1,721,350 research outputs found
Chronic viral hepatitis: the histology report.
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In chronic viral hepatitis, the role of liver biopsy as a diagnostic test has seen a decline, paralleled by its increasing importance for prognostic purposes. Nowadays, the main indication for liver biopsy in chronic viral hepatitis is to assess the severity of the disease, in terms of both necro-inflammation (grade) and fibrosis (stage), which is important for prognosis and therapeutic management. Several scoring systems have been proposed for grading and staging chronic viral hepatitis and there is no a general consensus on the best system to be used in the daily practice. All scoring systems have their drawbacks and all may be affected by sampling and observer variability. Whatever the system used, a histological score is a reductive approach since damage in chronic viral hepatitis is a complex biological process. Thus, scoring systems are not intended to replace the detailed, descriptive, pathology report. In fact, lesions other than those scored for grading and staging may have clinical relevance and should be assessed and reported. This paper aims to provide a systematic approach to the interpretation of liver biopsies obtained in cases of chronic viral hepatitis, with the hope of helping general pathologists in their diagnostic practice
Umanizzazione e professione sanitaria. Comunicazione, organizzazione e territorio
No full textIl volume affronta numerosi temi connessi al rapporto paziente-operatore sanitario, fornendo ampie e articolate indicazioni affinché tale rapporto sia sempre più positivo e produttivo di risultati in termini di salute e nel contempo di soddisfazione per i servizi da parte degli utenti e per le prestazioni offerte da parte degli operatori. Nei diversi capitoli vengono riportati aspetti sia teoretici che empirici e sperimentali
Reproducibility and explainability in digital pathology: The need to make black-box artificial intelligence systems more transparent
Full text linkArtificial intelligence (AI), and more specifically Machine Learning (ML) and Deep learning (DL), has permeated the digital pathology field in recent years, with many algorithms successfully applied as new advanced tools to analyze pathological tissues. The introduction of high-resolution scanners in histopathology services has represented a real revolution for pathologists, allowing the analysis of digital whole-slide images (WSI) on a screen without a microscope at hand. However, it means a transition from microscope to algorithms in the absence of specific training for most pathologists involved in clinical practice. The WSI approach represents a major transformation, even from a computational point of view. The multiple ML and DL tools specifically developed for WSI analysis may enhance the diagnostic process in many fields of human pathology. AI-driven models allow the achievement of more consistent results, providing valid support for detecting, from H&E-stained sections, multiple biomarkers, including microsatellite instability, that are missed by expert pathologists
The application of the OsO4 maceration method to the study of human bioptic material. A procedure avoiding freeze-fracture.
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