Department of Mechanical Engineering, Stevens Institute of Technology, Hoboken, NJ.
Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY.
J Neuroimaging. 2019 Jul;29(4):440-446. doi: 10.1111/jon.12619. Epub 2019 May 6.
The brain's stiffness measurements from magnetic resonance elastography (MRE) strongly depend on actuation frequencies, which makes cross-study comparisons challenging. We performed a preliminary study to acquire optimal sets of actuation frequencies to accurately obtain rheological parameters for the whole brain (WB), white matter (WM), and gray matter (GM).
Six healthy volunteers aged between 26 and 72 years old went through MRE with a modified single-shot spin-echo echo planar imaging pulse sequence embedded with motion encoding gradients on a 3T scanner. Frequency-independent brain material properties and best-fit material model were determined from the frequency-dependent brain tissue response data (20 -80 Hz), by comparing four different linear viscoelastic material models (Maxwell, Kelvin-Voigt, Springpot, and Zener). During the material fitting, spatial averaging of complex shear moduli (G*) obtained under single actuation frequency was performed, and then rheological parameters were acquired. Since clinical scan time is limited, a combination of three actuation frequencies that would provide the most accurate approximation and lowest fitting error was determined for WB, WM, and GM by optimizing for the lowest Bayesian information criterion (BIC).
BIC scores for the Zener and Springpot models showed these models approximate the multifrequency response of the tissue best. The best-fit frequency combinations for the reference Zener and Springpot models were identified to be 30-60-70 and 30-40-80 Hz, respectively, for the WB.
Optimal sets of actuation frequencies to accurately obtain rheological parameters for WB, WM, and GM were determined from shear moduli measurements obtained via 3-dimensional direct inversion. We believe that our study is a first-step in developing a region-specific multifrequency MRE protocol for the human brain.
磁共振弹性成像（MRE）的脑僵硬度测量值强烈依赖于激励频率，这使得跨研究比较具有挑战性。我们进行了一项初步研究，以获取最佳的激励频率集，以准确获得整个大脑（WB）、白质（WM）和灰质（GM）的流变学参数。
6 名年龄在 26 岁至 72 岁之间的健康志愿者在 3T 扫描仪上使用嵌入运动编码梯度的改良单次激发自旋回波 echo 平面成像脉冲序列进行 MRE。通过比较四种不同的线性粘弹性材料模型（Maxwell、Kelvin-Voigt、Springpot 和 Zener），从频率相关的脑组织响应数据（20-80 Hz）中确定频率独立的脑材料特性和最佳拟合材料模型。在材料拟合过程中，对单个激励频率下获得的复剪切模量（G*）进行空间平均，然后获取流变学参数。由于临床扫描时间有限，通过优化最低贝叶斯信息准则（BIC），确定了用于 WB、WM 和 GM 的三个激励频率的组合，以提供最准确的逼近和最低的拟合误差。
Zener 和 Springpot 模型的 BIC 得分表明这些模型最能近似组织的多频响应。对于 WB，参考 Zener 和 Springpot 模型的最佳拟合频率组合分别确定为 30-60-70 和 30-40-80 Hz。
通过三维直接反演获得的剪切模量测量值，确定了用于准确获得 WB、WM 和 GM 流变学参数的最佳激励频率集。我们相信，我们的研究是为人类大脑开发特定区域多频 MRE 协议的第一步。
