Comparison of Acoustic Radiation Force Impulse Imaging and Strain Elastography in Differentiating Malignant From Benign Thyroid Nodules.
JOURNAL OF ULTRASOUND IN MEDICINE(2017)
Abstract
ObjectivesThis study aimed to evaluate the diagnostic value of acoustic radiation force impulse (ARFI) imaging and strain elastography in differentiating malignant from benign thyroid nodules. MethodsThis study included 128 patients (104 female and 24 male; mean agestandard deviation, 4811 years; range, 23-76 years) with 152 pathologically proven thyroid nodules. Conventional sonography, strain ratio (SR) of strain elastography, virtual touch tissue imaging (VTI) grade, and virtual touch tissue quantification (shear wave velocity [SWV]) from ARFI imaging data were generated for each nodule. The diagnostic performance of the three elastography analysis methods was analyzed and compared by multiple receiver operating characteristic curve analysis. The interobserver agreement for VTI grade was also assessed. ResultsThe best cutoff values for VTI grade, mean SWV, and mean SR for predicting malignant thyroid nodules were greater than or equal to grade , 2.87m/s and 2.37, respectively. The area under the receiver operating characteristic curve for VTI grade, mean SWV, and mean SR was 0.854, 0.869 and 0.849, respectively (P>.05), and the accuracy was 83.55, 81.58 and 80.26%, respectively (P>.05). The accuracy of the combined use of conventional sonography and ARFI imaging for VTI grade, mean SWV, and mean SR was 98.03, 95.39 and 96.71%, respectively, which was slightly higher than that of conventional sonography (P>.05). The interobserver agreement produced a -value of 0.98 (95% confidence interval, 0.959-1.000). ConclusionsBoth strain elastography and ARFI imaging have high sensitivity and specificity for differentiating malignant from benign thyroid nodules. Combined with sonography, these techniques can improve the accuracy of thyroid nodule diagnosis.
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Key words
acoustic radiation force impulse,sonography,strain elastography,thyroid nodule,virtual touch tissue imaging,virtual touch tissue quantification
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