Decision Support System for Predicting outcome of ER+ breast cancers

描述(由申请人提供)：我们提出了一种替代的、廉价的方法来确定ER+乳腺癌患者中仅激素治疗就足够而不需要辅助化疗的子集。我们的新方法使用计算机视觉和机器学习技术从数字化的乳腺组织切片中提取信息(例如，细胞核、淋巴细胞、纹理外观和小管密度的图形和形态排列)，产生连续的基于图像的风险评分(IBRIS)，从0到1预测复发的风险。通过选择适当的临界值，可以使用IBRIS将ER+患者分成两类：低风险和高风险。低风险确定了那些只对激素治疗有良好反应的女性。在美国每年被诊断为雌激素受体阳性(ER+)乳腺癌的12万名妇女中，绝大多数将被认为在10年内有远处复发(转移)的高风险。根据目前的国家综合癌症网络(NCCN)指南，这些妇女将被建议在标准激素治疗(如他莫昔芬)的基础上接受辅助化疗。然而，这些妇女中85%将不会从化疗中受益，但仍将招致其有害的副作用。帮助更好地确定哪些女性应该单独接受他莫昔芬治疗的唯一非研究工具是Oncotype Dx分子分析，它现在被内科肿瘤学家广泛使用。Oncotype Dx能够正确地将50%的ER+癌症患者重新分类(为低风险)，这些患者已被NCCN指南归类为高风险(或中风险)，从而消除了她们需要化疗的情况。然而，由于成本高(4500美元)，而且要求组织样本被送到专门的远程机构，美国(以及世界各地)的大多数女性都无法获得Oncotype Dx。因此，市场显然需要一种能够接触到更广泛受众的低价检测方法。这项建议的具体目标如下：1)开发一种基于图像的风险评分(IBRIS)，用于预测不接受化疗的ER+乳腺癌患者亚组，以及2)评估IBRIS在预测单独使用他莫昔芬治疗的一组ER+乳腺癌患者复发方面的表现。与分子分析相比，IBRIS有几个关键的优势。首先，它不需要中断目前的临床方案，因为在常规病理检查中已经收集了必要的组织样本。其次，IBRIS的销售成本为零，因此可以作为分子检测的低价替代方案，或者作为一种定量分类，确定哪些患者应该接受更昂贵的分子检测。最后，由于IBRIS只需要一个数字幻灯片扫描仪(即不需要专门的设施)，它的足迹可以扩展到世界各地(通过互联网)。 与公共健康相关：在美国，每年有数万名雌激素受体阳性(ER+)乳腺癌女性接受化疗，尽管只有几千人会从中受益。在这项建议中，我们将开发一个基于图像的风险评分(IBRIS)来预测哪些ER+乳腺癌患者不需要化疗。这项测试将为目前使用的昂贵得多的基于基因表达的分析提供一种经济的替代方法。

DESCRIPTION (provided by applicant): We propose an alternative, inexpensive means for identifying the subset of women with ER+ breast cancer for whom hormonal therapy alone is sufficient, and adjuvant chemotherapy is not required. Our novel approach uses computer vision and machine learning techniques to extract information from digitized histological sections of breast tissue (e.g. graphical and morphological arrangement of nuclei, lymphocytes, textural appearance, and tubule density), yielding a continuous image-based risk score (IbRiS) from zero to one that predicts the risk of recurrence. By choosing the appropriate cutoff value, IbRiS can be used to stratify ER+ patients into two classes: low and high risk. A low risk identifies those women who would respond well to hormonal therapy alone. Of the 120,000 women annually diagnosed with estrogen receptor positive (ER+) breast cancer in the US, the vast majority will be considered at high risk of having distant recurrence (metastasis) within 10 years. Under current National Comprehensive Cancer Network (NCCN) guidelines, these women will be advised to receive adjuvant chemotherapy in addition to standard hormonal treatment (e.g. tamoxifen). However, 85% of these women will not benefit from chemotherapy, and yet will still incur its deleterious side-effects. The only non-investigational tool to help better determine which women should receive tamoxifen alone is the Oncotype Dx molecular assay, which is now widely used by medical oncologists. Oncotype Dx is able to correctly reclassify (as low-risk) 50% of those women with ER+ cancers that have been classified as high-risk (or intermediate-risk) by the NCCN guidelines, obviating their need for chemotherapy. However, Oncotype Dx is inaccessible to the majority of women in the US (and worldwide) because of its high cost ($4500), and requirement that the tissue samples be sent to specialized remote facilities. Consequently, there is clearly a market need for a lower-priced assay capable of reaching a wider audience. The specific aims of this proposal are as follows: 1) develop an image-based risk score (IbRiS) for predicting the subset of women with ER+ breast cancer that wil respond wel without chemotherapy and 2) evaluate IbRiS performance in predicting recurrence over an independent set of ER+ breast cancers treated with tamoxifen alone. IbRiS has several key advantages over molecular assays. First, it requires no disruption of the current clinical protocol since the necessary tissue samples are already collected during routine pathological examinations. Second, IbRiS has a zero cost-of-goods sold, and thus could serve as either a lower-priced alternative to a molecular assay or as a quantitative triage, determining which patients should be administered the more expensive molecular test. Finally, since IbRiS only requires a digital slide scanner (i.e. no specialized facility is necessary), its footprint could extend worldwide (via the internet). PUBLIC HEALTH RELEVANCE: Every year tens of thousands of women in the US with estrogen receptor positive (ER+) breast cancer are treated with chemotherapy, though only a few thousand will benefit from it. In this proposal we will develop an image-based risk score (IbRiS) to predict which women with ER+ breast cancer do not require chemotherapy. This test will provide an economical alternative to the far more expensive gene-expression based assays currently in use.