新的成像軟件可能與病理學(xué)家的眼睛相媲美,。
研究人員創(chuàng)建了一種叫做“C-路徑”的電腦程序,，這種程序可對乳腺組織做顯微圖象的掃描以尋找6000種以上的癌癥特征。
該軟件在2組婦女中幫助預(yù)測了乳腺癌的嚴重性,，它可能是一種判斷某位患者存活機會的有用工具,。
自1920年代以來,，病理學(xué)家大多依賴于同一組少數(shù)特征來發(fā)現(xiàn)組織樣本中的異常,。 Andrew Beck及其同事研發(fā)的C-路徑旨在發(fā)現(xiàn)可幫助更為精確地反映患者存活結(jié)果的癌組織的額外特征,。 他們對采自荷蘭的一組病人的組織樣本做了C-路徑的測試。
該軟件發(fā)現(xiàn)了與不良存活機會有關(guān)的一組嶄新的特征,。
在另外一組來自溫哥華的病人中,，C-路徑根據(jù)一套已知的綜合性特征及新的癌組織特癥預(yù)測了這些婦女生存的機會。將組織分類為上皮或基質(zhì)組織是癌癥診斷的一個重要部分,，但它需要作更多一點的工作：該研究小組必須教該電腦程序如何用手工標(biāo)記的樣本來發(fā)現(xiàn)每種組織的類型,。一則相關(guān)的《觀點欄目》稱贊C-路徑為第一個潛在可用的電腦化病理系統(tǒng)，但它也指出該軟件存在可能阻止其立刻用于醫(yī)療機構(gòu)中的顯著的局限性,。(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.
