Taslidere Ezgi, Cohen Fernand S, Georgiou Georgia
Drexel Univ., Philadelphia, PA 19104, USA.
IEEE Trans Ultrason Ferroelectr Freq Control. 2008 Jan;55(1):50-63. doi: 10.1109/TUFFC.2008.616.
Visual inspection of ultrasound is diagnostically limited for characterizing breast tissue, in particular when it comes to visually detecting hyperplasia that forms in the ducts at its early formation (at submillimeter resolution) stages. It can, of course, be seen using biopsies. But this will not be done unless the areas have been flagged using noninvasive modalities. The aim of this paper is to draw to the attention of the medical community (albeit through simulations) that the continuous wavelet transform decomposition (CWTD) that was proven in vivo for tissue characterization before has the potential to flag out simulated hyperplasia data at submillimeter resolutions. And it might be an excellent candidate for detecting in vivo hyperplastic changes in the breast. To the best of our knowledge, this is the first attempt at studying the potential of detecting cell growth in breast ducts using ultrasound. The stochastic decomposition model (the CWTD) of the RF echo with its coherent and diffuse components, yields image parameters that correlate closely with the structural parameters of the (simulated) hyperplastic stages of the breast tissue. The discrimination power of the various parameters is studied under a host of conditions, such as varying resolution, depth, and coherent to diffuse energy ratio (CDR) values using a point-scatterer model simulator that mimics epithelium hyperplastic growth in the breast ducts. These are shown to be useful for detecting the various types of simulated hyperplastic data. Careful analysis shows that three parameters, in particular the number of coherent scatterers, the Rayleigh scattering degree, and the energy of the diffuse scatterers, are most sensitive to variations in the hyperplastic simulated data. And they show very high ability to discriminate between various stages of simulated hyperplasia, even in cases of low resolution and low CDR values. Using the area under the receiver operating characteristics (ROC) curve (A(z)) as the performance metric, values of A(z) > 0.942 are obtained when discriminating between stages for resolution <or= 0.4 mm, even for low CDR values. Then it drops below the 0.9 range as the resolution exceeds the 0.4-mm range. A nonparametric segmentation method to extract ductal areas from breast scans is presented to be used as a pre-step before classification of hyperplastic stages in breast ducts. This is a necessary step for segmenting the RF scan into ductal versus nonductal areas from breast scans. This is tested using breast tissue mimicking phantom data resulting values of A(z) > 0.948 for different duct densities.
超声的视觉检查在表征乳腺组织方面存在诊断局限性，尤其是在目视检测导管早期形成阶段（亚毫米分辨率）形成的增生时。当然，可以通过活检看到。但除非使用非侵入性方法标记出这些区域，否则不会进行活检。本文的目的是引起医学界的关注（尽管是通过模拟），即之前已在体内证明可用于组织表征的连续小波变换分解（CWTD）有潜力在亚毫米分辨率下标记出模拟增生数据。它可能是检测乳腺体内增生变化的极佳候选方法。据我们所知，这是首次尝试研究使用超声检测乳腺导管中细胞生长的潜力。具有相干和漫射分量的射频回波的随机分解模型（CWTD）产生的图像参数与乳腺组织（模拟）增生阶段的结构参数密切相关。使用模拟乳腺导管上皮增生生长的点散射体模型模拟器，在多种条件下研究了各种参数的辨别能力，例如分辨率、深度和相干与漫射能量比（CDR）值的变化。结果表明这些参数对于检测各种类型的模拟增生数据很有用。仔细分析表明，特别是相干散射体数量、瑞利散射程度和漫射散射体能量这三个参数对模拟增生数据的变化最为敏感。即使在低分辨率和低CDR值的情况下，它们在区分模拟增生的不同阶段方面也表现出很高的能力。使用接收器操作特征（ROC）曲线下面积（A(z)）作为性能指标，在分辨率≤0.4 mm时区分不同阶段，即使对于低CDR值，也能获得A(z)>0.942的值。当分辨率超过0.4 mm范围时，它会降至0.9范围以下。提出了一种从乳腺扫描中提取导管区域的非参数分割方法，用作乳腺导管增生阶段分类之前的预处理步骤。这是将射频扫描从乳腺扫描中分割为导管区域和非导管区域的必要步骤。使用模拟乳腺组织的体模数据对其进行测试，对于不同的导管密度，得到的A(z)>0.948的值。
