Noncancerous breast tissue and cancerous breast tissue have different elastic properties. In particular, cancerous breast tumors are stiff when compared to the noncancerous surrounding tissue. This difference in elasticity can be used as a means for detection through the method of elastographic tomosynthesis by means of physical modulation. This paper deals with a method to visualize elasticity of soft tissues, particularly breast tissues, via x-ray tomosynthesis. X-ray tomosynthesis is now used to visualize breast tissues with better resolution than the conventional single-shot mammography. The advantage of X-ray tomosynthesis over X-ray CT is that fewer projections are needed than CT to perform the reconstruction, thus radiation exposure and cost are both reduced. Two phantoms were used for the testing of this method, a physical phantom and an in silico phantom. The standard root mean square error in the tomosynthesis for the physical phantom was 2.093 and the error in the in silico phantom was negligible. The elastographs were created through the use of displacement and strain graphing. A Gaussian Mixture Model with an expectation–maximization clustering algorithm was applied in three dimensions with an error of 16.667%. The results of this paper have been substantial when using phantom data. There are no equivalent comparisons yet in 3D x-ray elastographic tomosynthesis. Tomosynthesis with and without physical modulation in the 3D elastograph can identify feature groupings used for biopsy. The studies have potential to be applied to human test data used as a guide for biopsy to improve accuracy of diagnosis results. Further research on this topic could prove to yield new techniques for human patient diagnosis purposes.

中文翻译：

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来自乳腺癌 X 射线应变成像的弹性成像断层合成

非癌性乳腺组织和癌性乳腺组织具有不同的弹性特性。特别是，与非癌性周围组织相比，癌性乳腺肿瘤是僵硬的。这种弹性差异可用作通过物理调制的弹性断层摄影合成方法进行检测的手段。本文介绍了一种通过 X 射线断层合成来可视化软组织，尤其是乳房组织的弹性的方法。X 射线断层合成现在用于以比传统单次乳房 X 光检查更好的分辨率显示乳房组织。X 射线断层合成相对于 X 射线 CT 的优势在于执行重建所需的投影比 CT 少，因此辐射暴露和成本都降低。两个体模用于测试该方法，一个物理幻影和一个 in silico 幻影。物理体模断层合成的标准均方根误差为 2.093，计算机体模的误差可以忽略不计。弹性图是通过使用位移和应变图创建的。在三个维度上应用了具有期望最大化聚类算法的高斯混合模型，误差为 16.667%。当使用幻像数据时，本文的结果是可观的。在 3D X 射线弹性成像断层合成中还没有等效的比较。在 3D 弹性成像仪中进行和不进行物理调制的断层合成可以识别用于活检的特征分组。这些研究有可能应用于人体测试数据，用作活检指南，以提高诊断结果的准确性。