Department of Medical Ultrasound, Changzhou First People's Hospital and The Third Affiliated Hospital of Soochow University, Changzhou, 213003, China.
Department of Echocardiography, Changzhou First People's Hospital and The Third Affiliated Hospital of Soochow University, Changzhou, 213000, China.
Clin Radiol. 2021 Jan;76(1):79.e21-79.e28. doi: 10.1016/j.crad.2020.08.016. Epub 2020 Sep 15.
To assess the value of quantitative analysis of sound touch elastography of tissues around breast lesions to facilitate the evaluation of malignancy of the lesions.
With the permission of the Ethics Committee, every patient signed informed consent forms before the study. One hundred and eighty-two solid breast lesions were analysed retrospectively. Postoperative histopathology proved that 63 lesions were malignant and 119 were benign. All lesions were examined by two-dimensional ultrasonography, colour Doppler ultrasonography and ultrasound elastography including sound touch elastography (STE) and strain elastography. Using pathological diagnosis as the reference, the correlation between each ultrasound marker and the malignancy of the solid breast masses was evaluated by chi-square test, and the logistic regression model was constructed to determine the best diagnostic model with multiple markers.
The areas under the receiver operating characteristic (ROC) curve (AUCs) of various elastography markers were compared and the markers with the largest AUC values, including quantitative, semi-quantitative, and distance markers were identified. Logistic regression analysis showed that the combination of accuracy of Breast Imaging Reporting and Data System (BI-RADS) classification + age + maximum elasticity value of the tissue around the lesion (EMax_shell) in predicting malignant lesions was higher than that of the other combinations. The prediction model verified that the sensitivity of diagnosis of the mammary lump was 94.12% and the specificity was 84.13%.
EMax_shell in the elasticity is the most valuable marker for the diagnosis of breast cancer, and age combined with EMax_shell can effectively improve the diagnostic efficacy of the BI-RADS classification in breast cancer.
评估声触诊组织量化分析技术在乳腺病变周围组织中的应用价值,以辅助评估病变的恶性程度。
本研究获得伦理委员会的批准,所有患者均在研究前签署了知情同意书。回顾性分析了 182 例乳腺实性病灶。术后组织病理学证实 63 例为恶性,119 例为良性。所有病灶均经二维超声、彩色多普勒超声及超声弹性成像(包括声触诊组织量化分析及应变弹性成像)检查。以病理诊断为参照,采用卡方检验评估各超声标志物与乳腺实性肿块恶性程度的相关性,构建多标志物的逻辑回归模型,确定最佳诊断模型。
比较了各弹性成像标志物的受试者工作特征曲线(ROC)下面积(AUC),并确定了具有最大 AUC 值的定量、半定量和距离标志物。Logistic 回归分析显示,预测恶性病灶的最佳模型是 BI-RADS 分类准确性+年龄+病变周围组织最大弹性值(EMax_shell)的组合,其诊断效能高于其他组合。验证模型表明,对乳腺肿块的诊断敏感度为 94.12%,特异度为 84.13%。
弹性中的 EMax_shell 是诊断乳腺癌最有价值的标志物,年龄与 EMax_shell 相结合可有效提高 BI-RADS 分类在乳腺癌中的诊断效能。