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BI-RADS 分类联合自动乳腺容积扫描仪和剪切波弹性成像对乳腺病变的诊断意义。

The Diagnostic Significance of the BI-RADS Classification Combined With Automated Breast Volume Scanner and Shear Wave Elastography for Breast Lesions.

机构信息

Department of Medical Ultrasound, Ma'anshan People's Hospital, Ma'anshan, China.

Department of Radiology, Nanjing Gaochun People's Hospital, Nanjing, China.

出版信息

J Ultrasound Med. 2023 Jul;42(7):1459-1469. doi: 10.1002/jum.16154. Epub 2022 Dec 19.

Abstract

OBJECTIVE

We herein compared the diagnostic accuracy of the BI-RADS, ABVS, SWE, and combined techniques for the classification of breast lesions.

METHODS

Breast lesions were appraised using the BI-RADS classification system as well as the combinations of BI-RADS plus ABVS (BI-RADS + ABVS) and BI-RADS plus SWE (BI-RADS + SWE), and both methods (BI-RADS + ABVS + SWE) by two specialties Medical Ultrasound physician. The Fisher's exact and χ tests were performed to compare the degree of malignancy for the various methods with a pathology ground truth. Receiver operating characteristic curves (ROC) were generated and the corresponding area under the curve (AUC) values were determined to test the diagnostic efficacy of the various methods and identify the optimal SWE cut-off indicative of malignancy.

RESULTS

The incidence of the retraction phenomenon on ABVS images of the malignant group was significantly higher (P < .001) than that of the benign group. The specificity, sensitivity, and positive and negative predictive values of the BI-RADS classification were 88.72, 79.38, 83.70, and 85.50%, respectively. BI-RADS plus SWE-Max exhibited enhanced specificity, sensitivity, and positive and negative predictive values of 88.72, 92.78, 85.70, and 94.40%, respectively. Similarly, when BI-RADS + ABVS was utilized, the sensitivity and negative predictive value increased to 95.88 and 96.40%, respectively. BI-RADS + ABVS + SWE possessed the highest overall sensitivity (96.91%), specificity (94.74%), and positive (93.10%) and negative (97.70%) predictive values from all four indices.

CONCLUSION

ABVS and SWE can reduce the subjectivity of BI-RADS. As a result, BI-RADS + ABVS + SWE resulted in the best diagnostic accuracy.

摘要

目的

本研究旨在比较 BI-RADS、ABVS、SWE 及联合技术在乳腺病变分类中的诊断准确性。

方法

应用 BI-RADS 分类系统及 BI-RADS 联合 ABVS(BI-RADS+ABVS)、BI-RADS 联合 SWE(BI-RADS+SWE)两种方法评估乳腺病变,两名医学超声专业医生均采用 BI-RADS、BI-RADS+ABVS+SWE 两种方法进行评估。采用 Fisher 确切检验和 χ 检验比较不同方法与病理金标准之间的恶性程度。绘制受试者工作特征曲线(ROC),并确定相应的曲线下面积(AUC)值,以检验各种方法的诊断效能,并确定最佳的 SWE 截断值以指示恶性程度。

结果

恶性组 ABVS 图像回缩现象的发生率显著高于良性组(P<0.001)。BI-RADS 分类的特异性、敏感性、阳性预测值和阴性预测值分别为 88.72%、79.38%、83.70%和 85.50%。BI-RADS+SWE-Max 表现出增强的特异性、敏感性、阳性预测值和阴性预测值,分别为 88.72%、92.78%、85.70%和 94.40%。同样,当使用 BI-RADS+ABVS 时,敏感性和阴性预测值分别提高到 95.88%和 96.40%。BI-RADS+ABVS+SWE 在四项指标中的总敏感性(96.91%)、特异性(94.74%)、阳性预测值(93.10%)和阴性预测值(97.70%)最高。

结论

ABVS 和 SWE 可降低 BI-RADS 的主观性。因此,BI-RADS+ABVS+SWE 可获得最佳的诊断准确性。

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