Optimizing spatiotemporal sampling for k-t BLAST and k-t SENSE: application to high-resolution real-time cardiac steady-state free precession

Abstract

In k-t BLAST and k-t SENSE, data acquisition is accelerated by sparsely sampling k-space over time. This undersampling in k-t space causes the object signals to be convolved with a point spread function in x-f space (x = spatial position, f = temporal frequency). The resulting aliasing is resolved by exploiting spatiotemporal correlations within the data. In general, reconstruction accuracy can be improved by controlling the k-t sampling pattern to minimize signal overlap in x-f space. In this work, we describe an approach to obtain generally favorable patterns for typical image series without specific knowledge of the image series itself. These optimized sampling patterns were applied to free-breathing, untriggered (i.e., real-time) cardiac imaging with steady-state free precession (SSFP). Eddy-current artifacts, which are otherwise increased drastically in SSFP by the undersampling, were minimized using alternating k-space sweeps. With the synergistic combination of the k-t approach with optimized sampling and SSFP with alternating k-space sweeps, it was possible to achieve a high signal-to-noise ratio, high contrast, and high spatiotemporal resolutions, while achieving substantial immunity against eddy currents. Cardiac images are shown, demonstrating excellent image quality and an in-plane resolution of approximately 2.0 mm at >25 frames/s, using one or more receiver coils.