The peritoneal histology of 224 peritoneal dialysis (PD) patients without sclerosing peritonitis (SP) and of 39 PD patients with SP was evaluated. Of the 224 patients, 180 showed simple sclerosis (SS). In these subjects, slight thickness of sclerosis (10 – 70 μm), slight parvicellular infiltration (5/180), slight arterial thickening with no vessel occlusion (19/180), and slight tissue calcification (1/180) were observed. In the 39 patients with SP, striking histological changes versus SS were detected: thickness of sclerosis 250 – 4000 μm, p < 0.01; inflammation 39/39, p < 0.01 (parvicellular infiltration 36/39, p < 0.01; microabscesses 15/39, p < 0.05; giant cells 38/39, p < 0.01; granulation tissue 38/39, p < 0.01); arterial alterations 39/39, p < 0.01 (thickening 39/39, p < 0.01; occlusion 39/39, p < 0.01; calcification 26/39, p < 0.01; ossification 9/39, p < 0.01); tissue calcification 12/39, p < 0.01 (with ossification 4/39, with bone marrow 2/39). The thickness of sclerosis in SS was higher in parietal (30 – 70 μm) than in visceral peritoneum (10 – 40 μm, p < 0.05); in SP it was higher in visceral (600 – 4000 μm) than in parietal peritoneum (250 – 2000 μm, p < 0.05). These striking differences suggest consideration of SS and SP as two separate nosological entities. Differences in frequency, animal models, etiology, and clinical impact seem to confirm this hypothesis, showing that SP is not just the evolution of SS.

Background: Our study aims to provide an overview of existing evidence regarding the image quality of dual-energy CT (DECT) employing reduced contrast media (CM) volumes, in comparison to single-energy CT (SECT) with standard CM loads. The advantages, indications, and possible applications of DECT were investigated from the perspective of providing better patient care, minimizing CM volume and managing CM shortage. Methods: In this systematic review (PRISMA methodology), PubMed and WOS were searched from January 2010 to January 2023 by two independent reviewers. The scan and CM characteristics, radiation dose, and results of quantitative (contrast to noise ratio, CNR, and signal to noise ratio, SNR) and qualitative assessment of image quality were collected. Sixty non-duplicated records eligible for full-text screening were examined. Results: Finally, 22 articles (1818 patients) were included. The average CM reduction with DECT ranged between 43.4 ± 11%. Despite the wide variability in CT scan protocols, no differences were found in radiation doses between DECT and SECT. Conclusions: DECT scanners allow the employment of lower CM volumes with equal or better image quality evaluated by quantitative and qualitative analyses and similar dose radiation compared to SECT. Using image reconstructions at low monochromatic energy levels, DECT increases iodine conspicuity and attenuation contributing to CM containment measures.

Encapsulating peritoneal sclerosis (EPS) is drawing attention to the PD community because of its unpredictable onset and high mortality.

Deep learning is widely applied in bioinformatics and biomedical imaging, due to its ability to perform various clinical tasks automatically and accurately. In particular, the application of deep learning techniques for the automatic identification of glomeruli in histopathological kidney images can play a fundamental role, offering a valid decision support system tool for the automatic evaluation of the Karpinski metric. This will help clinicians in detecting the presence of sclerotic glomeruli in order to decide whether the kidney is transplantable or not. In this work, we implemented a deep learning framework to identify and segment sclerotic and non-sclerotic glomeruli from scanned Whole Slide Images (WSIs) of human kidney biopsies. The experiments were conducted on a new dataset collected by both the Siena and Trieste hospitals. The images were segmented using the DeepLab V2 model, with a pre-trained ResNet101 encoder, applied to 512 × 512 patches extracted from the original WSIs. The results obtained are promising and show a good performance in the segmentation task and a good generalization capacity, despite the different coloring and typology of the histopathological images. Moreover, we present a novel use of the CD10 staining procedure, which gives promising results when applied to the segmentation of sclerotic glomeruli in kidney tissues.