ObjectiveTo study the Young's modulus obtained by the real-time shear wave elastography (SWE) in healthy adults' parotid gland and submaxillary gland and to explore the probable factors affecting the Young's modulus, such as bilateral parotid and submaxillary gland, sex, age, height and weight. MethodsThere were 35 healthy volunteers who underwent SWE in parotid gland and submaxillary gland between December 3 and 18, 2013. The difference of Young's modulus in bilateral parotid and submaxillary gland, and the modulus values of different sex, age, height and weight groups were also compared. ResultsThe Young's modulus of parotid gland was (8.14±1.78) kPa, and the Young's modulus of submaxillary gland was (11.52±2.34) kPa. The differences of Young's modulus between the two sides of parotid gland and submaxillary gland were not statistically significant (P>0.05); the differences of Young's modulus of parotid and submaxillary gland between different sex, age, height and weight groups had no statistical significance, either (P>0.05). ConclusionThe real-time shear wave elastography can be applied to evaluate the elasticity of parotid and submaxillary gland and to lay the foundation for further diagnosis of salivary lesions.
Objective To evaluate the diagnostic performance of thyroid imaging reporting and data system (TI-RADS)classification and elastography in differentiating benign and malignant thyroid nodules according to size. Methods A total of 222 thyroid nodules (209 cases) with solid or predominantly solid internal contentdiagnosed at pathological findings were enrolled in this study, all the 209 cases underwent surgery in our hospital from Jan.2014 to Jun.2014. The diagnostic performance of TI-RADS classification and elastography in differentiating benign and malignant thyroid nodules according to size nodules were evaluated (for≤1 cm and > 1 cm respectively). Results By using TI-RADS category and elastography, 178 thyroid nodules were diagnosed as malignant nodules, and 44 thyroid nodules were diagnosed as benign nodules. The high predictive factors for malignant thyroid nodules of > 1 cm were irregular shape(OR=6.376), microcalcification(OR=21.525), and capsule invasion(OR=3.852), P < 0.05. The factors for thyroid nodules of≤1 cm were anteroposterior to transverse diameter ratio≥1(OR=3.406), capsule invasion (OR=3.922), and high elastography score(OR=1.606), that suggested the possibility of malignant (P < 0.05). For nodules of > 1 cm, the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and Youden index of TI-RADS combining with elastography were 98.3%(59/60), 68.6%(24/35), 87.4%(83/95), 84.3%(59/70), 96.0% (24/25), and 66.9% respectively; for nodules of≤1 cm, the sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and Youden index were 98.5%(67/68), 30.5%(18/59), 66.9%(85/127), 62.0%(67/108), 94.7%(18/19), and 29.0% respectively. Conclusion TI-RADS category combined with elastography for diagnosis of thyroid nodules in different size has just a bit differently diagnostic indicators, but that play a high diagnostic performance on the thyroid nodules with maximum diameter > 1 cm.
ObjectiveTo establish logistic regression analysis model to evaluate the diagnostic efficacy of breast imaging report and data system (BI-RADS) ultrasound signs in forecasting malignant risk of breast lesions. MethodUltrasound graphic materials of 1 660 breast lesions diagnosed during January to September 2011 were retrospectively studied and standardized by BI-RADS. Pathology results were regarded as gold standard reference. Ultrasound signs with significant efficacy after single-factor logistic regression were evaluated in multi-factor logistic regression model to predict the malignant risk of breast lesions. ResultsEighteen ultrasound signs of breast lesions on BI-RADS were included in the final regression model. Among them, Cooper ligaments stretch, echogenic halo, skin thickening, axillary lymph node abnormalities, structural distortions and speculation had high OR values of 30 or more and had higher specificity than 90%. The diagnosis values of regressions model were high, with a sensitivity of 84.5%, specificity 95.5% and accuracy 91.4%. The area under ROC curve was 0.964 and prediction accuracy was 91.0%. ConclusionsThe logistic regression model based on BI-RADS ultrasound signs of breast lesions has high diagnostic values in detecting breast cancer.