Journal Article

FZJ-2020-02798

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Application of Evolution Strategies to the Design of SAR Efficient Parallel Transmit Multi-Spoke Pulses for Ultra-High Field MRI

Eberhardt, B.FZJ* ; Poser, B. A. ; Shah, N. J.FZJ* ; Felder, J. (Corresponding author)FZJ*

2020
IEEE New York, NY

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Please use a persistent id in citations: http://hdl.handle.net/2128/26335  doi:10.1109/TMI.2020.3013982

Abstract: We present an evolution-strategy based approach to solve the magnitude least squares (MLS) design problem of low flip-angle slice-selective parallel transmit RF pulses for ultra-high field MRI using SAR and peak-RF-constraints. A combined transmit k-space trajectory and RF pulse weight optimization is proposed in two algorithmic steps. The first step is a coarse grid search to find an initial solution that fulfills all constraints for the subsequent multistage optimization. This avoids convergence to the next nearest local minimum. The second step attempts to refine the results using multiple evolution strategies. We compare the performance of our approach with the non-convex optimization methods described in the literature. The proposed algorithm converges for phantom and in vivo data and only requires an initial estimate of the range of suitable regularization parameters. It demonstrates improved excitation homogeneity compared to published spoke-design methods and allows optimization for homogeneity with a subsequent reduction in the SAR burden. Moreover, excitation homogeneity and the SAR burden can be balanced against each other, enabling a further reduction in SAR at the cost of minor relaxations in excitation homogeneity. This feature makes the algorithm a good candidate for SAR limited sequences in ultra-high field imaging. The algorithm is validated using phantom and in vivo measurements obtained with a 16-channel transmit array at 9.4T.

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Contributing Institute(s):

1. Physik der Medizinischen Bildgebung (INM-4)
2. Jara-Institut Quantum Information (INM-11)
3. Jülich-Aachen Research Alliance - Translational Brain Medicine (JARA-BRAIN)

Research Program(s):

1. 573 - Neuroimaging (POF3-573) (POF3-573)

Appears in the scientific report 2020

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Database coverage:
; ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Current Contents - Engineering, Computing and Technology ; Ebsco Academic Search ; Essential Science Indicators ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index ; Science Citation Index Expanded ; Web of Science Core Collection

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