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一种用于乳腺梭形细胞病变的算法方法。

An algorithmic approach to spindle cell lesions of the breast.

机构信息

Department of Pathology and Laboratory Medicine, Weill Cornell Medical College, New York, NY 10065, USA.

出版信息

Adv Anat Pathol. 2013 Mar;20(2):95-109. doi: 10.1097/PAP.0b013e3182862846.

Abstract

Spindle cell lesions arising in the breast represent reactive, benign, and malignant tumors with overlapping morphologic, clinico-radiologic, and immunohistochemical characteristics. Moreover, common entities comprising this subset are usually uncommon entities in overall prevalence. The combination of such diagnostic "disadvantages" can make the practicing pathologist feel uncertain from the onset of encountering such a case. We hope to dispel some of this discomfort by delineating a simple algorithm that provides structure and direction to the diagnostic work-up. Finally, we provide short summaries of the most commonly encountered mammary spindle cell lesions.

摘要

乳腺中出现的梭形细胞病变代表具有重叠形态学、临床放射学和免疫组织化学特征的反应性、良性和恶性肿瘤。此外,由这些亚群组成的常见实体在总体流行率中通常较为罕见。这种诊断上的“劣势”的组合可能会使执业病理学家在遇到这种病例时感到不确定。我们希望通过制定一个简单的算法来消除这种不适,该算法为诊断工作提供了结构和方向。最后,我们提供了最常见的乳腺梭形细胞病变的简短总结。

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