K-space sampling strategies

Abstract. The k-space algorithm offers a comprehensive way for classification and understanding of the imaging properties of all commonly used MR sequences. This presentation describes the basic concepts of k-space and its most relevant properties for MR imaging. The ramifications of k-space sampling is discussed for the most commonly used groups of MR sequences including gradient-echo techniques, echo-planar imaging, spin echo, and rapid acquisition relation enhanced imaging (e. g., turbo spin echo, fast spin echo). In addition, the basic problems and properties of sequences based on non-rectilinear k-space sampling, such as spiral imaging, are discussed. Their artifact behavior is significantly different from rectilinear scans, which project all imperfections along the phase-encoding directions, whereas the artifact produced by spirals are more complex and not always easily recognizable as such. An understanding of the k-space sampling offers important insight into the basic properties of a given sequence regarding signal-to-noise ratio, image distortion, resolution and contrast. It is demonstrated that the ultimate limitation in imaging speed is given by the loss of signal-to-noise ratio inherent to faster data sampling.