Zhu Ying, Jia Xiao-Hong, Zhou Wei, Zhan Wei-Wei, Zhou Jian-Qiao
Department of Ultrasound, Shanghai Ruijin Hospital Affiliated to Medical School of Shanghai Jiaotong University, Shanghai, People's Republic of China.
Cancer Manag Res. 2020 Mar 18;12:2037-2045. doi: 10.2147/CMAR.S241815. eCollection 2020.
To test the value of qualitative virtual touch imaging quantification (VTIQ) features in differentiating benign from malignant breast lesions.
From November 2016 to August 2017, 230 lesions were subjected to conventional US and virtual touch imaging quantification before biopsy. The maximum shear wave velocity (SWVmax) was measured using a standardized method. Qualitative VTIQ features, including the "stiff rim" sign and color pattern classification, were assessed according to a binary classification. The sensitivity, specificity and area under the receiver operating curve (AUC) of Breast Imaging Reporting and Data System (BI-RADS), SWVmax, qualitative VTIQ features, and combined data were compared.
Among the 230 breast lesions, 150 were benign and 80 were malignant. Compared to the benign lesions, the malignant ones had higher SWVmax values and were more likely to show the "stiff rim" sign and VTIQ pattern 2 (P <0.001 for all). The AUC value was 0.885 for the qualitative VTIQ combination (the presence of the "stiff rim" sign and/or the display of VTIQ pattern 2), similar to that for SWVmax (P=0.472). BI-RADS combined with the qualitative VTIQ combination and with SWVmax yielded similar results, including significantly higher AUC values (P = 0.018 and 0.014, respectively), significantly higher specificities (P<0.001 for both), and nonsignificantly decreased sensitivities (P = 0.249 for both) compared to BI-RADS alone.
The dual-category classification of qualitative VTIQ features according to the presence of the "stiff rim" sign and/or the classification of VTIQ pattern 2 is a simple and useful method that may be representative of quantitative VTIQ parameters in the evaluation of breast masses.
检验定性虚拟触诊成像定量（VTIQ）特征在鉴别乳腺良恶性病变中的价值。
2016年11月至2017年8月，230个病变在活检前行常规超声和虚拟触诊成像定量检查。采用标准化方法测量最大剪切波速度（SWVmax）。根据二元分类评估定性VTIQ特征，包括“硬边”征和彩色模式分类。比较乳腺影像报告和数据系统（BI-RADS）、SWVmax、定性VTIQ特征及联合数据的灵敏度、特异度和受试者操作特征曲线下面积（AUC）。
230个乳腺病变中，150个为良性，80个为恶性。与良性病变相比，恶性病变的SWVmax值更高，更易出现“硬边”征和VTIQ模式２（均P<0.001）。定性VTIQ联合（存在“硬边”征和/或显示VTIQ模式２）的AUC值为0.885，与SWVmax的AUC值相似（P=0.472）。BI-RADS联合定性VTIQ联合及SWVmax产生相似结果，与单独使用BI-RADS相比，AUC值显著更高（分别为P = 0.018和0.014），特异度显著更高（均P<0.001），灵敏度无显著降低（均P = 0.249）。
根据“硬边”征的存在和/或VTIQ模式2的分类对定性VTIQ特征进行二元分类是一种简单有用的方法，在乳腺肿块评估中可能代表定量VTIQ参数。
