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BI-RADS®-US 4 类乳腺肿块的超声亚型分类简单规则。

Simple rules for ultrasonographic subcategorization of BI-RADS®-US 4 breast masses.

机构信息

Department of Obstetrics and Gynecology, Faculty of Medical Sciences, State University of Campinas - Unicamp, Campinas, São Paulo, Brazil.

出版信息

Eur J Radiol. 2013 Aug;82(8):1231-5. doi: 10.1016/j.ejrad.2013.02.032. Epub 2013 Mar 27.

Abstract

OBJECTIVES

To evaluate an objective method for ultrasonographic (US) subcategorization of BI-RADS(®)-US 4 breast masses based on clear and simple rules in order for woman to benefit from a more complete and homogeneous breast mass analysis.

METHODS

In this cross-sectional study, we selected 330 women, with 339 US breast masses, classified as BI-RADS(®)-US 4. Three physicians experienced in breast imaging independently reviewed all US images, assessing mass shape, margins, orientation, echo texture and vascularity. These experts further subdivided the masses into subcategories 4a, 4b and 4c, according to simple US rules. Inter-observer agreement was calculated for US features categories and for final subcategory assessment. We also estimated the positive predictive value (PPV) for BI-RADS(®)-US subcategories 4a, 4b and 4c assigned by each of the three observers.

RESULTS

Pathological examination of all masses confirmed 144 (42%) malignant and 195 (58%) benign tumors. Moderate agreement was obtained for mass shape, margins, vascularity and for final BI-RADS(®)-US 4 subcategory. Substantial agreement was obtained for the description of mass orientation and echo texture. The PPV for subcategories 4a, 4b and 4c were, 17%, 45% and 85%, respectively, for the first observer and 20%, 38% and 79% and 17%, 40% and 85% for the other two observers.

CONCLUSION

Standardization of a US subcategorization of BI-RADS(®)-US 4 breast masses seems to be feasible, with substantial inter-observer agreement and progressive increase in the PPV in the subcategories 4a, 4b and 4c, provided that clear and simple classification rules are defined.

摘要

目的

评估一种基于清晰简单规则的超声(US)BI-RADS(®)-US 4 乳腺肿块亚分类的客观方法,以便女性能够从更完整和同质的乳腺肿块分析中受益。

方法

在这项横断面研究中,我们选择了 330 名女性,共 339 个 US 乳腺肿块,分类为 BI-RADS(®)-US 4。三位经验丰富的乳腺影像学医生独立回顾了所有 US 图像,评估肿块形状、边缘、方位、回声纹理和血管。这些专家根据简单的 US 规则进一步将肿块细分为 4a、4b 和 4c 亚类。计算了 US 特征类别和最终亚类评估的观察者间一致性。我们还估计了三位观察者分别分配的 BI-RADS(®)-US 亚类 4a、4b 和 4c 的阳性预测值(PPV)。

结果

所有肿块的病理检查均证实 144 个(42%)为恶性肿瘤,195 个(58%)为良性肿瘤。肿块形状、边缘、血管和最终 BI-RADS(®)-US 4 亚类的评估获得了中度一致性。肿块方位和回声纹理的描述获得了高度一致性。第一位观察者的亚类 4a、4b 和 4c 的 PPV 分别为 17%、45%和 85%,另外两位观察者的 PPV 分别为 20%、38%和 79%和 17%、40%和 85%。

结论

BI-RADS(®)-US 4 乳腺肿块的 US 亚分类似乎可以标准化,具有相当的观察者间一致性,并随着亚类 4a、4b 和 4c 的 PPV 逐渐增加,只要定义了清晰简单的分类规则。

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