探讨声触诊组织成像定量技术（VTIQ）联合乳腺影像报告和数据系统（BI-RADS）分类对乳腺良、恶性病变的诊断价值。

回顾性选取2016年8月至2017年4月在哈尔滨医科大学附属第一医院就诊并获得病理结果的172例患者共172个乳腺病变，172例乳腺病变患者均行常规超声检查及BI-RADS分类，并行弹性成像检查，采用VTIQ模式，获得质量模式图及速度模式图，每个病变记录7组剪切波速度（SWV）测值，取平均值。以病理结果为"金标准"，绘制VTIQ、BI-RADS分类方法及VTIQ联合BI-RADS分类方法诊断乳腺良、恶性病变的ROC曲线，计算曲线下面积并确定最佳诊断界值，分析比较3种方法取最佳诊断界值时的诊断效能。并对BI-RADS分类、VTIQ联合BI-RADS分类计算得出的乳腺病变活检率进行比较分析。

BI-RADS分类的ROC曲线下面积为0.762，最佳诊断界值为BI-RADS 3与4a类之间；VTIQ（SWV平均值）的ROC曲线下面积为0.895，最佳诊断界值为3.13 m/s；VTIQ联合BI-RADS分类的ROC曲线下面积为0.908，显著高于BI-RADS分类法的0.762（Z=5.79，P<0.01）。由ROC曲线得出VTIQ联合BI-RADS分类法的最佳诊断界值为BI-RADS 4a与4b类之间，其灵敏度、特异度、阳性预测值、阴性预测值和准确性分别为92.9%、88.8%、80.0%、96.3%和90.1%，与BI-RADS分类相比较，其诊断的特异度提高了32.8%，准确性提高了20.9%，阳性预测值提高了28.6%。116例良性病变中，根据BI-RADS分类计算，需要进行活检的为51例（51/116，43.9%）；根据VTIQ联合BI-RADS分类计算，需进一步活检的为16例（16/116，13.8%），活检率较BI-RADS分类法降低，差异有统计学意义（χ²=25.71，P=0.00）。

VTIQ技术联合BI-RADS分类对乳腺良、恶性病变具有较好的诊断效能，与BI-RADS分类比较，其有助于提高诊断的特异度及准确性，且可降低良性病变临床活检率，减少不必要的临床干预，可将弹性成像技术作为常规超声BI-RADS分类的有效补充和辅助诊断方法。

To assess the diagnostic value of virtual touch imaging quantification (VTIQ) technique combined with breast imaging reporting and data system (BI-RADS) classification for benign and malignant breast lesions.

A total of 172 breast lesions were selected from 172 patients who were admitted to the First Affiliated Hospital of Harbin Medical University from August 2016 to April 2017, and all the lesions were first examined by US and classified by BI-RADS, and then examined by elastograpy. Using the VTIQ mode, we can obtain both the quality mode map and the speed mode map, and record seven sets of SWV values for each lesion to calculate the average. Using the pathological results as the gold standard, the receiver operating characteristic (ROC) curves of VTIQ, BI-RADS classification method, and VTIQ combined with BI-RADS classification method in the identification of benign and malignant breast lesions were plotted to calculate the area under the curve and determine the cut-off value. The diagnostic efficacy of the three methods was compared. The biopsy rates of breast lesions calculated by BI-RADS classification and VTIQ combined with BI-RADS classification were also compared and analyzed.

The area under the ROC curve of the BI-RADS classification was 0.762, and the best diagnostic boundary value was between BI-RADS 3 and 4a classification. The area under the ROC curve of VTIQ (SWV average) was 0.895, and the optimal diagnostic cut-off value was 3.13 m/s. The area under the ROC curve of the VTIQ combined with the BI-RADS classification was 0.908, which was significantly higher than that of the BI-RADS classification (Z=5.79, P<0.01). According to the ROC curve, the best diagnostic boundary value of VTIQ combined with BI-RADS classification was between BI-RADS 4a and 4b, and the sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 92.9%, 88.8%, 80.0%, 96.3%, and 90.1%, respectively. Compared with the BI-RADS classification, the diagnostic specificity, accuracy, and positive predictive value of the VTIQ combined with the BI-RADS classification increased by 32.8%, 20.9%, and 28.6%, respectively. According to the BI-RADS classification, there were 51 cases requiring biopsy among the 116 benign lesions (51/116, 43.9%), and there were only 16 patients requiring further biopsy according to the VTIQ combined with BI-RADS classification (16/116, 13.8%). There was a significant difference in the biopsy rate between them (χ²=25.71, P=0.00).

VTIQ technology combined with BI-RADS classification shows good diagnostic performance for benign and malignant breast lesions. Compared with BI-RADS classification alone, VTIQ technology combined with BI-RADS classification can improve the specificity and accuracy of diagnosis and reduce the clinical biopsy rate of benign lesions and unnecessary clinical interventions. Elasticity imaging technique can be used as an effective supplement and an auxiliary diagnostic method for the conventional ultrasound BI-RADS classification.