In:
Journal of Ultrasound in Medicine, Wiley, Vol. 36, No. 2 ( 2017-02), p. 251-260
Abstract:
To investigate the diagnostic performance of a 2‐dimensional shear wave elastographic technique (Virtual Touch tissue imaging and quantification [VTIQ]; Siemens Medical Solutions, Mountain View, CA) for predicting thyroid malignancy. Methods A total of 302 thyroid nodules underwent conventional sonography and VTIQ before fine‐needle aspiration examination or surgery. Compared with histopathologic or cytologic results in combination with follow‐up, the diagnostic performance of various shear wave speed (SWS) indices (minimum [SWS min ], maximum [SWS max ], and mean [SWS mean ]) on VTIQ as well as conventional sonographic features for predicting thyroid malignancy was evaluated in all of the nodules. Results Sixty‐five malignant and 237 benign thyroid nodules were histopathologically or cytologically confirmed. All SWS indices on VTIQ were lower in benign nodules than thyroid malignancy (all P 〈 .001). For discrimination between malignant and benign nodules, all VTIQ SWS indices were better than conventional sonographic features, such as a solid component, a taller‐than‐wide shape, microcalcification, a poorly defined margin and hypoechogenicity, in predicting thyroid malignancy (all P 〈 .05). By applying a cutoff SWS mean value of 2.60 m/s, VTIQ achieved sensitivity and negative predictive values of 84.6% and 94.3%, respectively, for differentiating nodules. The areas under the receiver operating characteristic curve of SWS max (0.862 versus 0.717), SWS min (0.866 versus 0.717), and SWS mean (0.891 versus 0.725) for nodules larger than 10 mm were higher than those for nodules of 10 mm or smaller (all P 〈 .05). Interoperator and intraoperator reproducibility was proven to be excellent, with all interclass correlation coefficient values higher than 0.80 (range, 0.813–0.905) Conclusions Virtual Touch tissue imaging and quantification is a useful and reproducible tool for predicting thyroid malignancy.
Type of Medium:
Online Resource
ISSN:
0278-4297
,
1550-9613
DOI:
10.7863/ultra.15.12070
Language:
English
Publisher:
Wiley
Publication Date:
2017
detail.hit.zdb_id:
2067124-6
