Role of Sonographic Diagnosis in Managing Bethesda Class III Nodules
Open Access
- 15 September 2011
- journal article
- research article
- Published by American Society of Neuroradiology (ASNR) in American Journal of Neuroradiology
- Vol. 32 (11), 2136-2141
- https://doi.org/10.3174/ajnr.a2686
Abstract
BACKGROUND AND PURPOSE: Bethesda class III cytology is an important limitation of the US-FNA in assessing thyroid nodules. This study aimed to assess the diagnostic efficacy of US in evaluating thyroid nodules with Bethesda class III cytology. MATERIALS AND METHODS: From January 2008 to December 2009, 1036 patients with 1289 thyroid nodules diagnosed by US and subsequent US-FNA biopsy were enrolled in the study. On the basis of US features, each thyroid nodule was prospectively classified by a single radiologist into 1 of 5 diagnostic categories: benign, probably benign, borderline, possibly malignant, and malignant. Solid nodules were classified by using all 5 categories, whereas partially cystic nodules were classified by using 4 (borderline was omitted). We calculated the diagnostic efficacy of thyroid US by comparing the US diagnoses with the histopathology results of Bethesda class III nodules. RESULTS: Of the 51 Bethesda class III nodules, 35 were surgically confirmed and 8 were histologically diagnosed, and a malignancy rate of 46.5% (20/43) was determined. From the 43 nodules, the sensitivity, specificity, positive and negative predictive values, and accuracy were calculated with 9 borderline nodules excluded (100%, 94.7%, 93.3%, 100%, and 97.0%, respectively) and with the 9 when reclassified as benign (63.6%, 95.2%, 93.3%, 71.4%, and 79.1%, respectively) and malignant (100%, 85.7%, 88.0%, 100%, and 93.0%, respectively). The values obtained with exclusion and malignancy reclassification of 9 borderline nodules were not significantly different (P = .250). CONCLUSIONS: US diagnosis by using the present US classification system can be helpful for managing Bethesda class III nodules.This publication has 31 references indexed in Scilit:
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