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B-Mode Ultrasound Combined with Color Doppler and Strain Elastography in the Diagnosis of Non-mass Breast Lesions: A Prospective Study

机译:B模式超声结合彩色多普勒和菌株弹性术在诊断非质量乳腺病变中:一项潜在研究

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Abstract Non-mass breast lesions on ultrasound (US) are areas without an associated mass. The purpose of this study was to evaluate whether combining B-mode US with color Doppler US and strain elastography (SE) improves US differentiation between benign and malignant non-mass breast lesions and the decision for biopsy. In this prospective study, three different radiologists analyzed the US images of 77 non-mass lesions independently and recorded Breast Imaging Reporting and Data System (BI-RADS) categories for four data sets. The image characteristics and BI-RADS categories of the four data sets were analyzed by another radiologist. The final diagnosis was made on the basis of pathologic findings. Values for area under the receiver operating curve (AUC), sensitivity, specificity and accuracy were compared among the data sets. The AUC of B-mode US combined with both color Doppler US and SE was greater than that of B-mode US alone (0.666 vs. 0.828) ( p ?=?0.011). The specificity of making the decision for biopsy increased from 6.5% to 38.7% when B-mode US was combined with color Doppler and SE, without a statistically significant change in sensitivity ( p ??0.001). Combined use of color Doppler and SE could improve the diagnostic value of B-mode US in distinguishing benign from malignant non-mass breast lesions and the specificity of making the decision for biopsy of non-mass breast lesions. ]]>
机译:摘要超声波(US)上的非质量乳房病变是没有相关质量的区域。本研究的目的是评估与颜色多普勒美国和菌株弹性摄影(SE)的组合B模式是否改善了良性和恶性非质量乳房病变与活检的决定之间的差异。在这项前瞻性研究中,三个不同的放射科医生独立分析了美国77个非质量病变的美国图像,并记录了四个数据集的乳房成像报告和数据系统(BI-RADS)类别。通过另一个放射科医生分析了四种数据集的图像特征和BI-RADS类别。最终诊断是在病理发现的基础上进行的。在数据集中比较了接收器操作曲线(AUC)下的区域的值,灵敏度,特异性和准确度。 B模式US的AUC与彩色多普勒US和SE相结合的大于B模式US(0.666 Vs. 0.828)(P?= 0.011)。当B模式美国与彩色多普勒和SE组合时,使活组织检查决定的特异性从6.5%增加到38.7%,而没有统计学上显着的敏感性变化(p≤≤0.001)。彩色多普勒和SE的结合使用可以提高B模式我们在区分恶性非质量乳腺病变中的诊断价值以及作出非质量乳腺病变活检决定的特异性。 ]]>

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