Department of Pathology, Erasme's Hospital, Université Libre de Bruxelles, Brussels, Belgium.
Curepath laboratory, CHU Tivoli and CHIREC institute, Jumet, Belgium.
Technol Cancer Res Treat. 2023 Jan-Dec;22:15330338231169603. doi: 10.1177/15330338231169603.
In the era of "precision medicine," the availability of high-quality tumor biomarker tests is critical and tumor proliferation evaluated by Ki-67 antibody is one of the most important prognostic factors in breast cancer. But the evaluation of Ki-67 index has been shown to suffer from some interobserver variability. The goal of the study is to develop an easy, automated, and reliable Ki-67 assessment approach for invasive breast carcinoma in routine practice.
A total of 151 biopsies of invasive breast carcinoma were analyzed. The Ki-67 index was evaluated by 2 pathologists with MIB-1 antibody as a global tumor index and also in a hotspot. These 2 areas were also analyzed by digital image analysis (DIA).
For Ki-67 index assessment, in the global and hotspot tumor area, the concordances were very good between DIA and pathologists when DIA focused on the annotations made by pathologist (0.73 and 0.83, respectively). However, this was definitely not the case when DIA was not constrained within the pathologist's annotations and automatically established its global or hotspot area in the whole tissue sample (concordance correlation coefficients between 0.28 and 0.58).
The DIA technique demonstrated a meaningful concordance with the indices evaluated by pathologists when the tumor area is previously identified by a pathologist. In contrast, basing Ki-67 assessment on automatic tissue detection was not satisfactory and provided bad concordance results. A representative tumoral zone must therefore be manually selected prior to the measurement made by the DIA.
在“精准医学”时代,高质量肿瘤标志物检测的可用性至关重要,Ki-67 抗体评估的肿瘤增殖是乳腺癌最重要的预后因素之一。但是,Ki-67 指数的评估已经显示出一些观察者间的可变性。本研究的目的是开发一种在常规实践中用于评估浸润性乳腺癌的简单、自动化和可靠的 Ki-67 评估方法。
分析了 151 例浸润性乳腺癌活检。Ki-67 指数由 2 名病理学家用 MIB-1 抗体进行评估,作为全局肿瘤指数,并在热点区域进行评估。这两个区域也通过数字图像分析(DIA)进行分析。
对于 Ki-67 指数评估,在全局和热点肿瘤区域,当 DIA 专注于病理学家的注释时,DIA 与病理学家之间的一致性非常好(分别为 0.73 和 0.83)。然而,当 DIA 不受病理学家注释的限制,并且自动在整个组织样本中建立其全局或热点区域时,情况肯定不是这样(一致性相关系数在 0.28 和 0.58 之间)。
当肿瘤区域先前由病理学家识别时,DIA 技术与病理学家评估的指数显示出有意义的一致性。相比之下,基于自动组织检测的 Ki-67 评估并不令人满意,并且提供了较差的一致性结果。因此,在进行 DIA 测量之前,必须手动选择代表性的肿瘤区域。