4.3 Article

Two-spoke placement optimization under explicit specific absorption rate and power constraints in parallel transmission at ultra-high field

Journal

JOURNAL OF MAGNETIC RESONANCE
Volume 255, Issue -, Pages 59-67

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jmr.2015.03.013

Keywords

Parallel transmission; RF optimization; Spoke placement

Funding

  1. European Research Council under the European Union's Seventh Framework Program (FP7)/ERC Grant [309674]

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The spokes method combined with parallel transmission is a promising technique to mitigate the B-1(+) inhomogeneity at ultra-high field in 2D imaging. To date however, the spokes placement optimization combined with the magnitude least squares pulse design has never been done in direct conjunction with the explicit Specific Absorption Rate (SAR) and hardware constraints. In this work, the joint optimization of 2-spoke trajectories and RF subpulse weights is performed under these constraints explicitly and in the small tip angle regime. The problem is first considerably simplified by making the observation that only the vector between the 2 spokes is relevant in the magnitude least squares cost-function, thereby reducing the size of the parameter space and allowing a more exhaustive search. The algorithm starts from a set of initial k-space candidates and performs in parallel for all of them optimizations of the RF subpulse weights and the k-space locations simultaneously, under explicit SAR and power constraints, using an active-set algorithm. The dimensionality of the spoke placement parameter space being low, the RF pulse performance is computed for every location in k-space to study the robustness of the proposed approach with respect to initialization, by looking at the probability to converge towards a possible global minimum. Moreover, the optimization of the spoke placement is repeated with an increased pulse bandwidth in order to investigate the impact of the constraints on the result. Bloch simulations and in vivo T-2*-weighted images acquired at 7 T validate the approach. The algorithm returns simulated normalized root mean square errors systematically smaller than 5% in 10 s. (C) 2015 Elsevier Inc. All rights reserved.

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