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Background: Kidney biopsy is the gold-standard for diagnosing medical renal diseases, but the accuracy of the diagnosis greatly depends on the quality of the biopsy specimen, particularly the amount of renal cortex obtained. Inadequate biopsies, characterized by insufficient cortex or predominant medulla, can lead to inconclusive or incorrect diagnoses, and repeat biopsy. Unfortunately, there has been a concerning increase in the rate of inadequate kidney biopsies, and not all medical centers have access to trained professionals who can assess biopsy adequacy in real time. In response to this challenge, we aimed to develop a machine learning model capable of assessing the percentage cortex of each biopsy pass using smartphone images of the kidney biopsy tissue at the time of biopsy. Methods: 747 kidney biopsy cores and corresponding smartphone macro images were collected from five unused deceased donor kidneys. Each core was imaged, formalin-fixed, sectioned, and stained with Periodic acid-Schiff (PAS) to determine cortex percentage. The fresh unfixed core images were captured using the macro camera on an iPhone 13 Pro. Two experienced renal pathologists independently reviewed the PAS-stained sections to determine the cortex percentage. For the purpose of this study, the biopsies with less than 30% cortex were labeled as inadequate, while those with 30% or more cortex were classified as adequate. The dataset was divided into training (n=643), validation (n=30), and test (n=74) sets. Preprocessing steps involved converting High-Efficiency Image Container iPhone format images to JPEG, normalization, and renal tissue segmentation using a U-Net deep learning model. Subsequently, a classification deep learning model was trained on the renal tissue region of interest and corresponding class label. Results: The deep learning model achieved an accuracy of 85% on the training data. On the independent test dataset, the model exhibited an accuracy of 81%. For inadequate samples in the test dataset, the model showed a sensitivity of 71%, suggesting its capability to identify cases with inadequate cortical representation. The area under the receiver-operating curve (AUC-ROC) on the test dataset was 0.80. Conclusion: We successfully developed and tested a machine learning model for classifying smartphone images of kidney biopsies as either adequate or inadequate, based on the amount of cortex determined by expert renal pathologists. The model's promising results suggest its potential as a smartphone application to assist real-time assessment of kidney biopsy tissue, particularly in settings with limited access to trained personnel. Further refinements and validations are warranted to optimize the model's performance.
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Introduction: Antibrush border antibody disease (ABBA) is an autoimmune tubulointerstitial kidney disease that primarily affects older individuals and results in progressive kidney failure. It is rare with only 20 reported cases. Here, we describe a case series to further define the clinicopathologic spectrum and natural history, and to inform management. Methods: We identified 67 patients with ABBA who underwent kidney biopsy, including 65 native and 2 transplants. Demographics, clinical findings, and laboratory data were obtained. Histopathologic data included light microscopy, immunofluorescence, electron microscopy and immunostaining for LRP2, CUBN, and AMN. Follow-up data, including treatment(s), laboratory values, and outcomes, were available from 51 patients. Results: Patients with ABBA were predominantly male with a median age of 72 years. Median serum creatinine was 2.7 mg/dl, proteinuria was 2.8 g/day, and hematuria was present in two-thirds of the patients. Tubular injury with LRP2-positive tubular basement membrane (TBM) deposits were seen in 94.2% of patients. Thirty-eight patients (56.7%) had a second kidney disease, commonly glomerular diseases with high-grade proteinuria. These diseases included podocytopathies, membranous nephropathy (MN), IgA nephropathy, diabetic glomerulopathy, lupus nephritis (LN), crescentic glomerulonephritis (GN), tubulointerstitial nephritis, and involvement by lymphoma. The majority of patients were treated with immunosuppression. Of those patients with follow-up, 29.4% achieved remission, 70.6% had no response, and 52.8% required dialysis or were deceased. Untreated patients were at the highest risk. Conclusion: ABBA is a rare autoimmune kidney disease that often occurs with other kidney diseases. Although the overall prognosis of ABBA is poor, there is potential benefit from immunosuppression.
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The escalating incidence of kidney biopsies providing insufficient tissue for diagnosis poses a dual challenge, straining the healthcare system and jeopardizing patients who may require rebiopsy or face the prospect of an inaccurate diagnosis due to an unsampled disease. Here, we introduce a web-based tool that can provide real-time, quantitative assessment of kidney biopsy adequacy directly from photographs taken with a smartphone camera. The software tool was developed using a deep learning-driven automated segmentation technique, trained on a dataset comprising nephropathologist-confirmed annotations of the kidney cortex on digital biopsy images. Our framework demonstrated favorable performance in segmenting the cortex via 5-fold cross-validation (Dice coefficient: 0.788±0.130) (n=100). Offering a bedside tool for kidney biopsy adequacy assessment has the potential to provide real-time guidance to the physicians performing medical kidney biopsies, reducing the necessity for re-biopsies. Our tool can be accessed through our web-based platform: http://www.biopsyadequacy.org.
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BACKGROUND AND AIMS: No endoscopic scoring system has been established for immune-mediated colitis (IMC). This study aimed to establish such a system for IMC and explore its utility in guiding future selective immunosuppressive therapy (SIT) use compared to clinical symptoms. METHODS: This retrospective, international, 14-center study included 674 patients who developed IMC after immunotherapy and underwent endoscopic evaluation. Ten endoscopic features were selected by group consensus and assigned 1 point each to calculate an IMC endoscopic score (IMCES). IMCES cutoffs were chosen to maximize specificity for SIT use. This specificity was compared between IMCESs, and clinical symptoms were graded according to a standardized instrument. RESULTS: A total of 309 (45.8%) patients received SIT. IMCES specificity for SIT use was 82.8% with a cutoff of 4. The inclusion of ulceration as a mandatory criterion resulted in higher specificity (85.0% for a cutoff of 4). In comparison, the specificity of a Mayo endoscopic subscore of 3 was 74.6%, and the specificity of clinical symptom grading was much lower at 27.4% and 12.3%, respectively. Early endoscopy was associated with timely SIT use (P < .001; r = 0.4084). CONCLUSIONS: This is the largest multicenter study to devise an endoscopic scoring system to guide IMC management. An IMCES cutoff of 4 has a higher specificity for SIT use than clinical symptoms, supporting early endoscopic evaluation for IMC.
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Colitis , Colonoscopía , Índice de Severidad de la Enfermedad , Humanos , Estudios Retrospectivos , Masculino , Femenino , Persona de Mediana Edad , Adulto , Colitis/patología , Colonoscopía/métodos , Inmunosupresores/uso terapéutico , Anciano , Inmunoterapia/métodos , Sensibilidad y Especificidad , Úlcera/patologíaRESUMEN
RACIONAL: A doença celíaca é afecção inflamatória do intestino delgado associada à intolerância permanente ao glúten, que ocorre em indivíduos geneticamente susceptíveis. OBJETIVO: Conhecer as características clínicas e epidemiológicas dessa doença em nosso meio. MÉTODO: Tratou-se de estudo descritivo transversal com amostra não-probabilística selecionada entre os membros da Associação dos Celíacos do Brasil - Regional de Santa Catarina, aos quais foi enviado questionário abrangendo diversos aspectos da doença. RESULTADOS: Dos 506 associados, 145 (28,7 por cento) foram incluídos no estudo - todos celíacos confirmados por biopsia. Suas idades variaram entre 3,3 e 82,5 anos (média de 30,8 anos). A maioria era do sexo feminino (proporção de 2 mulheres para 1 homem). A idade média ao diagnóstico foi de 16 anos para os homens e 26,7 para as mulheres. Os principais sintomas relatados foram distensão abdominal (71,8 por cento), dor abdominal (71 por cento) e diarréia (65,5 por cento). No sexo masculino, predominaram diarréia e déficit ponderal enquanto que no sexo feminino aftas, constipação e anemia. Apenas 42,1 por cento dos associados foram submetidos a biopsia em momento compatível com o diagnóstico correto de doença celíaca (44,2 por cento relataram biopsia somente em vigência de dieta já isenta de glúten e 11,7 por cento não souberam informar). Quanto aos testes sorológicos, 61,4 por cento realizaram pelo menos um teste. Doenças associadas ou complicações foram relatadas por 65,5 por cento; dessas, a mais freqüente foi a intolerância à lactose (33 por cento). Suplementação vitamínica ou mineral foi indicada em 45 por cento dos casos e 35,2 por cento foram submetidos a densitometria óssea. Desses, 59 por cento relataram um resultado alterado (osteopenia ou osteoporose). CONCLUSÕES: Os resultados apontam para uma tendência de diagnóstico da doença celíaca em idades mais avançadas em nosso meio, especialmente entre as mulheres, e sugerem...
BACKGROUND: Celiac disease is an enteropathy induced by gluten in genetically predisposed individuals. AIM: To establish the demographic and clinical characteristics of this disease in Santa Catarina State, Brazil. METHODS: A descriptive transversal study was performed involving members of a regional celiac association, to whom a questionnaire focusing various aspects of the disease was sent. RESULTS: From a total of 506 members, 145 (28.7 percent) were enrolled in the study - all of them biopsy-proven celiacs. Their mean age was 30.8 years (range, 3.3-82.5 years). Female to male rate was 2.1:1. The mean age at diagnosis was 16 years for men and 26.7 years for women. Most frequently reported symptoms were: abdominal distention (71.8 percent), abdominal pain (71 percent) and diarrhea (65.5 percent). Anemia, aphthous ulcers and constipation were more related by women, while diarrhea and low weight were more frequent in men. Only 42.1 percent of the participants had been submitted to biopsies compatible with a correct investigation of the disease (44.2 percent had been submitted to biopsy only after gluten exclusion of the diet and 11.7 percent did not mentioned whether they were in a gluten-free diet when biopsied). Only 61.4 percent had been submitted to serological tests for diagnostic or dietary control purposes. Associated diseases were related by 65 percent of the individuals, of which the most common was lactose intolerance (33 percent). Vitaminic or mineral supplementation was indicated to 45 percent and only 32.5 percent have had bone mineral density measured. Of these, 59 percent had altered results. CONCLUSIONS: The results suggest a tendency of diagnosis of celiac disease in older ages, specially among women. This may indicate the necessity of improving public and medical knowledge in Santa Catarina concerning the diagnosis and treatment of this disease.