新的成像软件可能与病理学家的眼睛相媲美。
研究人员创建了一种叫做“C-路径”的电脑程序，这种程序可对乳腺组织做显微图象的扫描以寻找6000种以上的癌症特征。
该软件在2组妇女中帮助预测了乳腺癌的严重性，它可能是一种判断某位患者存活机会的有用工具。
自1920年代以来，病理学家大多依赖于同一组少数特征来发现组织样本中的异常。 Andrew Beck及其同事研发的C-路径旨在发现可帮助更为精确地反映患者存活结果的癌组织的额外特征。 他们对采自荷兰的一组病人的组织样本做了C-路径的测试。
该软件发现了与不良存活机会有关的一组崭新的特征。
在另外一组来自温哥华的病人中，C-路径根据一套已知的综合性特征及新的癌组织特症预测了这些妇女生存的机会。将组织分类为上皮或基质组织是癌症诊断的一个重要部分，但它需要作更多一点的工作：该研究小组必须教该电脑程序如何用手工标记的样本来发现每种组织的类型。一则相关的《观点栏目》称赞C-路径为第一个潜在可用的电脑化病理系统，但它也指出该软件存在可能阻止其立刻用于医疗机构中的显著的局限性。(生物谷 Bioon.com)
doi:10.1126/scitranslmed.3002564
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Systematic Analysis of Breast Cancer Morphology Uncovers Stromal Features Associated with Survival
Andrew H. Beck, Ankur R. Sangoi, Samuel Leung, Robert J. Marinelli, Torsten O. Nielsen, Marc J. van de Vijver, Robert B. West, Matt van de Rijn and Daphne Koller
The morphological interpretation of histologic sections forms the basis of diagnosis and prognostication for cancer. In the diagnosis of carcinomas, pathologists perform a semiquantitative analysis of a small set of morphological features to determine the cancer’s histologic grade. Physicians use histologic grade to inform their assessment of a carcinoma’s aggressiveness and a patient’s prognosis. Nevertheless, the determination of grade in breast cancer examines only a small set of morphological features of breast cancer epithelial cells, which has been largely unchanged since the 1920s. A comprehensive analysis of automatically quantitated morphological features could identify characteristics of prognostic relevance and provide an accurate and reproducible means for assessing prognosis from microscopic image data. We developed the C-Path (Computational Pathologist) system to measure a rich quantitative feature set from the breast cancer epithelium and stroma (6642 features), including both standard morphometric descriptors of image objects and higher-level contextual, relational, and global image features. These measurements were used to construct a prognostic model. We applied the C-Path system to microscopic images from two independent cohorts of breast cancer patients [from the Netherlands Cancer Institute (NKI) cohort, n = 248, and the Vancouver General Hospital (VGH) cohort, n = 328]. The prognostic model score generated by our system was strongly associated with overall survival in both the NKI and the VGH cohorts (both log-rank P ≤ 0.001). This association was independent of clinical, pathological, and molecular factors. Three stromal features were significantly associated with survival, and this association was stronger than the association of survival with epithelial characteristics in the model. These findings implicate stromal morphologic structure as a previously unrecognized prognostic determinant for breast cancer.
