Xu Han1, Katherine L. Wright1, Vikas Gulani2, 3, Nicole Seiberlich1
1Dept. of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States; 2Dept. of Radiology, Case Western Reserve University, Cleveland, OH, United States; 3Dept. of Radiology, University Hospitals, Cleveland, OH, United States
The goal of this work is to demonstrate that undersampled golden angle radial data can be reconstructed using through-time radial GRAPPA. The golden-angle trajectory is advantageous when it is not clear what acceleration factor is desired, as any subset of temporally adjacent k-space lines can be used for the reconstruction. This abstract describes two approaches for through-time radial GRAPPA weight calibration: using an additional sequentially ordered golden angle calibration dataset and a self-calibrating golden angle technique. Using these formulations, real-time free-breathing cardiac images can be reconstructed at retrospectively selected temporal resolutions from the same golden angle dataset.