Abstract：
The histopathological findings of the glomeruli from whole slide images (WSIs) of a renal biopsy play an important role in diagnosing and grading kidney disease. This study aimed to develop an automated computational pipeline to detect glomeruli and to segment the histopathological regions inside of the glomerulus in a WSI. In order to assess the significance of this pipeline, we conducted a multivariate regression analysis to determine whether the quantified regions were associated with the prognosis of kidney function in 46 cases of immunoglobulin A nephropathy (IgAN). The developed pipelines showed a mean intersection over union (IoU) of 0.670 and 0.693 for five classes (i.e., background, Bowman\'s space, glomerular tuft, crescentic, and sclerotic regions) against the WSI of its facility, and 0.678 and 0.609 against the WSI of the external facility. The multivariate analysis revealed that the predicted sclerotic regions, even those that were predicted by the external model, had a significant negative impact on the slope of the estimated glomerular filtration rate after biopsy. This is the first study to demonstrate that the quantified sclerotic regions that are predicted by an automated computational pipeline for the segmentation of the histopathological glomerular components on WSIs impact the prognosis of kidney function in patients with IgAN.
摘要：
来自肾脏活检的整个幻灯片图像（WSI）的肾小球的组织病理学发现在肾脏疾病的诊断和分级中起着重要作用。这项研究旨在开发一种自动计算管道来检测肾小球并分割WSI中肾小球内部的组织病理学区域。为了评估这条管道的重要性，在46例免疫球蛋白A肾病(IgAN)患者中,我们进行了多变量回归分析,以确定定量区域是否与肾功能预后相关.开发的管道显示五个类别的联合平均交集(IoU)为0.670和0.693(即，背景,鲍曼的空间，肾小球簇绒，月牙形,和硬化区域)对抗其设施的WSI，对外部设施的WSI和0.678和0.609。多变量分析显示，预测的硬化区域，即使是那些由外部模型预测的，对活检后估计的肾小球滤过率的斜率有显著的负面影响。这是第一项研究，证明通过自动计算管道预测的定量硬化区域，用于WSI上组织病理学肾小球成分的分割会影响IgAN患者肾功能的预后。
