用于乳腺实性良恶性肿块鉴别诊断的剪切波弹性成像（ShearWave™ Elastography）图像模式分类
Pattern classification of ShearWave™ Elastography images for differential diagnosis between benign and malignant solid breast masses.
作者信息
Tozaki Mitsuhiro, Fukuma Eisuke
机构信息
Division of Breast Imaging, Breast Center, Kameda Medical Center, Kamogawa, Chiba, Japan.
出版信息
Acta Radiol. 2011 Dec 1;52(10):1069-75. doi: 10.1258/ar.2011.110276. Epub 2011 Oct 19.
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.
背景
剪切波弹性成像（SWE）可对组织硬度进行定量测量，可能有助于改善乳腺肿块的特征描述。然而，杨氏模量测量的意义以及合适的SWE评估标准尚未确立。
目的
评估模式分类和杨氏模量测量在乳腺实性良恶性肿块鉴别诊断中的作用。
材料与方法
分析96例（年龄范围18 - 84岁，平均54岁）经超声检查后进行组织采样的100个乳腺实性肿块患者。我们试图基于SWE图像创建一种视觉模式分类。在对视觉模式进行分类后，对每个病例的病变杨氏模量进行测量。
结果
通过视觉评估可将图像分为四种模式：无异常发现（均匀编码为蓝色；模式1）、垂直条纹状伪像（模式2）、病变边缘的局部彩色区域（模式3）以及病变内部的不均匀彩色区域（模式4）。模式1病变有17个，模式2病变有14个，模式3病变有20个，模式4病变有49个。当假定模式1和模式2为良性，模式3和模式4为恶性时，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值分别为42 kPa和146 kPa（P < 0.0001）。模式3的良性和恶性病变之间未发现显著差异。然而，在模式4中，良性病变的杨氏模量（50 kPa）低于恶性病变的最小杨氏模量（61 kPa）。
结论
视觉模式分类并结合杨氏模量测量可能有助于改善乳腺实性肿块的特征描述。
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