Kawazoe Yoshimasa, Shimamoto Kiminori, Yamaguchi Ryohei, Nakamura Issei, Yoneda Kota, Shinohara Emiko, Shintani-Domoto Yukako, Ushiku Tetsuo, Tsukamoto Tatsuo, Ohe Kazuhiko
Artificial Intelligence in Healthcare, Graduate School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo 113-0033, Japan.
Ohshima Memorial Kisen Hospital, 3-5-15, Misaki, Chiba 274-0812, Japan.
Diagnostics (Basel). 2022 Nov 25;12(12):2955. doi: 10.3390/diagnostics12122955.
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.
肾活检全切片图像（WSIs）中肾小球的组织病理学发现对肾脏疾病的诊断和分级起着重要作用。本研究旨在开发一种自动化计算流程，以检测肾小球并分割WSIs中肾小球内部的组织病理学区域。为了评估该流程的意义，我们进行了多变量回归分析，以确定在46例免疫球蛋白A肾病（IgAN）病例中，量化区域是否与肾功能预后相关。所开发的流程针对其机构的WSIs，五类（即背景、鲍曼间隙、肾小球丛、新月体和硬化区域）的平均交并比（IoU）分别为0.670和0.693，针对外部机构的WSIs，平均交并比分别为0.678和0.609。多变量分析显示，预测的硬化区域，即使是由外部模型预测的区域，对活检后估计肾小球滤过率的斜率也有显著负面影响。这是第一项证明通过自动化计算流程预测的、用于分割WSIs中组织病理学肾小球成分的量化硬化区域会影响IgAN患者肾功能预后的研究。
