Compressed Sensing 3D-GRASE for faster High-Resolution MRI
Compressed Sensing 3D-GRASE for faster High-Resolution MRI
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DOI：
10.1002/mrm.27789
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发表时间：
2019-09-01
影响因子：
3.3
通讯作者：
Hernandez-Tamames, J. A.
中科院分区：
文献类型：
--
作者：
Cristobal-Huerta, A.;Poot, D. H. J.;Hernandez-Tamames, J. A.
目的：高分辨率三维(3D)结构磁共振成像可用于显示复杂或微小的身体结构。然而，该方法采集时间长、SAR高，限制了其临床应用。本工作的目的是通过结合压缩传感和并行成像(CSPI)在3D-GRAS序列上加速高分辨率图像的获取，并将其与(CS)PI 3D-FSE序列进行比较。研究了几种采样模式对图像质量的影响。方法：所提出的k空间采样模式是基于两个欠采样k空间网格、变密度泊松圆盘和VD伪随机高斯，以及文献中描述的五种不同轨迹。进行Bloch仿真以获得变换点扩展函数并评估每个采样图案的相干性。图像分辨率以半高全宽(FWHM)为评价指标。采用CSPI 3D-Grase体模和膝关节和大脑的活体实验，与PI 3D-Grase、PI 3D-FSE和CSPI 3D-FSE进行比较，以评估图像质量、SNR、SAR和采集时间。结果：对于PD加权和T-2加权的采集，使用VD Poisson-Disk的采样模式获得的一致性最低。与VD泊松圆盘相比，VD伪随机高斯获得了更低的半高宽，但更高的旁瓣。结论：与CSPI 3D-FSE相比，CSPI 3D-GRASE缩短了采集时间(PD加权43%，T2加权40%)和SAR(接近45%)。结论：与CSPI 3DFSE相比，CSPI 3D-GRASE缩短了采集时间，并保持了图像质量。在CSPI 3D-Grase图像采集中，采样模式的设计对图像质量至关重要。
Purpose: High-resolution three-dimensional (3D) structural MRI is useful for delineating complex or small structures of the body. However, it requires long acquisition times and high SAR, limiting its clinical use. The purpose of this work is to accelerate the acquisition of high-resolution images by combining compressed sensing and parallel imaging (CSPI) on a 3D-GRASE sequence and to compare it with a (CS) PI 3D-FSE sequence. Several sampling patterns were investigated to assess their influence on image quality.Methods: The proposed k-space sampling patterns are based on two undersampled k-space grids, variable density (VD) Poisson-disc, and VD pseudo-random Gaussian, and five different trajectories described in the literature. Bloch simulations are performed to obtain the transform point spread function and evaluate the coherence of each sampling pattern. Image resolution was assessed by the full-width at half-maximum (FWHM). Prospective CSPI 3D-GRASE phantom and in vivo experiments in knee and brain are carried out to assess image quality, SNR, SAR, and acquisition time compared to PI 3D-GRASE, PI 3D-FSE, and CSPI 3D-FSE acquisitions.Results: Sampling patterns with VD Poisson-disc obtain the lowest coherence for both PD-weighted and T-2-weighted acquisitions. VD pseudo-random Gaussian obtains lower FWHM, but higher sidelobes than VD Poisson-disc. CSPI 3D-GRASE reduces acquisition time (43% for PD-weighted and 40% for T-2-weighted) and SAR (similar to 45% for PD-weighted and T-2-weighted) compared to CSPI 3D-FSE.Conclusions: CSPI 3D-GRASE reduces acquisition time compared to a CSPI 3DFSE acquisition, preserving image quality. The design of the sampling pattern is crucial for image quality in CSPI 3D-GRASE image acquisitions.