Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, QC, Canada; Institute of Biomedical Engineering, University of Montreal, Montréal, QC, Canada.
Laboratory of Biorheology and Medical Ultrasonics, University of Montreal Hospital Research Center (CRCHUM), Montréal, QC, Canada.
Ultrasonics. 2019 Jan;91:77-91. doi: 10.1016/j.ultras.2018.07.012. Epub 2018 Jul 21.
Polar strain (radial and circumferential) estimations can suffer from artifacts because the center of a nonsymmetrical carotid atherosclerotic artery, defining the coordinate system in cross-sectional view, can be misregistered. Principal strains are able to remove coordinate dependency to visualize vascular strain components (i.e., axial and lateral strains and shears). This paper presents two affine model-based estimators, the affine phase-based estimator (APBE) developed in the framework of transverse oscillation (TO) beamforming, and the Lagrangian speckle model estimator (LSME). These estimators solve simultaneously the translation (axial and lateral displacements) and deformation (axial and lateral strains and shears) components that were then used to compute principal strains. To improve performance, the implemented APBE was also tested by introducing a time-ensemble estimation approach. Both APBE and LSME were tested with and without the plane strain incompressibility assumption. These algorithms were evaluated on coherent plane wave compounded (CPWC) images considering TO. LSME without TO but implemented with the time-ensemble and incompressibility constraint (Porée et al., 2015) served as benchmark comparisons. The APBE provided better principal strain estimations with the time-ensemble and incompressibility constraint, for both simulations and in vitro experiments. With a few exceptions, TO did not improve principal strain estimates for the LSME. With simulations, the smallest errors compared with ground true measures were obtained with the LSME considering time-ensemble and the incompressibility constraint. This latter estimator also provided the highest elastogram signal-to-noise ratios (SNRs) for in vitro experiments on a homogeneous vascular phantom without any inclusion, for applied strains varying from 0.07% to 4.5%. It also allowed the highest contrast-to-noise ratios (CNRs) for a heterogeneous vascular phantom with a soft inclusion, at applied strains from 0.07% to 3.6%. In summary, the LSME outperformed the implemented APBE, and the incompressibility constraint improved performances of both estimators.
极应变(径向和周向)估计可能会受到伪影的影响,因为非对称颈动脉粥样硬化动脉的中心(定义了横截面坐标系)可能会错位。主应变能够消除坐标依赖性,以可视化血管应变分量(即轴向和侧向应变和剪切)。本文提出了两种仿射模型基估计器,即基于横向振荡(TO)波束形成的仿射相位基估计器(APBE)和拉格朗日散斑模型估计器(LSME)。这些估计器同时求解平移(轴向和侧向位移)和变形(轴向和侧向应变和剪切)分量,然后用于计算主应变。为了提高性能,还对实现的 APBE 进行了测试,引入了时间集合估计方法。APBE 和 LSME 都在考虑 TO 的情况下进行了有无平面应变不可压缩性假设的测试。这些算法在相干平面波复合(CPWC)图像上进行了评估,考虑了 TO。LSME 没有 TO,但实现了时间集合和不可压缩性约束(Porée 等人,2015 年)作为基准比较。APBE 在考虑时间集合和不可压缩性约束时,提供了更好的主应变估计,无论是在模拟还是在体外实验中。除了少数例外,TO 并没有提高 LSME 的主应变估计。通过模拟,与地面真实测量相比,考虑到时间集合和不可压缩性约束的 LSME 获得了最小的误差。在没有任何包含物的均匀血管仿体上进行的体外实验中,对于从 0.07%到 4.5%的应用应变,该估计器还提供了最高的弹性图信号噪声比(SNR)。对于具有软包含物的异质血管仿体,它还在从 0.07%到 3.6%的应用应变下提供了最高的对比噪声比(CNR)。总之,LSME 的性能优于实现的 APBE,不可压缩性约束提高了两个估计器的性能。