Enhanced complex local frequency elastography method for tumor viscoelastic shear modulus reconstruction
Enhanced complex local frequency elastography method for tumor viscoelastic shear modulus reconstruction
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DOI：
10.1016/j.cmpb.2020.105605
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发表时间：
2020-10-01
影响因子：
6.1
通讯作者：
Shan, Xiang
中科院分区：
文献类型：
--
作者：
Hu, Liangliang;Shan, Xiang
背景和目标：马约诊所提供名为MRE Wave的磁共振（MR）弹性成像软件，该软件使用传统的局部频率弹性成像（LFE）方法。然而，MRE Wave无法为弹性成像提供复杂的粘弹性图。我们试图改进LFE中使用的局部频率估计算法，我们称之为增强型复杂局部频率弹性成像（EC-LFE）algorithm.Methods：该算法使用线性，各向同性和局部均匀的假设下的波动方程。使用两个二维仿真模型来研究EC-LFE算法检测小肿瘤的准确性和灵敏度。相应的统计学参数为相对均方根（RMS）误差和对比噪声比（CNR）。用两个不同的参数集研究EC-LFE，一个具有最佳选择的参数xi（简称EC-LFE Adj），另一个具有xi = 0（EC-LFE 0）。结果：MRE Wave软件的弹性均方根误差约为1%，EC-LFE 0和EC-LFE Adj软件的弹性均方根误差约为0.2%。MRE Wave软件的弹性标准差约为平均值的3%，EC-LFE 0和EC-LFE Adj的弹性标准差约为平均值的1%。EC-LFE 0的弹性CNR值在小肿瘤区域（小于10点采样）达到MRE波的1.93倍。结论：与传统方法相比，EC-LFE 0方法对小肿瘤的检测更准确、灵敏，且具有更高的抗干扰能力。改进后的算法输出更多参数，性能优于MRE Wave，从而使其更适合临床应用。(C)2020爱思唯尔B. V.保留所有权利。
Background and objectives: The Mayo Clinic provides a magnetic resonance (MR) elastography software named MRE Wave, which uses the conventional local frequency elastography (LFE) method. However, MRE Wave is unable to supply complex viscoelasticity maps for elastography. We sought to improve the local frequency estimation algorithm used in LFE, which we refer to as the Enhanced Complex Local Frequency Elastography (EC-LFE) algorithm.Methods: The proposed algorithm uses wave equations under the hypotheses of being linear, isotropic, and locally homogeneous. Two 2D simulation models were used to investigate the accuracy and sensitivity of the EC-LFE algorithm for detecting small tumors. The corresponding statistical parameters were the relative root mean square (RMS) error and contrast-to-noise ratio (CNR). EC-LFE was investigated with two different parameter sets, one with an optimally chosen parameter xi (EC-LFE Adj, for short) and the other with xi = 0 (EC-LFE0). We compared the MRE Wave and the EC-LFE using series signal-to-noise (SNR) wave data.Results: The elasticity RMS error of the MRE Wave software was about 1%, and that of the EC-LFE0 and EC-LFE Adj were about 0.2%. The elasticity standard deviation of the MRE Wave software was about 3% of the mean value, and those of the EC-LFE0 and EC-LFE Adj were about 1% of the mean value. The elasticity CNR value of EC-LFE0 reached 1.93 times that of the MRE Wave in the region of small tumors (less than 10-point sampling). The viscosity RMS errors of the EC-LFE0 could be less than 5%.Conclusion: Compared to conventional methods, the EC-LFE was more accurate and sensitive for small tumor detection and exhibited higher noise immunity. The improved algorithm output more parameters and outperformed than the MRE Wave, thereby rendering them more suitable for clinical applications. (C) 2020 Elsevier B.V. All rights reserved.