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目的 :探讨自动乳腺全容积成像冠状面特征对改良BI-RADS分类的临床价值。方法:对201个BI-RADS分类为3~5类的乳腺肿块进行回顾性分析,所有的肿块术前均行常规彩超与自动乳腺全容积成像(ABVS)检查,用BI-RADS分类的标准化术语描述乳腺肿块的各种信息,并记录ABVS冠状面图像上肿块的完整界面回声、“汇聚征”、成角、毛刺,最后进行BI-RADS分类。结果:ABVS冠状面的汇聚征、完整界面回声、成角、毛刺在良恶性肿块鉴别上差异均有显著性(P<0.000 1)。ABVS的汇聚征诊断乳腺恶性肿块的敏感性为68.2%,特异性为93.4%,准确性为82.0%。常规超声联合ABVS冠状面特征改良BI-RADS分类后显示:3类的恶性率由8.5%降为3.2%,4a类的恶性率由25.2%降低为12.1%,5类的恶性率由94.2%升为98.0%。结论:ABVS的汇聚征可作为预测乳腺恶性肿块的有意义的独立指标;彩超联合ABVS有助于提高超声BI-RADS分类的准确性。
Objective: To investigate the clinical value of automatic breast total volume imaging coronary angiography in improving the classification of BI-RADS. Methods: 201 breast masses with BI-RADS classification of 3 to 5 were retrospectively analyzed. All the masses were examined by conventional color Doppler ultrasound and automatic breast total volumetric imaging (ABVS) before surgery. The standardized terms classified by BI-RADS Describe a variety of breast lump information and record the complete interface echo of the lump on the ABVS coronal image, “Convergence ”, angulation, glitches, and finally BI-RADS classification. Results: There were significant differences in the differential diagnosis of benign and malignant tumors between the ABVS coronal plane echo, intact interface echo, angulation and burr (P <0.000 1). The sensitivity of ABVS for the diagnosis of breast malignancy was 68.2%, specificity was 93.4% and accuracy was 82.0%. Conventional ultrasound combined with ABVS coronal features improved BI-RADS classification showed: three types of malignant rate decreased from 8.5% to 3.2%, 4a type of malignancy decreased from 25.2% to 12.1%, 5 categories of malignancy increased from 94.2% Is 98.0%. CONCLUSIONS: The ABVS confluence can be used as a significant independent predictor of breast malignancy. The combination of color Doppler ultrasonography and ABVS can improve the accuracy of the ultrasound BI-RADS classification.