Synopsis
Current parallel transmit pulse design methods are
based on a spatial domain formulation that has prohibitive memory and computational
requirements when the number of coils or the number of dimensions is large. We describe a k-space domain parallel transmit pulse design method
that directly solves for the columns of a sparse design matrix with a much
smaller memory footprint than existing methods, and is highly parallelizable. The
method is validated with phantom and in vivo 7T 8-channel spiral excitations.
Introduction
Parallel transmission enables the excitation of
multidimensional selective patterns with short RF pulse durations [1,2], and
has been applied to enable reduced-FOV imaging and mitigation of B1+
inhomogeneity. The spatial-domain formulation is currently the most widely used
approach for parallel transmit pulse design [3], but for large problem sizes (as
in high-resolution 2D pulse design, many-coil parallel excitation, 3D and
spectral-spatial pulse design), matrix inverse and iterative solutions
have large memory and/or computational requirements. Here we introduce and validate a k-space-based
approach to parallel transmit pulse design that has low memory and
computational requirements, and is highly parallelizable.Methods
The k-space domain pulse design method solves for the
columns of a sparse matrix W that relates the discrete Fourier transform of a
target pattern d to a vector of RF pulses, as:
ˆb=WF(d)
where the designed pulses are stacked end-on-end in the
vector ˆb. Each column of W represents a location in the target excitation
k-space grid, and contains a set of weights that relate the desired energy at
that target location to the RF pulses. These weights can be determined
column-by-column, by solving the system of equations that results from
discretizing the following equation over the neighborhood around each target
location:
δ(→k−→ktarg)=∑i∈traj∑j∈coilswj(→ki)sj(→k−→ki)
where i indexes
excitation trajectory locations →ki that are near the target location →ktarg.
Figure 1 illustrates this equation graphically. The discretized system of
equations can be recast in matrix-vector form, as:
Sw=δ
where δ is a vector that contains a one at the target
location, and zeros elsewhere. The weights vector can be solved using regularized pseudoinverse, as:
ˆw=(SHS+λI)−1stargH
where starg=SHδ is the row of the matrix S corresponding to the target location. The weights are then inserted into the
sparse matrix W for pulse design.
Experiments
were performed to validate the k-space domain pulses and compare them to
spatial domain pulses designed using a regularized matrix pseudoinverse. First,
B1+ maps were measured in a 3D-printed head phantom on a 7T scanner (Philips
Healthcare, Best, Netherlands) with 8-channel parallel transmit. B1+ map processing,
B0 shimming, and RF pulse
interfacing was performed with MRCodeTool (MRCode BV, Zaltbommel, Netherlands).
Spiral-in RF pulses were designed to excite an oval region in the middle of the
brain phantom with 7.5 cm excitation-FOV, 0.7 cm resolution, 3.4 ms duration,
and one-degree flip angle. The same pulse design was repeated for a healthy
human volunteer with IRB approval, but was scaled to 90 degrees and used as a
saturation pulse, followed by a crusher and a one-degree excitation. In both
cases the excitation patterns were imaged with a gradient-recalled echo
sequence with TE/TR = 2/100 ms. The k-space domain designs used 20 x 20
neighborhoods around each target location.
Results
Figure 2 shows full-scale and windowed-down phantom
excitation pattern images. The spatial domain-designed pulses had lower design
error than the k-space domain pulses (1.7% versus 6.1% NRMSE with the same RMS
RF amplitude), but the imaged patterns contain no significant differences.
Figure 3 shows in vivo images with midbrain saturation. The spatial
domain-designed pulses again had lower design error (2.9% versus 7.4% with the
same RMS RF amplitude), but the shape and quality of the saturation regions are indistinguishable. The
number of nonzero elements in the k-space domain designs' W matrices was 350,000, while the number of
elements in the inverse spatial domain matrix was 14.5 million. Discussion
The presented k-space domain method is related to the
method of Katscher et al [1], but that method does not decouple calculation of
the design matrix columns, or take advantage of the limited support of B1+ maps
in the frequency domain. As a result, it has the same computational and memory requirements as the spatial domain method [3]. Errors in
k-space domain pulse designs will predominantly appear at the boundaries of the
excited volume, where the B1+ maps will be rounded off due to k-space
truncation. This may be mitigated by growing the maps past the boundary or using other means to restrict their frequency content. Our next steps will be to
parallelize the weight computations across target locations/columns of W,
extend the design to 3D and spectral-spatial pulse designs, and implement
off-resonance-compensated k-space pulse design using time- or frequency-segmentation.Conclusion
A new k-space domain parallel transmit pulse
design method was described, which has reduced memory requirements
compared to existing spatial domain formulations (41x smaller for the presented
spiral designs), and can be finely parallelized.Acknowledgements
This work was supported by NIH grants R01 EB
016695 and U01 EB 025162. References
- U. Katscher, P. Boernert, C. Leussler, and J. S. van den Brink. Transmit SENSE. Magn Reson Med, 49(1):144–150, Jan 2003.
- Y. Zhu. Parallel excitation with an array of transmit
coils. Magn Reson Med, 51(4):775–784, Apr 2004.
-
W. A. Grissom, C. Y. Yip, Z. Zhang, V. A. Stenger, J. A.
Fessler, and D. C. Noll. Spatial domain method for the design of RF pulses in
multicoil parallel excitation. Magn Reson Med, 56(3):620–9, Sep 2006.