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Golden-angle radial sparse parallel MRI: combination of compressed sensing, parallel imaging, and golden-angle radial
Li Feng1, Robert Grimm, Kai Tobias Block
1Bernard and Irene Schwartz Center for Biomedical Imaging, New York University School of Medicine New York, New York, USA; Sackler Institute of Graduate Biomedical Sciences, New York University School of Medicine New York, New York, USA.
Purpose:
To develop a fast and flexible free-breathing dynamic volumetric MRI technique, iterative Golden-angle RAdial Sparse Parallel MRI (iGRASP), that combines compressed sensing, parallel imaging, and golden-angle radial sampling.
Methods:
Radial k-space data are acquired continuously using the golden-angle scheme and sorted into time series by grouping an arbitrary number of consecutive spokes into temporal frames. An iterative reconstruction procedure is then performed on the undersampled time series where joint multicoil sparsity is enforced by applying a total-variation constraint along the temporal dimension. Required coil-sensitivity profiles are obtained from the time-averaged data.
Results:
iGRASP achieved higher acceleration capability than either parallel imaging or coil-by-coil compressed sensing alone. It enabled dynamic volumetric imaging with high spatial and temporal resolution for various clinical applications, including free-breathing dynamic contrast-enhanced imaging in the abdomen of both adult and pediatric patients, and in the breast and neck of adult patients.
Conclusion:
The high performance and flexibility provided by iGRASP can improve clinical studies that require robustness to motion and simultaneous high spatial and temporal resolution. Magn Reson Med 72:707-717, 2014. © 2013 Wiley Periodicals, Inc.
