The multidimensional fast Fourier transform (MFFT) for arbitrary n-dimensional periodic grids allows images with non-cuboid voxels and fields of view (FOV) to be reconstructed efficiently. In this study, we apply the MFFT with a modified Smith normal form to iterative k-t SENSE reconstruction of data from a golden-angle stack-of-stars DCE-MRI sequence to produce a 4-D image with a non-cuboid FOV tailored to fit tight around the imaged subject. Compared to FFT-based reconstruction on a tight-fitting cuboid FOV, the non-cuboid MFFT reduced reconstruction time by 18% and memory usage by 11% while producing voxel values identical to those found in the reconstruction domain of the cuboid FOV.
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