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Simultaneous automatic scoring and co-registration of hormone receptors in tumour areas in whole slide images of breast cancer tissue slides

机译:乳腺癌组织玻片全玻片图像中肿瘤区域激素受体的同时自动评分和共配准

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摘要

Aims: \ud\udAutomation of downstream analysis may offer many potential benefits to routine histopathology. One area of interest for automation is in the scoring of multiple immunohistochemical markers in order to predict the patient's response to targeted therapies. Automated serial slide analysis of this kind requires robust registration to identify common tissue regions across sections. We present an automated method for co-localised scoring of Estrogen Receptor and Progesterone Receptor (ER/PR) in breast cancer core biopsies using whole slide images.\ud\udMethods and Results: \ud\udRegions of tumour in a series of fifty consecutive breast core biopsies were identified by annotation on H&E whole slide images. Sequentially cut immunohistochemical stained sections were scored manually, before being digitally scanned and then exported into JPEG 2000 format. A two-stage registration process was performed to identify the annotated regions of interest in the immunohistochemistry sections, which were then scored using the Allred system. Overall correlation between manual and automated scoring for ER and PR was 0.944 and 0.883 respectively, with 90% of ER and 80% of PR scores within in one point or less of agreement.\ud\udConclusions: \ud\udThis proof of principle study indicates slide registration can be used as a basis for automation of the downstream analysis for clinically relevant biomarkers in the majority of cases. The approach is likely to be improved by implantation of safeguarding analysis steps post registration.
机译:目的:自动化下游分析可能会为常规组织病理学带来许多潜在的好处。自动化的兴趣领域之一是对多个免疫组织化学标记物进行评分,以预测患者对靶向疗法的反应。这种自动的连续载玻片分析需要强大的配准,以识别出整个切片的共同组织区域。我们提供了一种使用完整的幻灯片图像对乳腺癌核心活检组织中的雌激素受体和孕激素受体(ER / PR)进行共定位评分的自动化方法。\ ud \ ud方法和结果:\ ud \ ud连续五十个连续的肿瘤区域通过在H&E整个幻灯片图像上进行注释来识别乳房核心活组织检查。对连续切割的免疫组织化学染色切片进行人工评分,然后进行数字扫描,然后导出为JPEG 2000格式。进行了两个阶段的注册过程,以识别免疫组织化学部分中感兴趣的注释区域,然后使用Allred系统对其进行评分。 ER和PR手动和自动评分之间的总体相关性分别为0.944和0.883,其中ER分数的90%和PR分数的80%在一个或更少的一致性内。\ ud \ ud结论:\ ud \ ud表明在大多数情况下,载玻片配​​准可用作自动化临床相关生物标志物下游分析的基础。该方法可能会通过在注册后植入保护性分析步骤而得到改进。

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