Computer-extracted features of nuclear morphology in hematoxylin and eosin images distinguish stage II and IV colon tumors.
Computer-extracted features of nuclear morphology in hematoxylin and eosin images distinguish stage II and IV colon tumors.
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DOI：
10.1002/path.5864
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发表时间：
2022-05
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我们评估了从数字化苏木精和伊红染色的全切片图像 (WSI) 中提取的结肠癌细胞核定量特征的效用，以区分 II 期和 IV 期结肠癌。我们的发现队列由来自克利夫兰大学医院医学中心 (UHCMC) 的 100 例 II 期和 IV 期结肠癌病例组成。我们对来自 UHCMC（癌症基因组图谱的结肠腺癌，TCGA-COAD，队列）的 51 (143) 例 II 期和 79 (54) 例 IV 期结肠癌病例进行了初始（独立）模型验证。我们的方法包括以下步骤：（1）训练具有 VGG-18 架构的全卷积深度神经网络来在 WSI 上定位癌症； (2) 使用另一个基于 Mask-RCNN 和 Resnet-50 架构的深度学习模型来分割已识别癌症区域内的所有细胞核； (3)从肿瘤细胞核内外提取了总共26~641个与核形状、大小和纹理有关的定量形态特征； (4) 使用 Wilcoxon 秩和检验选择的五个最具辨别力的特征训练随机森林分类器来区分 II 期和 IV 期结肠癌。我们训练的分类器使用这五个前五个特征，在 UHCMC 和 TCGA 验证集中的保留案例上，AUC 分别为 0.81 和 0.78。对于 197 个 TCGA-COAD 病例，Cox 比例风险模型得出的风险比为 2.20（95% CI 1.24-3.88），一致性指数为 0.71，仅使用前 5 个特征进行总体生存风险分层。 Kaplan-Meier 估计还显示低风险和高风险患者之间存在统计学上的显着差异，对数秩 P 值为 0.0097。最后，对前五个特征的无监督聚类显示，与具有血行扩散的 IV 期结肠癌相比，具有腹膜扩散的 IV 期结肠癌在形态学上与没有长期转移的 II 期结肠癌更相似。 © 2022 作者。 《病理学杂志》由 John Wiley & Sons Ltd 代表大不列颠及爱尔兰病理学会出版。
We assessed the utility of quantitative features of colon cancer nuclei, extracted from digitized hematoxylin and eosin‐stained whole slide images (WSIs), to distinguish between stage II and stage IV colon cancers. Our discovery cohort comprised 100 stage II and stage IV colon cancer cases sourced from the University Hospitals Cleveland Medical Center (UHCMC). We performed initial (independent) model validation on 51 (143) stage II and 79 (54) stage IV colon cancer cases from UHCMC (The Cancer Genome Atlas's Colon Adenocarcinoma, TCGA‐COAD, cohort). Our approach comprised the following steps: (1) a fully convolutional deep neural network with VGG‐18 architecture was trained to locate cancer on WSIs; (2) another deep‐learning model based on Mask‐RCNN with Resnet‐50 architecture was used to segment all nuclei from within the identified cancer region; (3) a total of 26 641 quantitative morphometric features pertaining to nuclear shape, size, and texture were extracted from within and outside tumor nuclei; (4) a random forest classifier was trained to distinguish between stage II and stage IV colon cancers using the five most discriminatory features selected by the Wilcoxon rank‐sum test. Our trained classifier using these top five features yielded an AUC of 0.81 and 0.78, respectively, on the held‐out cases in the UHCMC and TCGA validation sets. For 197 TCGA‐COAD cases, the Cox proportional hazards model yielded a hazard ratio of 2.20 (95% CI 1.24–3.88) with a concordance index of 0.71, using only the top five features for risk stratification of overall survival. The Kaplan–Meier estimate also showed statistically significant separation between the low‐risk and high‐risk patients, with a log‐rank P value of 0.0097. Finally, unsupervised clustering of the top five features revealed that stage IV colon cancers with peritoneal spread were morphologically more similar to stage II colon cancers with no long‐term metastases than to stage IV colon cancers with hematogenous spread. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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DOI：
10.1158/1078-0432.ccr-18-2013
发表时间：
2019-03-01
期刊：
Clinical cancer research : an official journal of the American Association for Cancer Research
影响因子：
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