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首页> 外文期刊>Acta Radiologica >Pattern classification of ShearWave Elastography images for differential diagnosis between benign and malignant solid breast masses.
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Pattern classification of ShearWave Elastography images for differential diagnosis between benign and malignant solid breast masses.

机译:ShearWave弹性成像图像的模式分类,可用于良性和恶性实性乳腺肿块之间的鉴别诊断。

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摘要

BACKGROUND: ShearWave Elastography (SWE) provides a quantitative measurement of tissue stiffness and may improve characterization of breast masses. However, the significance of Young's modulus measurements and appropriate SWE evaluation criteria has not been established yet. PURPOSE: To assess the usefulness of the pattern classification and Young's modulus measurements in the differential diagnosis between benign and malignant solid breast masses. MATERIAL AND METHODS: Ninety-six patients (age range 18-84 years, mean 54 years) with 100 solid breast masses who underwent tissue sampling after a US examination were analyzed. We tried to create a visual pattern classification based on the SWE images. After classifying the visual patterns, the Young's modulus of the lesions was measured in every case. RESULTS: It was possible to classify the images into four patterns by the visual evaluation: no findings (coded blue homogeneously; Pattern 1), vertical stripe pattern artifacts (Pattern 2), a localized colored area at the margin of the lesion (Pattern 3), and heterogeneously colored areas in the interior of the lesion (Pattern 4). There were 17 Pattern 1 lesions, 14 Pattern 2 lesions, 20 Pattern 3 lesions, and 49 Pattern 4 lesions. When Patterns 1 and 2 were assumed to be benign, and Patterns 3 and 4 were assumed to be malignant, the sensitivity and specificity were 91.3% (63/69) and 80.6% (25/31), respectively. The mean Young's modulus measurements of the benign and the malignant lesions were 42 kPa and 146 kPa, respectively (P < 0.0001). No significant differences were found between benign and malignant lesions in Pattern 3. In Pattern 4, however, the Young's modulus of the benign lesions (50 kPa) was lower than the smallest Young's modulus of malignant lesions (61 kPa). CONCLUSION: The visual pattern classification and adding Young's modulus measurements may improve characterization of solid breast masses.
机译:背景:ShearWave弹性成像(SWE)提供组织硬度的定量测量,并可能改善乳腺肿块的特征。但是,尚未确定杨氏模量测量和合适的SWE评估标准的重要性。目的:评估模式分类和杨氏模量测量在良性和恶性固体乳腺肿块鉴别诊断中的有用性。材料与方法:分析了96例100例乳腺肿块(年龄范围18-84岁,平均54岁)的患者,这些患者在美国检查后接受了组织采样。我们试图基于SWE图像创建视觉图案分类。在对视觉图案进行分类之后,在每种情况下都测量病变的杨氏模量。结果:有可能通过视觉评估将图像分为四个模式:无发现(均匀地编码为蓝色;模式1),垂直条纹模式伪像(模式2),病变边缘的局部彩色区域(模式3) ),以及病变内部的颜色不均一的区域(模式4)。模式1有17个病变,模式2有14个病变,模式3有20个病变,模式4有49个病变。当模式1和2被认为是良性的,而模式3和4被认为是恶性的时,敏感性和特异性分别为91.3%(63/69)和80.6%(25/31)。良性和恶性病变的平均杨氏模量测量分别为42 kPa和146 kPa(P <0.0001)。在模式3中,良性和恶性病变之间没有发现显着差异。但是在模式4中,良性病变的杨氏模量(50 kPa)低于最小的恶性病变的杨氏模量(61 kPa)。结论:视觉模式分类和增加的杨氏模量测量值可以改善乳腺实性肿块的特征。

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