An introduction to coil array design for parallel MRI

Abstract

The basic principles of radiofrequency coil array design for parallel MRI are described from both theoretical and practical perspectives. Because parallel MRI techniques rely on coil array sensitivities to provide spatial information about the sample, a careful choice of array design is essential. The concepts of coil array spatial encoding are first discussed from four qualitative perspectives. These qualitative descriptions include using coil arrays to emulate spatial harmonics, choosing coils with selective sensitivities to aliased pixels, using coil sensitivities with broad k-space reception profiles, and relying on detector coils to provide a set of generalized projections of the sample. This qualitative discussion is followed by a quantitative analysis of coil arrays, which is discussed in terms of the baseline SNR of the received images as well as the noise amplifications (g-factor) in the reconstructed data. The complications encountered during the experimental evaluation of coil array SNR are discussed, and solutions are proposed. A series of specific array designs are reviewed, with an emphasis on the general design considerations that motivate each approach. Finally, a set of special topics is discussed, which reflect issues that have become important, especially as arrays are being designed for more high-performance applications of parallel MRI. These topics include concerns about the depth penetration of arrays composed of small elements, the use of adaptive arrays for systems with limited receiver channels, the management of inductive coupling between array elements, and special considerations required at high field strengths. The fundamental limits of spatial encoding using coil arrays are discussed, with a primary emphasis on how the determination of these limits impacts the design of optimized arrays. This review is intended to provide insight into how arrays are currently used for parallel MRI and to place into context the new innovations that are to come.