Implementation of Digital Image Analysis in Assessment of Ki67 Index in Breast Cancer.

IF 1.3 4区 医学 Q3 ANATOMY & MORPHOLOGY
Rachel K Vanderschelden, Jacob A Jerome, Daniel Gonzalez, Lindsey Seigh, Gloria J Carter, Beth Z Clark, Esther Elishaev, Jeffrey Louis Fine, Lakshmi Harinath, Mirka W Jones, Tatiana M Villatoro, Thing Rinda Soong, Jing Yu, Chengquan Zhao, Doug Hartman, Rohit Bhargava
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引用次数: 0

Abstract

The clinical utility of the proliferation marker Ki67 in breast cancer treatment and prognosis is an active area of research. Studies have suggested that differences in pre-analytic and analytic factors contribute to low analytical validity of the assay, with scoring methods accounting for a large proportion of this variability. Use of standard scoring methods is limited, in part due to the time intensive nature of such reporting protocols. Therefore, use of digital image analysis tools may help to both standardize reporting and improve workflow. In this study, digital image analysis was utilized to quantify Ki67 indices in 280 breast biopsy and resection specimens during routine clinical practice. The supervised Ki67 indices were then assessed for agreement with a manual count of 500 tumor cells. Agreement was excellent, with an intraclass correlation coefficient of 0.96 for the pathologist-supervised analysis. This study illustrates an example of a rapid, accurate workflow for implementation of digital image analysis in Ki67 scoring in breast cancer.

数字图像分析在癌症Ki67指数评估中的应用。
增殖标志物Ki67在乳腺癌症治疗和预后中的临床应用是一个活跃的研究领域。研究表明,分析前因素和分析因素的差异导致测定的分析有效性较低,评分方法在这种可变性中占很大比例。标准评分方法的使用受到限制,部分原因是此类报告协议的时间密集性。因此,使用数字图像分析工具可能有助于标准化报告和改进工作流程。在这项研究中,在常规临床实践中,使用数字图像分析来量化280个乳腺活检和切除标本中的Ki67指数。然后评估监督的Ki67指数与手动计数500个肿瘤细胞是否一致。一致性非常好,病理学家监督分析的组内相关系数为0.96。本研究举例说明了在癌症Ki67评分中实现数字图像分析的快速、准确的工作流程。
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来源期刊
Applied Immunohistochemistry & Molecular Morphology
Applied Immunohistochemistry & Molecular Morphology ANATOMY & MORPHOLOGY-MEDICAL LABORATORY TECHNOLOGY
CiteScore
3.20
自引率
0.00%
发文量
153
期刊介绍: ​Applied Immunohistochemistry & Molecular Morphology covers newly developed identification and detection technologies, and their applications in research and diagnosis for the applied immunohistochemist & molecular Morphologist. Official Journal of the International Society for Immunohistochemisty and Molecular Morphology​.
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