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.
To reduce the effects of respiratory motion in the quantitative analysis based on liver contrast-enhanced ultrasound (CEUS) image sequencesof single mode. The image gating method and the iterative registration method using model image were adopted to register liver contrast-enhanced ultrasound image sequences of single mode. The feasibility of the proposed respiratory motion correction method was explored preliminarily using 10 hepatocellular carcinomas CEUS cases. The positions of the lesions in the time series of 2D ultrasound images after correction were visually evaluated. Before and after correction, the quality of the weighted sum of transit time (WSTT) parametric images were also compared, in terms of the accuracy and spatial resolution. For the corrected and uncorrected sequences, their mean deviation values (mDVs) of time-intensity curve (TIC) fitting derived from CEUS sequences were measured. After the correction, the positions of the lesions in the time series of 2D ultrasound images were almost invariant. In contrast, the lesions in the uncorrected images all shifted noticeably. The quality of the WSTT parametric maps derived from liver CEUS image sequences were improved more greatly. Moreover, the mDVs of TIC fitting derived from CEUS sequences after the correction decreased by an average of 48.48±42.15. The proposed correction method could improve the accuracy of quantitative analysis based on liver CEUS image sequences of single mode, which would help in enhancing the differential diagnosis efficiency of liver tumors.