III. Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Institute of Medical Systems Biology, Center for Biomedical AI (bAIome), Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
JCI Insight. 2021 Apr 8;6(7):144779. doi: 10.1172/jci.insight.144779.
Morphologic examination of tissue biopsies is essential for histopathological diagnosis. However, accurate and scalable cellular quantification in human samples remains challenging. Here, we present a deep learning-based approach for antigen-specific cellular morphometrics in human kidney biopsies, which combines indirect immunofluorescence imaging with U-Net-based architectures for image-to-image translation and dual segmentation tasks, achieving human-level accuracy. In the kidney, podocyte loss represents a hallmark of glomerular injury and can be estimated in diagnostic biopsies. Thus, we profiled over 27,000 podocytes from 110 human samples, including patients with antineutrophil cytoplasmic antibody-associated glomerulonephritis (ANCA-GN), an immune-mediated disease with aggressive glomerular damage and irreversible loss of kidney function. We identified previously unknown morphometric signatures of podocyte depletion in patients with ANCA-GN, which allowed patient classification and, in combination with routine clinical tools, showed potential for risk stratification. Our approach enables robust and scalable molecular morphometric analysis of human tissues, yielding deeper biological insights into the human kidney pathophysiology.
组织活检的形态学检查对于组织病理学诊断至关重要。然而，在人体样本中进行准确且可扩展的细胞定量仍然具有挑战性。在这里，我们提出了一种基于深度学习的人类肾脏活检中抗原特异性细胞形态计量学方法，它将间接免疫荧光成像与基于 U-Net 的架构相结合，用于图像到图像的转换和双重分割任务，实现了人类水平的准确性。在肾脏中，足细胞丢失是肾小球损伤的标志，可以在诊断性活检中进行估计。因此，我们对来自 110 个样本的超过 27000 个足细胞进行了分析，其中包括抗中性粒细胞胞质抗体相关性肾小球肾炎 (ANCA-GN) 患者，这是一种免疫介导的疾病，具有侵袭性的肾小球损伤和肾功能不可逆转的丧失。我们在 ANCA-GN 患者中发现了以前未知的足细胞耗竭的形态计量学特征，这些特征允许对患者进行分类，并与常规临床工具相结合，显示出分层风险的潜力。我们的方法能够对人体组织进行稳健且可扩展的分子形态计量学分析，为人类肾脏病理生理学提供更深入的生物学见解。
