k-t BLAST¹ is a technique that works in the spatiotemporal frequency domain (x-f space) to resolve aliasing caused by lattice undersampling of the k-t space. Due to the strategic k-t sampling pattern, aliasing patterns in the in the x-f space are predictable and can be resolved using additional information from a training dataset. Previous methods for extending the concepts of k-t BLAST to non-Cartesian trajectories focused on solving the general inversion problem using an iterative conjugate gradient (CG) method², but this approach can be time-consuming and does not take advantage of the symmetry inherent in some commonly-used trajectories. This method presents a non-iterative extension of Cartesian k-t BLAST to dynamic radial imaging by using the radial symmetry of the data to simplify the reconstruction problem.In Cartesian k-t BLAST the k-space is undersampled in an interleaved fashion, which produces an offset aliasing pattern in the x-f space. Unlike Cartesian data, radially sampled data does not produce an aliased image with the clear aliasing artifacts required for k-t BLAST. However, the Radon transform of the underlying image can be generated by performing a Fourier transform only along the read-out direction; a subsequent Fourier transform along the projection direction will result in aliasing artifacts that are similar to those seen in Cartesian k-t BLAST. We refer to this domain as the “aliased space,” as shown in Figure 1. This space can then be Fourier transformed through time to obtain a type of x-f space, which we call the a-f space, where the necessary offset aliasing is present to perform the k-t BLAST reconstruction. Low-resolution training data can be obtained from the center of k-space of the undersampled radial data. After the k-t BLAST reconstruction in a-f space, the reconstructed data are transformed back into radial k-space, and then gridded using the NUFFT ³. This technique was first applied to in-vivo cardiac breathheld cine scans downsampled to mimic different acceleration factors. These data were collected along an interleaved radial trajectory on a Siemens Skyra 3T whole-body scanner with a bSSFP sequence using TR = 29 ms, TE = 1.5ms, BW = 1 kHz, FoV = 300mm, spatial resolution = 2.3x2.3x8.0 mm³, flip-angle = 57 degrees. Matrix dimensions were 128x128 with 144 fully sampled projections for the cine and 144/R for the accelerated scans. The fully-sampled cine images were used to calculate RMSE values for the reconstructed image series. Additionally, a-f BLAST was applied to prospectively accelerated real-time radial scans with R=4 and the same scan parameters as the cine dataset with the following exceptions: TR=2.94ms, flip angle=37 degrees.Figure 2 shows that a-f BLAST reduces the radial artifacts from a retrospectively undersampled cine dataset with R=4 without compromising the temporal resolution in the x-t images. Figure 3 shows the RMSE values for reconstructions of varying acceleration factors. It can be seen for increasing accelerations RMSE values steadily increase and image quality deteriorates. Figure 4 shows the performance of a-f BLAST for prospectively accelerated R=4 radial data. Figure 5 is a gif showing the same dataset as Figure 4 in an animated form.a-f BLAST, or non-iterative non-Cartesian k-t BLAST performed in Radon space, may enable a significantly faster reconstruction of radially undersampled images by removing the gridding/degridding steps required in non-Cartesian k-t BLAST.² The a-f BLAST approach does not require a separate training dataset, as the center of k-space can be used as the low-resolution training data. However, the two techniques have not been compared for speed or performance, which depends on the relative sparsity of the data in each of the domains (a-f vs. x-f). a-f BLAST also presents a new space which can be used to rapidly reconstruct undersampled radial data, which may be advantageous for other reconstruction techniques, including non-Cartesian parallel imaging and compressed sensing.