation of nephron loss with aging by either increased glomerulosclerosis or by cortical volume decline is consistent with atrophy and reabsorption of globally sclerotic glomeruli and hypertrophy of remaining nephrons. In conclusion, lower nephron number in healthy adults associates with characteristics reflective of both lower nephron endowment at birth and subsequent loss of nephrons.

BACKGROUND The glomerular filtration rate (GFR) assesses the function of all nephrons, and the single-nephron GFR assesses the function of individual nephrons. How the single-nephron GFR relates to demographic and clinical characteristics and kidney-biopsy findings in humans is unknown. METHODS We identified 1388 living kidney donors at the Mayo Clinic and the Cleveland Clinic who underwent a computed tomographic (CT) scan of the kidney with the use of contrast material and an iothalamate-based measurement of the GFR during donor evaluation and who underwent a kidney biopsy at donation. The mean single-nephron GFR was calculated as the GFR divided by the number of nephrons (calculated as the cortical volume of both kidneys as assessed on CT times the biopsy-determined glomerular density). Demographic and clinical characteristics and biopsy findings were correlated with the single-nephron GFR. RESULTS A total of 58% of the donors were women, and the mean (±SD) age of the donors was 44±12 years. The mean GFR was 115±24 ml per minute, the mean number of nephrons was 860,000±370,000 per kidney, and the mean single-nephron GFR was 80±40 nl per minute. The single-nephron GFR did not vary significantly according to age (among donors <70 years of age), sex, or height (among donors ≤190 cm tall). A higher single-nephron GFR was independently associated with larger nephrons on biopsy and more glomerulosclerosis and arteriosclerosis than would be expected for age. A higher single-nephron GFR was associated with a height of more than 190 cm, obesity, and a family history of end-stage renal disease. CONCLUSIONS Among healthy adult kidney donors, the single-nephron GFR was fairly constant with regard to age, sex, and height (if ≤190 cm). A higher single-nephron GFR was associated with certain risk factors for chronic kidney disease and certain kidney-biopsy findings. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases.)

BackgroundThe development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolutional neural network for multiclass segmentation of digitized kidney tissue sections stained with periodic acid–Schiff (PAS).MethodsWe trained the network using multiclass annotations from 40 whole-slide images of stained kidney transplant biopsies and applied it to four independent data sets. We assessed multiclass segmentation performance by calculating Dice coefficients for ten tissue classes on ten transplant biopsies from the Radboud University Medical Center in Nijmegen, The Netherlands, and on ten transplant biopsies from an external center for validation. We also fully segmented 15 nephrectomy samples and calculated the network’s glomerular detection rates and compared network-based measures with visually scored histologic components (Banff classification) in 82 kidney transplant biopsies.ResultsThe weighted mean Dice coefficients of all classes were 0.80 and 0.84 in ten kidney transplant biopsies from the Radboud center and the external center, respectively. The best segmented class was “glomeruli” in both data sets (Dice coefficients, 0.95 and 0.94, respectively), followed by “tubuli combined” and “interstitium.” The network detected 92.7% of all glomeruli in nephrectomy samples, with 10.4% false positives. In whole transplant biopsies, the mean intraclass correlation coefficient for glomerular counting performed by pathologists versus the network was 0.94. We found significant correlations between visually scored histologic components and network-based measures.ConclusionsThis study presents the first convolutional neural network for multiclass segmentation of PAS-stained nephrectomy samples and transplant biopsies. Our network may have utility for quantitative studies involving kidney histopathology across centers and provide opportunities for deep learning applications in routine diagnostics.

IgG4-related disease (IgG4-RD) is a systemic immune-mediated disease that typically manifests as fibro-inflammatory masses that can affect nearly any organ system. Renal involvement by IgG4-RD usually takes the form of IgG4-related tubulointerstitial nephritis, but cases of membranous glomerulonephritis (MGN) have also been described. Here we present a series of 9 patients (mean age at diagnosis 58 years) with MGN associated with IgG4-RD. All patients showed MGN on biopsy, presented with proteinuria (mean 8.3 g/day), and most had elevated serum creatinine (mean 2.2 mg/dl). Seven patients had known extrarenal involvement by IgG4-RD, with 5 patients having concurrent IgG4-related tubulointerstitial nephritis. Immunohistochemical analysis for the phospholipase A2 receptor, a marker of primary MGN, was negative in all 8 biopsies so examined. Six of 7 patients with available follow-up (mean 39 months) were treated with immunosuppressive agents; one untreated patient developed end-stage renal disease and underwent transplantation, without recurrence at 12 years after transplant. All 6 treated patients showed decreased proteinuria (mean 1.2 g/day), and most showed decreased serum creatinine (mean 1.4 mg/dl). Thus, MGN should be included in the spectrum of IgG4-RD and should be suspected in proteinuric IgG4-RD patients. Conversely, patients with MGN and an appropriate clinical history should be evaluated for IgG4-RD.

Granulomatous inflammation is a histologic pattern of tissue reaction which appears following cell injury. Granulomatous inflammation is caused by a variety of conditions including infection, autoimmune, toxic, allergic, drug, and neoplastic conditions. The tissue reaction pattern narrows the pathologic and clinical differential diagnosis and subsequent clinical management. Common reaction patterns include necrotizing granulomas, non necrotizing granulomas, suppurative granulomas, diffuse granulomatous inflammation, and foreign body giant cell reaction. Prototypical examples of necrotizing granulomas are seen with mycobacterial infections and non-necrotizing granulomas with sarcoidosis. However, broad differential diagnoses exist within each category. Using a pattern based algorithmic approach, identification of the etiology becomes apparent when taken with clinical context.The pulmonary system is one of the most commonly affected sites to encounter granulomatous inflammation. Infectious causes of granuloma are most prevalent with mycobacteria and dimorphic fungi leading the differential diagnoses. Unlike the lung, skin can be affected by several routes, including direct inoculation, endogenous sources, and hematogenous spread. This broad basis of involvement introduces a variety of infectious agents, which can present as necrotizing or non-necrotizing granulomatous inflammation. Non-infectious etiologies require a thorough clinicopathologic review to narrow the scope of the pathogenesis which include: foreign body reaction, autoimmune, neoplastic, and drug related etiologies. Granulomatous inflammation of the kidney, often referred to as granulomatous interstitial nephritis (GIN) is unlike organ systems such as the skin or lungs. The differential diagnosis of GIN is more frequently due to drugs and sarcoidosis as compared to infections (fungal and mycobacterial).Herein we discuss the pathogenesis and histologic patterns seen in a variety of organ systems and clinical conditions.

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Renal pathologists and nephrologists met on February 20, 2015 to establish an etiology/pathogenesis-based system for classification and diagnosis of GN, with a major aim of standardizing the kidney biopsy report of GN. On the basis of etiology/pathogenesis, GN is classified into the following five pathogenic types, each with specific disease entities: immune-complex GN, pauci-immune GN, antiglomerular basement membrane GN, monoclonal Ig GN, and C3 glomerulopathy. The pathogenesis-based classification forms the basis of the kidney biopsy report. To standardize the report, the diagnosis consists of a primary diagnosis and a secondary diagnosis. The primary diagnosis should include the disease entity/pathogenic type (if disease entity is not known) followed in order by pattern of injury (mixed patterns may be present); score/grade/class for disease entities, such as IgA nephropathy, lupus nephritis, and ANCA GN; and additional features as detailed herein. A pattern diagnosis as the sole primary diagnosis is not recommended. Secondary diagnoses should be reported separately and include coexisting lesions that do not form the primary diagnosis. Guidelines for the report format, light microscopy, immunofluorescence microscopy, electron microscopy, and ancillary studies are also provided. In summary, this consensus report emphasizes a pathogenesis-based classification of GN and provides guidelines for the standardized reporting of GN.