Department of Medicine and Surgery, Pathology, IRCCS Fondazione San Gerardo dei Tintori, University of Milano-Bicocca, Italy.
Department of Medical Surgical Sciences and Biotechnologies, Sapienza University of Rome, Rome, Italy.
Pathologica. 2024 Apr;116(2):104-118. doi: 10.32074/1591-951X-990.
Kidneys are often targets of systemic vasculitis (SVs), being affected in many different forms and representing a possible sentinel of an underlying multi-organ condition. Renal biopsy still remains the gold standard for the identification, characterization and classification of these diseases, solving complex differential diagnosis thanks to the combined application of light microscopy (LM), immunofluorescence (IF) and electron microscopy (EM). Due to the progressively increasing complexity of renal vasculitis classification systems (e.g. pauci-immune vs immune complex related forms), a clinico-pathological approach is mandatory and adequate technical and interpretative expertise in nephropathology is required to ensure the best standard of care for our patients. In this complex background, the present review aims at summarising the current knowledge and challenges in the world of renal vasculitis, unveiling the potential role of the introduction of digital pathology in this setting, from the creation of hub-spoke networks to the future application of artificial intelligence (AI) tools to aid in the diagnostic and scoring/classification process.
肾脏通常是系统性血管炎(SVs)的靶器官,以多种不同形式受到影响,并可能成为潜在的多器官疾病的预警信号。肾脏活检仍然是确定、描述和分类这些疾病的金标准,通过结合应用光学显微镜(LM)、免疫荧光(IF)和电子显微镜(EM),解决复杂的鉴别诊断问题。由于肾脏血管炎分类系统的复杂性不断增加(例如,寡免疫与免疫复合物相关形式),必须采用临床病理方法,并且需要在肾脏病学方面具备足够的技术和解释专业知识,以确保为我们的患者提供最佳的护理标准。在这一复杂背景下,本综述旨在总结肾脏血管炎领域的现有知识和挑战,揭示数字病理学在这一领域的潜在作用,从创建中心辐射网络到未来应用人工智能(AI)工具来辅助诊断和评分/分类过程。