Department of Health Science and Technology, Aalborg University, Fredrik Bajersvej 7D2, 9220, Aalborg, Denmark.
Institute of Pathology, Aalborg University Hospital, Denmark.
Cytometry A. 2019 Apr;95(4):381-388. doi: 10.1002/cyto.a.23683. Epub 2018 Dec 17.
Breast cancer is the most frequent cancer among women worldwide. Ki67 can be used as an immunohistochemical pseudo marker for cell proliferation to determine how aggressive the cancer is and thereby the treatment of the patient. No standard Ki67 staining protocol exists, resulting in inter-laboratory stain variability. Therefore, it is important to determine the quality control of a staining protocol to ensure correct diagnosis and treatment of patients. Currently, quality control is performed by the organization NordiQC that use an expert panel-based qualitative assessment system. However, no objective method exists to determine the quality of a staining protocol. In this study, we propose an algorithm, to objectively assess staining quality from segmented cell nuclei structures extracted from cell lines. The cell nuclei were classified into either Ki67 positive or negative to determine the Ki67 proliferation index within the cell lines. A Ki67 stain quality model based on ordinal logistic regression was developed to determine the quality of a staining protocol from features extracted from the segmented cell nuclei in the cell lines. The algorithm was able to segment and classify Ki67 positive cell nuclei with a sensitivity and positive predictive value (PPV) of 0.90 and 0.94 and Ki67 negative cell nuclei with a sensitivity and PPV of 0.78 and 0.78. The mean difference between a manual and automatic Ki67 proliferation index was -0.003 with a standard deviation of 0.056. The ordinal logistic regression model found that the stain intensity for both the Ki67 positive and Ki67 negative cell nuclei were statistically significant as parameters determining the stain quality from the cell line cores. The framework shows great promise for using cell nuclei information from cell lines to predict the staining quality of staining protocols. © 2018 International Society for Advancement of Cytometry.
乳腺癌是全球女性最常见的癌症。Ki67 可用作细胞增殖的免疫组织化学伪标志物,以确定癌症的侵袭性,从而确定患者的治疗方法。目前不存在标准的 Ki67 染色方案,导致实验室间染色的可变性。因此,确定染色方案的质量控制对于确保正确诊断和治疗患者非常重要。目前,质量控制由 NordiQC 组织进行,该组织使用基于专家小组的定性评估系统。但是,目前还没有客观的方法来确定染色方案的质量。在这项研究中,我们提出了一种算法,从细胞系中提取的分割细胞核结构来客观评估染色质量。将细胞核分为 Ki67 阳性或阴性,以确定细胞系中的 Ki67 增殖指数。基于有序逻辑回归开发了基于 Ki67 染色质量模型,以从细胞系中分割的细胞核提取的特征来确定染色方案的质量。该算法能够分割和分类 Ki67 阳性细胞核,其灵敏度和阳性预测值(PPV)分别为 0.90 和 0.94,以及 Ki67 阴性细胞核,其灵敏度和 PPV 分别为 0.78 和 0.78。手动和自动 Ki67 增殖指数之间的平均差异为-0.003,标准偏差为 0.056。有序逻辑回归模型发现,Ki67 阳性和 Ki67 阴性细胞核的染色强度均为统计学显著参数,可用于从细胞系核心预测染色方案的染色质量。该框架有望利用细胞系中的细胞核信息来预测染色方案的染色质量。