Radial imaging is appealing for quantitative parameter mapping, due to their inherently robustness to undersampling compared to Cartesian trajectories and thus, its ability to yield parameter maps with high spatial resolution from highly undersampled data. Two-dimensional radial imaging typically acquires equiangular spaced lines, resulting in a circular field-of-view (FOV). Circular FOVs are not ideal for imaging applications with an anisotropic region-of-support (e.g., spine, leg). Larson et al. proposed an algorithm for designing fully sampled radial trajectories matching the prescribed anisotropic FOV. In this work we investigate the benefits of anisotropic FOV in radial MRI in the context of parameter mapping.
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