1 April 2016 Differential diagnosis of thyroid nodules with virtual touch tissue imaging of ARFI elastography
Author Affiliations +
The aim of this study was to evaluate the diagnostic performance of virtual touch tissue imaging (VTI) based on ARFI elastography technique for differentiating malignant from benign thyroid nodules. One hundred pathologically proven thyroid nodules (80 benign, 20 malignant) in 76 participants were recruited in this study. The likelihood of malignancy in the light of VTI features was scored into 6 levels by one experienced sonogist who was blinded to pathological results. In addition, the mean gray value within the thyroid nodule (mGVTN) derived from VTI image was calculated for quantitative analysis. Receiver-operating characteristic curve (ROC) analyses were performed to assess the diagnostic performance of VTI score and mGVTN. The frequency of malignant nodules (11/20) classified between VTI levels 4 to 6 was more than that of benign nodules (6/80) (p <0.001). The mGVTN of malignant nodules (45±23) was significantly lower than that of benign nodules (115±58) (p <0.001), where the range of mGVTN was from 0 to 255. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of VTI score were 55.0%, 92.5%, 85.0%, 64.7% and 89.2%, respectively. For mGVTN, those values were 70.0%, 90.0%, 86.0%, 63.6% and 92.3%, respectively. In conclusion, the VTI image seemed to be an effective tool in the differential diagnosis of thyroid nodules. The diagnosis performance of mGVTN was almost consistent with that of VTI score, which indicated that the mGVTN as a quantitative parameter might facilitate doctors diagnosing malignant thyroid nodules by VTI.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tao Li, Tao Li, Pei Zhou, Pei Zhou, Mingyue Ding, Mingyue Ding, Yongwei Mi, Yongwei Mi, Yiyong Li, Yiyong Li, Ji Zhang, Ji Zhang, } "Differential diagnosis of thyroid nodules with virtual touch tissue imaging of ARFI elastography", Proc. SPIE 9790, Medical Imaging 2016: Ultrasonic Imaging and Tomography, 97901I (1 April 2016); doi: 10.1117/12.2216190; https://doi.org/10.1117/12.2216190

Back to Top