Background: There is controversy about the accuracy of the fine-needle aspiration (FNA) cytology results in large sized thyroid nodules. Our aim was to evaluate the false-negative rate of FNA for large thyroid nodules and the usefulness of the Thyroid Imaging Reporting and Data System (TIRADS) in predicting false-negative cytology for large thyroid nodules with benign cytology. Methods: 632 thyroid nodules larger than or equal to 3cm in size with subsequent benign cytology on US-guided FNA were included. US features of internal composition, echogenicity, margin, calcifications, and shape were evaluated, and nodules were classified according to TIRADS. TIRADS category 3 included nodules without any of the following suspicious features:solidity, hypoechogenicity or marked hypoechogenicity, microlobulated or irregular margins, microcalcifications, and taller-than-wide shape. Category 4a, 4b, 4c, and 5 were assigned to nodules showing one, two, three or four, or five suspicious US features, respectively. US features associated with malignancy for these lesions were analyzed and malignancy risk according to TIRADS was calculated. Results: Of the 632 lesions, 23 lesions(3.6%) were malignant and 609(96.4%) were benign, suggesting a 3.6% false-negative rate for FNA cytology. Of the 23 malignant lesions, final pathology was mainly follicular carcinoma minimally invasive(65.2%, 15/23) and the follicular variant of papillary carcinoma(26.1%, 6/23). The malignancy risks of categories 3, 4a, 4b, and 4c nodules were 0.9%, 4.6%, 10.0%, and 11.8%, respectively. Conclusion: Large thyroid nodules with benign cytology had a relatively high false-negative risk of 3.6% and TIRADS was helpful in predicting false-negative cytology for these lesions.
Bibliographical notePublisher Copyright:
© 2017 Nam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
All Science Journal Classification (ASJC) codes
- Biochemistry, Genetics and Molecular Biology(all)
- Agricultural and Biological Sciences(all)