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使用自动乳腺容积扫描仪比较回缩现象和BI-RADS-US描述符在鉴别乳腺良恶性肿块中的作用

Comparison of retraction phenomenon and BI-RADS-US descriptors in differentiating benign and malignant breast masses using an automated breast volume scanner.

作者信息

Zheng Feng-Yang, Yan Li-Xia, Huang Bei-Jian, Xia Han-Sheng, Wang Xi, Lu Qing, Li Cui-Xian, Wang Wen-Ping

机构信息

Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China.

Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai 200032, China; Fu Dan University Institute of Medical Ultrasound and Engineering, Shanghai 200032, China.

出版信息

Eur J Radiol. 2015 Nov;84(11):2123-9. doi: 10.1016/j.ejrad.2015.07.028. Epub 2015 Jul 30.

Abstract

OBJECTIVE

To compare the diagnostic values of retraction phenomenon in the coronal planes and descriptors in the Breast Imaging Reporting and Data System-Ultrasound (BI-RADS-US) lexicon in differentiating benign and malignant breast masses using an automated breast volume scanner (ABVS).

MATERIALS AND METHODS

Two hundred and eight female patients with 237 pathologically proven breast masses (120 benign and 117 malignant) were included in this study. ABVS was performed for each mass after preoperative localization by conventional ultrasonography (US). Multivariate logistic regression analysis was performed to assess independent variables for malignancy prediction. Diagnostic performance was evaluated through the receiver operating characteristic (ROC) curve analysis.

RESULTS

Retraction phenomenon (odds ratio [OR]: 76.70; 95% confidence interval [CI]: 12.55, 468.70; P<0.001) was the strongest independent predictor for malignant masses, followed by microlobulated margins (OR: 55.87; 95% CI: 12.56, 248.44; P<0.001), angular margins (OR: 36.44; 95% CI: 4.55, 292.06; P=0.001), calcifications (OR: 5.53; 95% CI: 1.34, 22.88; P=0.018,) and patient age (OR: 1.10; 95% CI: 1.03, 1.17; P=0.004). Mass shape, orientation, echo pattern, indistinct margins, spiculated margins, and mass size were not significantly associated with breast malignancy. Area under the ROC curve (Az) for microlobulated margins and retraction phenomenon was higher than that for other significant independent predictors. Az, sensitivity, and specificity were 0.877 (95% CI: 0.829, 0.926) and 0.838 (95% CI: 0.783, 0.892), 82.9% and 70.1%, and 92.5% and 98.3%, respectively, for microlobulated margins and retraction phenomenon.

CONCLUSIONS

Retraction phenomenon and microlobulated margins have high diagnostic values in the differentiation of benign and malignant breast masses using an ABVS.

摘要

目的

使用自动乳腺容积扫描仪(ABVS)比较冠状面退缩现象和乳腺影像报告和数据系统超声(BI-RADS-US)词典中的描述符在鉴别乳腺良恶性肿块中的诊断价值。

材料与方法

本研究纳入了208例女性患者,共237个经病理证实的乳腺肿块(120个良性,117个恶性)。在术前通过传统超声(US)对每个肿块进行定位后,使用ABVS进行检查。进行多因素逻辑回归分析以评估预测恶性肿瘤的独立变量。通过受试者操作特征(ROC)曲线分析评估诊断性能。

结果

退缩现象(优势比[OR]:76.70;95%置信区间[CI]:12.55,468.70;P<0.001)是恶性肿块最强的独立预测因素,其次是微叶状边缘(OR:55.87;95%CI:12.56,248.44;P<0.001)、角状边缘(OR:36.44;95%CI:4.55,292.06;P=0.001)、钙化(OR:5.53;95%CI:1.34,22.88;P=0.018)和患者年龄(OR:1.10;95%CI:1.03,1.17;P=0.004)。肿块形状、方向、回声模式、边界不清、毛刺状边缘和肿块大小与乳腺恶性肿瘤无显著相关性。微叶状边缘和退缩现象的ROC曲线下面积(Az)高于其他显著的独立预测因素。微叶状边缘和退缩现象 的Az、敏感性和特异性分别为0.877(95%CI:0.829,0.926)和0.838(95%CI:0.783,0.892)、82.9%和70.1%、92.5%和98.3%。

结论

使用ABVS时,退缩现象和微叶状边缘在鉴别乳腺良恶性肿块方面具有较高的诊断价值。

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