Institute of Medical Informatics, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universitt zu Berlin, and Berlin Institute of Health, Berlin, 10117, Germany.
Center for Mathematical Modeling, Universidad de Chile, Santiago, 8370456, Chile; Bernoulli Institute, University of Groningen, Groningen, 9747AG, the Netherlands.
Med Image Anal. 2022 May;78:102416. doi: 10.1016/j.media.2022.102416. Epub 2022 Mar 14.
While MRI allows to encode the motion of tissue in the magnetization's phase, it remains yet a challenge to obtain high fidelity motion images due to wraps in the phase for high encoding efficiencies. Therefore, we propose an optimal multiple motion encoding method (OMME) and exemplify it in Magnetic Resonance Elastography (MRE) data. OMME is formulated as a non-convex least-squares problem for the motion using an arbitrary number of phase-contrast measurements with different motion encoding gradients (MEGs). The mathematical properties of OMME are proved in terms of standard deviation and dynamic range of the motion's estimate for arbitrary MEGs combination which are confirmed using synthetically generated data. OMME's performance is assessed on MRE data from in vivo human brain experiments and compared to dual encoding strategies. The unwrapped images are further used to reconstruct stiffness maps and compared to the ones obtained using conventional unwrapping methods. OMME allowed to successfully combine several MRE phase images with different MEGs, outperforming dual encoding strategies in either motion-to-noise ratio (MNR) or number of successfully reconstructed voxels with good noise stability. This lead to stiffness maps with greater resolution of details than obtained with conventional unwrapping methods. The proposed OMME method allows for a flexible and noise robust increase in the dynamic range and thus provides wrap-free phase images with high MNR. In MRE, the method may be especially suitable when high resolution images with high MNR are needed.
虽然 MRI 允许对组织在磁化相位中的运动进行编码，但由于在高编码效率时相位中的缠绕，获得高保真运动图像仍然是一个挑战。因此，我们提出了一种最优的多运动编码方法（OMME），并将其应用于磁共振弹性成像（MRE）数据中。OMME 是使用具有不同运动编码梯度（MEGs）的任意数量的相位对比测量值对运动进行非凸最小二乘问题的公式化。OMME 的数学性质是根据任意 MEG 组合的运动估计的标准差和动态范围来证明的，这是使用合成生成的数据来确认的。我们在来自体内人脑实验的 MRE 数据上评估了 OMME 的性能，并与双编码策略进行了比较。展开的图像进一步用于重建刚度图，并与使用传统展开方法获得的刚度图进行比较。OMME 成功地将具有不同 MEG 的多个 MRE 相位图像组合在一起，在运动信噪比（MNR）或成功重建体素的数量方面优于双编码策略，同时具有良好的噪声稳定性。这导致了具有比使用传统展开方法更高分辨率细节的刚度图。所提出的 OMME 方法允许灵活且抗噪地增加动态范围，从而提供具有高 MNR 的无缠绕相位图像。在 MRE 中，当需要具有高 MNR 的高分辨率图像时，该方法可能特别适用。
