Sonographic criteria predictive of benign thyroid nodules useful in avoiding unnecessary ultrasound-guided fine needle aspiration
- PMID: 24866975
- DOI: 10.1016/j.jfma.2014.03.015
Sonographic criteria predictive of benign thyroid nodules useful in avoiding unnecessary ultrasound-guided fine needle aspiration
Abstract
Background/purpose: There has been no individual ultrasound feature of having high accuracy for diagnosis of thyroid malignancy. In this study, we aimed to establish feature-oriented criteria to characterize benign thyroid nodules that do not require ultrasound (US)-guided fine needle aspiration (FNA).
Methods: We reviewed 374 patients with thyroid nodules who had undergone US-guided FNA at our institution (2005-2008). Thyroid nodules were classified into two groups: Category 1 (benign nodules that required follow-up 6-12 months later but not US-guided FNA); and Category 2 (indeterminate nodules or suspected carcinoma that required US-guided FNA). To test the validity, we reviewed 315 consecutive patients who had histologically proven thyroid carcinoma (n = 39) and randomly selected 40 of the 276 patients with benign nodules (2009-2010).
Results: Of 374 nodules, 354 (95%) were benign and 20 (5%) malignant. On US, 260 nodules had no calcification, no increase in vascularity, well-defined margin, and no lymphadenopathy (Category 1). Using a combination of these four features, we were able to discriminate benign from indeterminate nodules or suspected malignant nodules with a sensitivity of 73%, and specificity and positive predictive value of 100%. Validity testing revealed that none of the 39 malignant thyroid nodules had all four US features. All Category 1 nodules (2005-2008) remained benign at the 3-years follow up.
Conclusion: The combination of four US features of Category 1 nodules is highly predictive of benign disease, and we could avoid unnecessary US-guided FNA in 69.5% of our patients using this combined features.
Keywords: aspiration; biopsy; nodule; thyroid gland; ultrasound.
Copyright © 2014. Published by Elsevier B.V.
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