Zhu Yinghua, Guo Yi, Lingala Sajan Goud, Lebel R Marc, Law Meng, Nayak Krishna S
Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, USA.
Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, USA.
Magn Reson Imaging. 2016 Sep;34(7):940-50. doi: 10.1016/j.mri.2015.12.030. Epub 2015 Dec 19.
To develop and evaluate a novel 3D Cartesian sampling scheme which is well suited for time-resolved 3D MRI using parallel imaging and compressed sensing.
The proposed sampling scheme, termed GOlden-angle CArtesian Randomized Time-resolved (GOCART) 3D MRI, is based on golden angle (GA) Cartesian sampling, with random sampling of the ky-kz phase encode locations along each Cartesian radial spoke. This method was evaluated in conjunction with constrained reconstruction of retrospectively and prospectively undersampled in-vivo dynamic contrast enhanced (DCE) MRI data and simulated phantom data.
In in-vivo retrospective studies and phantom simulations, images reconstructed from phase encodes defined by GOCART were equal to or superior to those with Poisson disc or GA sampling schemes. Typical GOCART sampling tables were generated in <100ms. GOCART has also been successfully utilized prospectively to produce clinically valuable whole-brain DCE-MRI images.
GOCART is a practical and efficient sampling scheme for time-resolved 3D MRI. It shows great potential for highly accelerated DCE-MRI and is well suited to modern reconstruction methods such as parallel imaging and compressed sensing.
开发并评估一种适用于使用并行成像和压缩感知的时间分辨三维磁共振成像（3D MRI）的新型三维笛卡尔采样方案。
所提出的采样方案称为黄金角笛卡尔随机时间分辨（GOCART）3D MRI，基于黄金角（GA）笛卡尔采样，在每个笛卡尔径向辐条上对ky-kz相位编码位置进行随机采样。结合对回顾性和前瞻性欠采样的体内动态对比增强（DCE）MRI数据以及模拟体模数据的约束重建对该方法进行了评估。
在体内回顾性研究和体模模拟中，由GOCART定义的相位编码重建的图像等同于或优于泊松盘或GA采样方案重建的图像。典型的GOCART采样表在<100毫秒内生成。GOCART还已成功用于前瞻性地生成具有临床价值的全脑DCE-MRI图像。
GOCART是一种用于时间分辨3D MRI的实用且高效的采样方案。它在高度加速的DCE-MRI中显示出巨大潜力，并且非常适合诸如并行成像和压缩感知等现代重建方法。
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