Neuroscience Research Australia, Sydney, NSW, Australia; School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, NSW, Australia.
School of Biomedical Engineering and Imaging Sciences, The Rayne Institute, King's College London, SE1 7EH, London, United Kingdom.
Med Image Anal. 2021 Dec;74:102212. doi: 10.1016/j.media.2021.102212. Epub 2021 Sep 20.
Elastography has become widely used clinically for characterising changes in soft tissue mechanics that are associated with altered tissue structure and composition. However, some soft tissues, such as muscle, are not isotropic as is assumed in clinical elastography implementations. This limits the ability of these methods to capture changes in anisotropic tissues associated with disease. The objective of this study was to develop and validate a novel elastography reconstruction technique suitable for estimating the linear viscoelastic mechanical properties of transversely isotropic soft tissues. We derived a divergence-free formulation of the governing equations for acoustic wave propagation through a linearly transversely isotropic viscoelastic material, and transformed this into a weak form. This was then implemented into a finite element framework, enabling the analysis of wave input data and tissue structural fibre orientations, in this case based on diffusion tensor imaging. To validate the material constants obtained with this method, numerous in silico phantom experiments were run which encompassed a range of variations in wave input directions, material properties, fibre structure and noise. The method was also tested on ex vivo muscle and in vivo human volunteer calf muscles, and compared with a previous curl-based inversion method. The new method robustly extracted the transversely isotropic shear moduli (G, G, G) from the in silico phantom tests with minimal bias, including in the presence of experimentally realistic levels of noise in either fibre orientation or wave data. This new method performed better than the previous method in the presence of noise. Anisotropy estimates from the ex vivo muscle phantom agreed well with rheological tests. In vivo experiments on human calf muscles were able to detect increases in muscle shear moduli with passive muscle stretch. This new reconstruction method can be applied to quantify tissue mechanical properties of anisotropic soft tissues, such as muscle, in health and disease.
弹性成像是一种广泛应用于临床的技术，用于描述与组织结构和组成改变相关的软组织力学变化。然而，一些软组织，如肌肉，并不是各向同性的，这与临床弹性成像实施中的假设不同。这限制了这些方法捕捉与疾病相关的各向异性组织变化的能力。本研究的目的是开发和验证一种新的弹性成像重建技术，该技术适用于估计各向异性软组织的线性粘弹性力学特性。我们推导出了线性横向各向同性粘弹性材料中声波传播的控制方程的无散度公式，并将其转化为弱形式。然后将其实现到有限元框架中，从而能够分析波输入数据和组织结构纤维方向，在这种情况下，基于扩散张量成像。为了验证通过该方法获得的材料常数，进行了大量的数值模拟实验，涵盖了波输入方向、材料特性、纤维结构和噪声的变化范围。该方法还在离体肌肉和体内人类志愿者小腿肌肉上进行了测试，并与以前的卷曲反演方法进行了比较。新方法从数值模拟实验中稳健地提取了横向各向异性剪切模量（G、G、G），具有最小的偏差，包括在纤维方向或波数据中存在实际实验水平的噪声时也是如此。在存在噪声的情况下，新方法的性能优于以前的方法。离体肌肉模型的各向异性估计与流变学测试吻合良好。对人体小腿肌肉的活体实验能够检测到被动肌肉拉伸时肌肉剪切模量的增加。这种新的重建方法可用于量化各向异性软组织（如肌肉）的组织力学特性，无论是在健康还是疾病状态下。
