Alternative k-space sampling distributions for MR spectroscopic imaging

While acquiring data for magnetic resonance spectroscopic (MRS) images, signal-to-noise (SNR) and imaging time considerations limit the amount of sampled spatial frequencies. Typically, the small number of spatial frequencies are uniformly sampled in the center of the transform domain (k-space) and the resulting image, generated from zero-filling, appears blurry. Often times, the MRS image is further degraded by large interfering components. To improve these images, the authors use knowledge of the anticipated anatomical features in the spectroscopic image, as determined from a conventional magnetic resonance image (MRI). They use this prior knowledge during both data acquisition and reconstruction. They show results where the present method not only improves the resolution of the MRS image, but also reduces contamination from undesirable components, such as subcutaneous lipid