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一种用于免疫组化图像中平均抗体染色的稳健自动测量方法。

A robust automated measure of average antibody staining in immunohistochemistry images.

机构信息

Department of Statistics, University College Cork, Cork, Ireland.

出版信息

J Histochem Cytochem. 2010 Feb;58(2):95-107. doi: 10.1369/jhc.2009.953554.

Abstract

Identifying and scoring cancer markers plays a key role in oncology, helping to characterize the tumor and predict the clinical course of the disease. The current method for scoring immunohistochemistry (IHC) slides is labor intensive and has inherent issues of quantitation. Although multiple attempts have been made to automate IHC scoring in the past decade, a major limitation in these efforts has been the setting of the threshold for positive staining. In this report, we propose the use of an averaged threshold measure (ATM) score that allows for automatic threshold setting. The ATM is a single multiplicative measure that includes both the proportion and intensity scores. It can be readily automated to allow for large-scale processing, and it is applicable in situations in which individual cells are hard to distinguish. The ATM scoring method was validated by applying it to simulated images, to a sequence of images from the same tumor, and to tumors from different patient biopsies that showed a broad range of staining patterns. Comparison between the ATM score and manual scoring by an expert pathologist showed that both methods resulted in essentially identical scores when applied to these patient biopsies. This manuscript contains online supplemental material at http://www.jhc.org. Please visit this article online to view these materials.

摘要

鉴定和评分癌症标志物在肿瘤学中起着关键作用,有助于描述肿瘤并预测疾病的临床过程。目前,对免疫组织化学(IHC)切片进行评分的方法既费力又存在定量问题。尽管在过去十年中多次尝试对 IHC 评分进行自动化,但这些努力的一个主要限制是阳性染色的阈值设置。在本报告中,我们提出使用平均阈值测量(ATM)评分来进行自动阈值设置。ATM 是一个单一的乘法度量标准,包括比例和强度评分。它可以很容易地实现自动化,以便进行大规模处理,并且适用于难以区分单个细胞的情况。ATM 评分方法通过应用于模拟图像、来自同一肿瘤的一系列图像以及来自不同患者活检的肿瘤进行了验证,这些肿瘤显示出广泛的染色模式。ATM 评分与专家病理学家的手动评分之间的比较表明,当应用于这些患者活检时,这两种方法的评分基本相同。本文包含在线补充材料,可在 http://www.jhc.org 上查看。请在线访问本文以查看这些材料。

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