A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissue.
A methodology to ensure and improve accuracy of Ki67 labelling index estimation by automated digital image analysis in breast cancer tissue.
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DOI：
10.1186/bcr3639
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Bor C
中科院分区：
文献类型：
--
作者：
Laurinavicius A;Plancoulaine B;Laurinaviciene A;Herlin P;Meskauskas R;Baltrusaityte I;Besusparis J;Dasevicius D;Elie N;Iqbal Y;Bor C
免疫组织化学Ki 67标记指数（Ki 67 LI）反映了乳腺癌的增殖活性，是一个潜在的预后/预测指标。然而，由于缺乏标准化的测量方法，其临床实用性受到阻碍。除了组织异质性方面，方法学的关键要素仍然是准确估计Ki 67染色/复染肿瘤细胞谱。我们的目标是开发一种方法，以确保和提高数字图像分析（DIA）方法的准确性。对浸润性导管乳腺癌的组织微阵列（每个患者一个1 mm斑点，n = 164）进行Ki 67染色和扫描。通过使用覆盖在斑点图像上的体视学网格对阳性和阴性肿瘤细胞谱进行计数来获得标准（Ki 67-计数）。使用Aperio Genie/Nuclear算法进行DIA。通过方差分析、相关分析和回归分析估计偏倚。通过调整算法设置执行DIA的校准步骤：首先，通过主观DIA质量评估（DIA-1），其次，补偿建立的偏倚（DIA-2）。由5名病理学家独立地对相同图像进行视觉估计（Ki 67-VE）。方差分析显示DIA-0、DIA-1和两位病理医师的VE存在显著低估偏倚（P < 0.05），而DIA-2、VE-中位数和其他三个VE均在同一范围内。回归分析显示，DIA-2（R方= 0.90）的准确度最高，超过了VE中位数、个体VE和其他DIA设置。检测到DIA-2的双向偏倚，在量表的低端高估，在高端低估。应用通过逆回归的测量误差校正来改善基于DIA-2的Ki 67计数预测，特别是对于Ki 67计数<40%的临床相关区间。通过在10、15和20%的临界值下对病例进行二分来检验预测的潜在临床影响。实现了5-7%的错误分类率，相比之下，基于VE中位数的预测的错误分类率为11-18%。我们的实验提供了方法，以实现准确的Ki 67-LI估计DIA，基于适当的验证，校准和测量误差校正程序，指导量化偏差从体视学网格计数获得的参考值。该基本验证步骤是高通量自动化DIA应用的重要先决条件，用于研究Ki 67和其他免疫组织化学（IHC）生物标志物的组织异质性和临床实用性。
Immunohistochemical Ki67 labelling index (Ki67 LI) reflects proliferative activity and is a potential prognostic/predictive marker of breast cancer. However, its clinical utility is hindered by the lack of standardized measurement methodologies. Besides tissue heterogeneity aspects, the key element of methodology remains accurate estimation of Ki67-stained/counterstained tumour cell profiles. We aimed to develop a methodology to ensure and improve accuracy of the digital image analysis (DIA) approach. Tissue microarrays (one 1-mm spot per patient, n = 164) from invasive ductal breast carcinoma were stained for Ki67 and scanned. Criterion standard (Ki67-Count) was obtained by counting positive and negative tumour cell profiles using a stereology grid overlaid on a spot image. DIA was performed with Aperio Genie/Nuclear algorithms. A bias was estimated by ANOVA, correlation and regression analyses. Calibration steps of the DIA by adjusting the algorithm settings were performed: first, by subjective DIA quality assessment (DIA-1), and second, to compensate the bias established (DIA-2). Visual estimate (Ki67-VE) on the same images was performed by five pathologists independently. ANOVA revealed significant underestimation bias (P < 0.05) for DIA-0, DIA-1 and two pathologists’ VE, while DIA-2, VE-median and three other VEs were within the same range. Regression analyses revealed best accuracy for the DIA-2 (R-square = 0.90) exceeding that of VE-median, individual VEs and other DIA settings. Bidirectional bias for the DIA-2 with overestimation at low, and underestimation at high ends of the scale was detected. Measurement error correction by inverse regression was applied to improve DIA-2-based prediction of the Ki67-Count, in particular for the clinically relevant interval of Ki67-Count < 40%. Potential clinical impact of the prediction was tested by dichotomising the cases at the cut-off values of 10, 15, and 20%. Misclassification rate of 5-7% was achieved, compared to that of 11-18% for the VE-median-based prediction. Our experiments provide methodology to achieve accurate Ki67-LI estimation by DIA, based on proper validation, calibration, and measurement error correction procedures, guided by quantified bias from reference values obtained by stereology grid count. This basic validation step is an important prerequisite for high-throughput automated DIA applications to investigate tissue heterogeneity and clinical utility aspects of Ki67 and other immunohistochemistry (IHC) biomarkers.
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影响因子：
8.8
作者：
Mohammed, Z. M. A.;McMillan, D. C.;Elsberger, B.;Going, J. J.;Orange, C.;Mallon, E.;Doughty, J. C.;Edwards, J.
通讯作者：
Edwards, J.
影响因子：
4.6
作者：
Soenksen, Dirk
通讯作者：
Soenksen, Dirk
影响因子：
3.2
作者：
Laurinavicius, Arvydas;Laurinaviciene, Aida;Herlin, Paulette
通讯作者：
Herlin, Paulette
影响因子：
2.6
作者：
Kayser K;Görtler J;Borkenfeld S;Kayser G
通讯作者：
Kayser G
DOI：
10.1093/annonc/mdt303
发表时间：
2013-09
期刊：
Annals of oncology : official journal of the European Society for Medical Oncology
影响因子：
--
作者：
Goldhirsch A;Winer EP;Coates AS;Gelber RD;Piccart-Gebhart M;Thürlimann B;Senn HJ;Panel members
通讯作者：
Panel members