Advances in sensitivity encoding with arbitrary k-space trajectories

New, efficient reconstruction procedures are proposed for sensitivity encod ing (SENSE) with arbitrary k-space trajectories. The presented methods comb ine gridding principles with so-called conjugate-gradient iteration. In thi s fashion, the bulk of the work of reconstruction can be performed by fast Fourier transform (FFT), reducing the complexity of data processing to the same order of magnitude as in conventional gridding reconstruction. Using t he proposed method, SENSE becomes practical with nonstandard k-space trajec tories, enabling considerable scan time reduction with respect to mere grad ient encoding. This is illustrated by imaging simulations with spiral, radi al, and random k-space patterns. Simulations were also used for investigati ng the convergence behavior of the proposed algorithm and its dependence on the factor by which gradient encoding is reduced. The in vivo feasibility of non-Cartesian SENSE imaging with iterative reconstruction is demonstrate d by examples of brain and cardiac imaging using spiral trajectories. In br ain imaging with six receiver coils, the number of spiral interleaves was r educed by factors ranging from 2 to 6. In cardiac real-time imaging with fo ur coils, spiral SENSE permitted reducing the scan time per image from 112 ms to 56 ms, thus doubling the frame-rate. (C) 2001 Wiley-Liss, Inc.