Blessin Niclas C, Yang Cheng, Mandelkow Tim, Raedler Jonas B, Li Wenchao, Bady Elena, Simon Ronald, Vettorazzi Eik, Lennartz Maximilian, Bernreuther Christian, Fraune Christoph, Jacobsen Frank, Krech Till, Marx Andreas, Lebok Patrick, Minner Sarah, Burandt Eike, Clauditz Till S, Wilczak Waldemar, Sauter Guido, Heinzer Hans, Haese Alexander, Schlomm Thorsten, Graefen Markus, Steurer Stefan
Institute of Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
College of Arts and Sciences, Boston University, Boston, MA, USA.
J Pathol. 2023 May;260(1):5-16. doi: 10.1002/path.6057. Epub 2023 Mar 6.
The Ki-67 labeling index (Ki-67 LI) is a strong prognostic marker in prostate cancer, although its analysis requires cumbersome manual quantification of Ki-67 immunostaining in 200-500 tumor cells. To enable automated Ki-67 LI assessment in routine clinical practice, a framework for automated Ki-67 LI quantification, which comprises three different artificial intelligence analysis steps and an algorithm for cell-distance analysis of multiplex fluorescence immunohistochemistry (mfIHC) staining, was developed and validated in a cohort of 12,475 prostate cancers. The prognostic impact of the Ki-67 LI was tested on a tissue microarray (TMA) containing one 0.6 mm sample per patient. A 'heterogeneity TMA' containing three to six samples from different tumor areas in each patient was used to model Ki-67 analysis of multiple different biopsies, and 30 prostate biopsies were analyzed to compare a 'classical' bright field-based Ki-67 analysis with the mfIHC-based framework. The Ki-67 LI provided strong and independent prognostic information in 11,845 analyzed prostate cancers (p < 0.001 each), and excellent agreement was found between the framework for automated Ki-67 LI assessment and the manual quantification in prostate biopsies from routine clinical practice (intraclass correlation coefficient: 0.94 [95% confidence interval: 0.87-0.97]). The analysis of the heterogeneity TMA revealed that the Ki-67 LI of the sample with the highest Gleason score (area under the curve [AUC]: 0.68) was as prognostic as the mean Ki-67 LI of all six foci (AUC: 0.71 [p = 0.24]). The combined analysis of the Ki-67 LI and Gleason score obtained on identical tissue spots showed that the Ki-67 LI added significant additional prognostic information in case of classical International Society of Urological Pathology grades (AUC: 0.82 [p = 0.002]) and quantitative Gleason score (AUC: 0.83 [p = 0.018]). The Ki-67 LI is a powerful prognostic parameter in prostate cancer that is now applicable in routine clinical practice. In the case of multiple cancer-positive biopsies, the sole automated analysis of the worst biopsy was sufficient. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Ki-67标记指数（Ki-67 LI）是前列腺癌中一种强大的预后标志物，尽管对其进行分析需要对200 - 500个肿瘤细胞中的Ki-67免疫染色进行繁琐的手动定量。为了在常规临床实践中实现Ki-67 LI的自动化评估，开发了一种用于Ki-67 LI定量的自动化框架，该框架包括三个不同的人工智能分析步骤以及一种用于多重荧光免疫组织化学（mfIHC）染色细胞距离分析的算法，并在12475例前列腺癌队列中进行了验证。在每个患者包含一个0.6毫米样本的组织微阵列（TMA）上测试了Ki-67 LI的预后影响。使用每个患者包含来自不同肿瘤区域的三到六个样本的“异质性TMA”来模拟对多个不同活检样本的Ki-67分析，并分析了30例前列腺活检样本，以比较基于“经典”明场的Ki-67分析与基于mfIHC的框架。在11845例分析的前列腺癌中，Ki-67 LI提供了强大且独立的预后信息（每项p < 0.001），并且在常规临床实践的前列腺活检样本中，Ki-67 LI自动化评估框架与手动定量之间发现了极好的一致性（组内相关系数：0.94 [95%置信区间：0.87 - 0.97]）。对异质性TMA的分析表明，Gleason评分最高的样本的Ki-67 LI（曲线下面积[AUC]：0.68）与所有六个病灶的平均Ki-67 LI（AUC：0.71 [p = 0.24]）的预后价值相当。对相同组织部位获得的Ki-67 LI和Gleason评分进行联合分析表明，在经典的国际泌尿病理学会分级（AUC：0.82 [p = 0.002]）和定量Gleason评分（AUC：0.83 [p = 0.018]）的情况下，Ki-67 LI增加了显著的额外预后信息。Ki-67 LI是前列腺癌中一个强大的预后参数，现在可应用于常规临床实践。在多个癌症阳性活检样本的情况下，仅对最差的活检样本进行自动化分析就足够了。© 2023作者。《病理学杂志》由约翰·威利父子有限公司代表大不列颠及爱尔兰病理学会出版。
