在传统的基于线性阵列(CLA)的弹性成像中,在一个方向上压缩组织(例如,轴向)导致所有其他方向的扩张(横向,海拔)。因此,横向位移和应变的估计可以提供关于组织机械性能的附加信息。然而,由于横向采样的固有限制,这些没有得到充分利用。最近,演示了一种名为执行器辅助光束平移(ABT)的方法来解决这个问题,其中使用外部台式装置在亚间距位置平移聚焦光束。然而,因为这种台式设置对于常规临床使用可能不切实际,超声换能器被定制为具有内部致动器。通过旋转弹性成像应用体模的实验研究了定制换能器的性能,这需要精确的横向位移估计。此外,将从ABT获得的结果与当前实践的空间位移复合(SDC)方法进行了比较,已知比传统方法产生质量更好的横向位移估计。结果表明,ABT方法产生全宽半最大值(FWHM)值,取自穿过点散射体的横向剖面,比使用CLA和SDC方法获得的小65%和24%,分别。此外,使用ABT方法获得的旋转弹性图估计的对比度噪声比(CNR)比使用CLA和SDC方法获得的要好300%和35%,分别。此外,结果表明,与空间复合方法相比,ABT方法具有更大的视场(FoV)的额外优势。
In conventional linear array (CLA)-based elastography tissue compression in one direction (e.g., axial) leads to an expansion in all other directions (lateral, elevation). Therefore, the estimation of the lateral displacements and strains may provide additional information on the tissue mechanical properties. However, these are not exploited fully due to the inherent limitation in lateral sampling. Recently, a method named actuator-assisted beam translation (ABT) was demonstrated to address this issue, wherein the focused beam was translated at subpitch locations using an external bench-top setup. However, because such bench-top setup may be impractical for routine clinical use, an ultrasound transducer was customized to have an internal actuator. The performance of the customized transducer was studied through experiments on phantoms for rotation elastography application, which requires precise lateral displacement estimation. Furthermore, the results obtained from ABT was compared against the currently practiced spatial displacement compounding (SDC) method, which is known to yield better quality lateral displacement estimates than conventional approaches. The results show that the ABT method yields a full-width half-maximum (FWHM) value, taken from the lateral profile across a point scatterer, which is 65% and 24% smaller than that obtained using CLA and SDC methods, respectively. Furthermore, the contrast-to-noise ratio (CNR) estimated from rotation elastogram obtained using ABT method is better by 300% and 35% compared with that obtained by using CLA and SDC methods, respectively. Furthermore, the results demonstrate an additional advantage of having larger field of view (FoV) for the ABT method compared with spatial compounding approach.