Callau Cristina, Lejeune Marylène, Korzynska Anna, García Marcial, Bueno Gloria, Bosch Ramon, Jaén Joaquín, Orero Guifré, Salvadó Teresa, López Carlos
Biomed Eng Online. 2015;14 Suppl 2(Suppl 2):S2. doi: 10.1186/1475-925X-14-S2-S2. Epub 2015 Aug 13.
Digital image (DI) analysis avoids visual subjectivity in interpreting immunohistochemical stains and provides more reproducible results. An automated procedure consisting of two variant methods for quantifying the cytokeratin-19 (CK19) marker in breast cancer tissues is presented.
The first method (A) excludes the holes inside selected CK19 stained areas, and the second (B) includes them. 93 DIs scanned from complete cylinders of tissue microarrays were evaluated visually by two pathologists and by the automated procedures.
There was good concordance between the two automated methods, both of which tended to identify a smaller CK19-positive area than did the pathologists. The results obtained with method B were more similar to those of the pathologists; probably because it takes into account the entire positive tumoural area, including the holes. However, the pathologists overestimated the positive area of CK19. Further studies are needed to confirm the utility of this automated procedure in prognostic studies.
数字图像(DI)分析避免了在解读免疫组化染色时的视觉主观性,并提供了更具可重复性的结果。本文介绍了一种由两种不同方法组成的自动化程序,用于定量乳腺癌组织中的细胞角蛋白-19(CK19)标记物。
第一种方法(A)排除选定的CK19染色区域内的空洞,第二种方法(B)则包括这些空洞。由两位病理学家通过视觉以及通过自动化程序对从组织微阵列完整圆柱体扫描得到的93幅数字图像进行评估。
两种自动化方法之间具有良好的一致性,两者识别出的CK19阳性区域往往比病理学家识别出的更小。方法B获得的结果与病理学家的结果更为相似;可能是因为它考虑了整个阳性肿瘤区域,包括空洞。然而,病理学家高估了CK19的阳性区域。需要进一步研究以证实这种自动化程序在预后研究中的效用。