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GOCART: GOlden-angle CArtesian randomized time-resolved 3D MRI
Yinghua Zhu1, Yi Guo1, Sajan Goud Lingala1
1Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, USA.
Purpose:
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.
Methods:
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.
Results:
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.
Conclusion:
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.
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