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@ARTICLE{Eberhardt:878351,
author = {Eberhardt, Boris and Poser, Benedikt A. and Shah, N. Jon
and Felder, Jorg},
title = {{A}pplication of {E}volution {S}trategies to the {D}esign
of {SAR} {E}fficient {P}arallel {T}ransmit {M}ulti-{S}poke
{P}ulses for {U}ltra-{H}igh {F}ield {MRI}},
journal = {IEEE transactions on medical imaging},
volume = {39},
number = {12},
issn = {1558-254X},
address = {New York, NY},
publisher = {IEEE},
reportid = {FZJ-2020-02798},
pages = {4225 - 4236},
year = {2020},
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.},
cin = {INM-4 / INM-11 / JARA-BRAIN},
ddc = {620},
cid = {I:(DE-Juel1)INM-4-20090406 / I:(DE-Juel1)INM-11-20170113 /
I:(DE-Juel1)VDB1046},
pnm = {573 - Neuroimaging (POF3-573)},
pid = {G:(DE-HGF)POF3-573},
typ = {PUB:(DE-HGF)16},
pubmed = {pmid:32763849},
UT = {WOS:000595547500041},
doi = {10.1109/TMI.2020.3013982},
url = {https://juser.fz-juelich.de/record/878351},
}