Filling the gap between microscopic and automated analysis of the tumor-stroma ratio

S. Sarvepalli, P. Lal, Afrin N. Kamal, A. Garber, J. McMichael, G. Morris-Stiff, J. Vargo, M. Rothberg, Maged Rizk, C. Burke
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Abstract

Determining the tumor-stroma ratio (TSR) using a conventional microscope is an easy to apply and highly reproducible method. Due to digitalization in the pathology workflow, the demand for automated analysis of the TSR method is rising. However, the process of automation is rather time consuming and needs validation before implementation in daily practice. In addition, international studies ask for exchange of digital images instead of the actual slides. This calls for an alternative digital scoring method. This brief report describes the pitfalls of analyzing the TSR using digital images and proposes essential adaptations to create a standardized and reproducible scoring protocol. By using a circular annotation to mimic the microscopic method, these pitfalls can be avoided. Scoring the TSR digitally using a circular annotation does not take much additional effort compared to the microscopic method. When a fixed size of the annotation is saved, new cases can be scored in less than two minutes. With this brief report we propose an adjusted method for scoring the TSR on digital images to fill the gap between microscopically and automated scoring of the TSR. In addition, it opens the opportunity for application in daily diagnostics.
填补了肿瘤-间质比显微分析和自动分析之间的空白
利用常规显微镜测定肿瘤间质比(TSR)是一种易于应用且重复性高的方法。由于病理工作流程的数字化,对TSR方法自动化分析的需求正在上升。然而,自动化的过程是相当耗时的,并且需要在日常实践中实施之前进行验证。此外,国际研究要求交换数字图像,而不是实际的幻灯片。这就需要另一种数字评分方法。这篇简短的报告描述了使用数字图像分析TSR的陷阱,并提出了创建标准化和可重复的评分协议的基本调整。通过使用循环注释来模拟微观方法,可以避免这些缺陷。与微观方法相比,使用循环注释对TSR进行数字化评分并不需要太多额外的努力。当保存固定大小的注释时,新案例可以在不到两分钟的时间内得分。在这篇简短的报告中,我们提出了一种在数字图像上进行TSR评分的调整方法,以填补TSR显微评分和自动评分之间的空白。此外,它还为日常诊断提供了应用机会。
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