用于肿瘤纯度估计的乳腺癌组织病理学图像分析流程
BREAST CANCER HISTOPATHOLOGY IMAGE ANALYSIS PIPELINE FOR TUMOR PURITY ESTIMATION.
作者信息
Azimi Vahid, Chang Young Hwan, Thibault Guillaume, Smith Jaclyn, Tsujikawa Takahiro, Kukull Benjamin, Jensen Bradden, Corless Christopher, Margolin Adam, Gray Joe W
机构信息
Oregon Health and Science University (OHSU).
出版信息
Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:1137-1140. doi: 10.1109/ISBI.2017.7950717. Epub 2017 Jun 19.
The translation of genomic sequencing technology to the clinic has greatly advanced personalized medicine. However, the presence of normal cells in tumors is a confounding factor in genome sequence analysis. Tumor purity, or the percentage of cancerous cells in whole tissue section, is a correction factor that can be used to improve the clinical utility of genomic sequencing. Currently, tumor purity is estimated visually by expert pathologists; however, it has been shown that there exist vast inter-observer discrepancies in tumor purity scoring. In this paper, we propose a quantitative image analysis pipeline for tumor purity estimation and provide a systematic comparison between pathologists' scores and our image-based tumor purity estimation.
基因组测序技术向临床的转化极大地推动了个性化医疗的发展。然而，肿瘤中正常细胞的存在是基因组序列分析中的一个混杂因素。肿瘤纯度，即整个组织切片中癌细胞的百分比，是一个校正因子，可用于提高基因组测序的临床应用价值。目前，肿瘤纯度由专业病理学家通过视觉评估；然而，研究表明，在肿瘤纯度评分方面，观察者之间存在巨大差异。在本文中，我们提出了一种用于肿瘤纯度估计的定量图像分析流程，并对病理学家的评分与我们基于图像的肿瘤纯度估计进行了系统比较。
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