Your browser doesn't support javascript.
loading
Virtual touch tissue imaging quantification combined with CEUS in differential diagnosis of benign and malignant TI-RADS 4 thyroid nodules / 中国医学影像技术
Article in Zh | WPRIM | ID: wpr-860989
Responsible library: WPRO
ABSTRACT
Objective: To explore the value of virtual touch tissue imaging quantification (VTIQ) combined with contrast-enhanced ultrasound (CEUS) in differential diagnosis of benign and malignant TI-RADS 4 thyroid nodules. Methods: Totally 86 patients underwent surgical operation and were pathologically diagnosed were selected, including 45 benign(benign group) and 53 malignant ( malignant group) TI-RADS 4 thyroid nodules. VTIQ and CEUS were performed before operation, and the maximal shear wave velocity (SWVmax), minimum shear wave velocity (SWVmin), mean shear wave velocity (SWVmean) as well as the ratio of lesion SWVmax to the surrounding normal tissue shear wave velocity (SWVratio) and CEUS characteristics were obtained and recorded. Then Logistic regression model of VTIQ combined with CEUS was established, the diagnostic effectiveness of VTIQ, CEUS and the combination of VTIQ and CEUS regression models of benign and malignant TI-RADS 4 thyroid nodules were compared using area under the curve (AUC). Results: SWVmax, SWVmin, SWVmean and SWVratio in malignant group were all higher than those in benign group (all P2.96 m/s and low enhancement were important indexes for malignant nodules (P<0.05). AUC of SWVmean, CEUS and Logistic regression model were 0.862, 0.835 and 0.933, respectively. Conclusion: VTIQ and CEUS have good differential diagnostic ability for benign and malignant TI-RADS 4 thyroid nodules. Combination of VTIQ and CEUS can significantly improve the diagnostic effectiveness.
Key words
Full text: 1 Index: WPRIM Type of study: Diagnostic_studies / Prognostic_studies Language: Zh Journal: Chinese Journal of Medical Imaging Technology Year: 2020 Type: Article
Full text: 1 Index: WPRIM Type of study: Diagnostic_studies / Prognostic_studies Language: Zh Journal: Chinese Journal of Medical Imaging Technology Year: 2020 Type: Article