Department of Medical Physics, University of Wisconsin, Madison, Wisconsin, USA.
Ultrasound Division, GE Healthcare, Wauwatosa, Wisconsin, USA.
Ultrasound Med Biol. 2019 Dec;45(12):3145-3159. doi: 10.1016/j.ultrasmedbio.2019.08.013. Epub 2019 Sep 21.
Non-linear mechanical properties of breast tissue can be employed to diagnose and differentiate breast tumors. To obtain such non-linear mechanical properties, it is necessary to track tissue motion under large deformation. In this study, a multi-compression strategy was utilized to produce large tissue deformation, and a method to estimate 3-D motion of tissue under large deformation was introduced. Given multiple volumes of ultrasound data, the proposed method first estimates volume-to-volume incremental displacements using a 3-D region-growing motion-tracking method. Then, possible outliers among all incremental displacements are removed to avoid error accumulation. Once large displacement errors have been removed, all incremental displacements are registered together to obtain accumulated displacements under large tissue deformation (e.g., >10%). The proposed method was tested with one set of in vivo tumor-bearing ultrasound data acquired from a human subject. A total of 10 small-strain deformation steps were performed to obtain the final accumulated displacement field, in which the breast lesion and its surrounding were deformed by approximately 6% and 16%, respectively. The contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) of the elasticity images obtained with the proposed method were all higher than those obtained with a 2-D tracking method. Furthermore, in three orthogonal views of accumulated axial strain images, the breast lesion was clearly visible with good correspondence between the axial strain and B-mode images.
乳腺组织的非线性力学特性可用于诊断和区分乳腺肿瘤。为了获得这些非线性力学特性,有必要跟踪大变形下的组织运动。在本研究中,采用多压缩策略产生大的组织变形,并引入了一种估计大变形下组织三维运动的方法。对于多组超声数据,该方法首先使用三维区域生长运动跟踪方法估计体素间的增量位移。然后,去除所有增量位移中的异常值,以避免误差累积。一旦消除了大位移误差,就可以将所有增量位移一起注册,以获得大组织变形(例如,>10%)下的累积位移。该方法在一组从人体获得的肿瘤超声数据上进行了测试。共进行了 10 次小应变变形步骤,以获得最终的累积位移场,其中乳腺病变及其周围组织的变形分别约为 6%和 16%。与二维跟踪方法相比,所提出方法获得的弹性图像的对比度噪声比(CNR)和信噪比(SNR)均更高。此外,在累积轴向应变图像的三个正交视图中,乳腺病变清晰可见,轴向应变与 B 模式图像之间具有良好的对应关系。