Fine-Needle Aspiration of Thyroid

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Abstract

Thyroid enlargement, either diffuse or in the form of thyroid nodules (solitary or multiple), is a very frequent finding, mostly by normal thyroid function tests. The prevalence of the thyroid nodules is estimated about 4% in the population of the western countries with a much higher frequency after performance of ultrasonographic studies (Brander et al. 1991; Christensen et al. 1984). Since the thyroid cancer usually appears as a nodular lesion, it seems reasonable to develop safe tests for the detection of cancer among the by far most common benign hyperplastic nodules. The therapeutic approach for benign nodules can be conservative since the morbidity of the surgical complications would exceed the morbidity of cancer if all thyroid nodules would be removed surgically (Mazzaferri et al. 1988). In this context, the fine-needle aspiration of thyroid emerged as the most useful tool in recognizing thyroid cancer as well as the most accurate and cost-effective test, compared with all noninvasive tests and represents therefore the corner stone in most guidelines for the management of thyroid nodules (Gharib et al. 2010). After the introduction of this method, the number of malignancies among the surgical specimens of the thyroid increased dramatically, reflecting a more accurate selection of the suspicious nodules for surgery. However, it does not represent an independent diagnostic test since the cytological findings must be interpreted in relation to all clinical and imaging data prior to the final recommendation for the management. Insofar it is obvious that the cytopathologists involved must be aware of the clinical implications of their report and the clinicians familiar with the pathological substrate of the nodules as well as from wording of the pathologists and the possibilities and limitations of the FNA (Buesseniers and Silver 2007).

Keywords

Thyroid Nodule Papillary Carcinoma Follicular Cell Multinucleated Giant Cell Thyroglossal Duct Cyst 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.First Department of PathologyMedical School – University of AthensAthensGreece

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