Imaging and Diagnostic Radiology (East Africa)
Objective: The objective of this study was to describe a reliable ultrasound based index scoring system based on ultraound characteristics to identify benign thyroid nodules and avoid unnecessary fine needle aspiration cytology.
Materials and Methods: Patients undergoing ultrasound-guided fine-needle aspiration cytology (FNAC) for thyroid nodules were evaluated prospectively. A total of 284 patients were evaluated from November 2005 to November 2011. There were 284 nodules. Any solid or partly solid focal nodule in the thyroid gland was included in the study. Cysts with no solid component were excluded. We used LOGIQ 9 (GE Healthcare) scanner equipped with a 10--14 MHz linear matrix transducer with color and power Doppler capability. Four US characteristics were evaluated, i.e., nodule margins, echo texture, vascularity, and calcification. Fine needle aspiration (FNA) was performed on all nodules. The nodules were labeled benign or suspicious using an ultrasound index score and the results compared with FNAC. Follicular neoplasms on fine-needle aspiration cytology were further assessed by excision biopsy and histology. Cytology/histology was used as the final diagnosis.
Results: In total 284 nodules were analyzed. All the 234 nodules in US labeled benign category were proven to be benign on cytology/histology. Therefore, the specificity of ultrasound in labeling a nodule benign was 100%. Twenty of the 50 nodules that were suspicious on US were malignant. The most significant US differentiating characteristics were nodule margins, vascularity, and microcalcification.
Conclusion: Our results show that US can accurately characterize benign thyroid nodules using an index scoring system and therefore preclude FNAC in these patients.
Journal of Clinical Imaging Science
(2012). Avoiding Unnecessary Fine-Needle Aspiration Cytology by Accuractely Predicting the Benign Nature of Thyroid Nodules Using Ultrasound. Journal of Clinical Imaging Science, 2(23).
Available at: http://ecommons.aku.edu/eastafrica_fhs_mc_imaging_diagn_radiol/25