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Preparation of cell blocks for lung cancer diagnosis and prediction: Protocol and experience of a high-volume center

机译:制备用于肺癌诊断和预测的细胞块:高容量中心的操作规程和经验

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摘要

Minimally invasive diagnostic techniques are increasingly being used to obtain specimens for pathological diagnosis and prediction. Referring to lung cancer, both endobronchial and endoesophageal ultrasound are used worldwide as diagnostic routine methods. Consequently, an increasing number of pathological samples are cytological and fewer are histological. On the other hand, the requirements for specific and sensitive tumor subtyping complemented by predictive analyses are steadily increasing and are an essential basis for evidence-based treatment decisions. In this article we focus on the cell block method as a helpful tool for diagnostic and predictive analyses in lung cancer and point out its advantages and disadvantages in comparison to conventional cytological and biopsy specimens. Furthermore, we retrospectively analyze the diagnostic results of the cell block method in a high-volume center over 5 years. The main advantages of cell blocks are the availability of established and validated protocols, archiving and the opportunity to have serial sections from the same specimens to provide or repeat molecular analyses. Actually, in case of tumor progression, even additional biomarkers can be tested using the original cell block when re-biopsies are not feasible. The cell block method should be considered as a reliable, complimentary approach to conventional cytological or biopsy procedures, which is helpful to fulfill the increasing requirements of high-quality diagnostics and prediction.
机译:越来越多地使用微创诊断技术来获取用于病理诊断和预测的标本。关于肺癌,支气管内和食管内超声均在世界范围内用作诊断常规方法。因此,越来越多的病理学样品是细胞学样品,而较少的是组织学样品。另一方面,对特异性和敏感性肿瘤亚型的需求以及预测分析的需求正在稳步增长,并且是基于证据的治疗决策的必要基础。在本文中,我们将重点放在细胞阻断法上,将其作为肺癌诊断和预测分析的有用工具,并指出其与常规细胞学和活检标本相比的优缺点。此外,我们回顾性分析了大容量中心5年以上的细胞阻滞方法的诊断结果。细胞块的主要优点是可以使用已建立和验证的方案,可以进行归档,也可以从同一样本中获得连续切片以提供或重复进行分子分析。实际上,在肿瘤进展的情况下,当无法进行活检时,甚至可以使用原始细胞块来测试其他生物标志物。细胞阻断法应被视为常规细胞学或活检程序的一种可靠的补充方法,这有助于满足高质量诊断和预测日益增长的要求。

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