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An Algorithmic Approach to the Diagnosis of Pancreatic Neoplasms

机译:诊断胰腺肿瘤的算法方法

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CONTEXT: The pancreas gives rise to an array of distinct neoplasms that can be solid, cystic, or intraductal and can recapitulate the various lines of differentiation present in the normal gland. OBJECTIVE: To develop an algorithmic approach to the diagnosis of pancreatic neoplasms that simplifies their pathologic evaluation. DATA SOURCES: We reviewed literature related to the classification of pancreatic neoplasms on the basis of their gross, histologic, and immunohistochemical features. CONCLUSIONS: By using a series of dichotomous decisions, the differential diagnosis of a pancreatic neoplasm can be narrowed, and in cases of the more common neoplasms, accurate classification can be achieved. Uncommon neoplasms not accounted for by this approach are also discussed, and the additional diagnostic information needed for complete pathologic reporting is presented.
机译:背景:胰腺产生了一系列不同的肿瘤,这些肿瘤可以是实体的,囊性的或导管内的,并可以概括正常腺中存在的各种分化谱系。目的:开发一种诊断胰腺肿瘤的算法方法,以简化其病理学评估。资料来源:我们根据胰腺肿瘤的总体,组织学和免疫组化特征,回顾了有关胰腺肿瘤分类的文献。结论:通过使用一系列二分决策,可以缩小胰腺肿瘤的鉴别诊断范围,在较常见的肿瘤中,可以实现准确的分类。还讨论了这种方法未解决的罕见肿瘤,并提出了完整病理报告所需的其他诊断信息。

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  • 来源
    《Archives of Pathology & Laboratory Medicine》 |2009年第3期|p.454-464|共11页
  • 作者单位

    David S. Klimstra, MD, Martha B. Pitman, MD, Ralph H. Hruban, MDAccepted for publication October 21, 2008.From the Department of Pathology, Memorial Sloan-Kettering Cancer Center, New York, New York (Dr Klimstra), Department of Pathology, Massachusetts General Hospital, Boston (Dr Pitman), and Department of Pathology, The Sol Goldman Pancreatic Cancer Research Center, The Johns Hopkins Medical Institutions, Baltimore, Maryland (Dr Hruban).The authors have no relevant financial interest in the products or companies described in this article.Reprints: David S. Klimstra, MD, Department of Pathology, Memorial Sloan-Kettering Cancer Center, 1275 York Ave, New York, NY 10065 (e-mail: klimstrd@mskcc.org).,;

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