Paul Chang1,2, Sahar Nassirpour1,2, and Anke Henning1,3
1Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, 2IMPRS for Cognitive and Systems Neuroscience, Eberhard Karls University of Tuebingen, Tuebingen, Germany, 3Institute for Biomedical Engineering, UZH and ETH Zurich, Zurich, Switzerland
Synopsis
A highly homogeneous B0 field is essential if we are to exploit the advantages of higher field strengths for MR applications. In this work, we model the real field of each shim channel of a 4th order shim system for a 9.4T MR system for in vivo B0 shimming applications. Each shim channel is modelled at a range of frequencies to account for the possibility of amplitude nonlinearities.
By modelling the fields generated by each shim channel, we were able to achieve better shim qualities than if perfect fields were assumed.
Introduction
MR systems often have 2nd order, 3rd order or even very high order spherical harmonic shim terms for B0
shimming. However, most B0 shimming methods make the assumption that
the generated B0 shim fields perfectly match spherical harmonic
functions, while real B0 shim fields can deviate greatly from the
ideal ones.
In
this work, we measured and modelled the generated real shim
fields for each shim term (and at a range of amplitudes) and used these models
to achieve a better B0 shim in the human brain at 9.4T.
Method
A 28 channel Resonance Research Inc
(Billerica, MA) insert shim was used with a 9.4T Siemens (Erlangen, Germany)
scanner. The
insert shim consisted of complete 2nd, 3rd and 4th as well as partial 5th and
6th order spherical harmonics.
The fields were measured on a 150mm
spherical phantom. A 2D GRE
sequence with the following parameters was used: resolution of 128x128;
200x200mm FOV; slice thickness of 3mm; 40 slices with a 20% distance factor; TR = 1200ms;
TE=4.00/4.76 ms; read-out bandwidth of 1500Hz/px.
To account for possible amplitudes
nonlinearities, the shim fields were measured at a range of field strengths.
Each shim term field was measured at: -1.0A, -0.5A, -0.2A, -0.1A, 0.1A, 0.2A,
0.5A, 1.0A and decomposed. Therefore each term has 8 field measurements (at
each of the different amplitudes) and each field measurement was characterised
using a 6th order decomposition.
The real shim field models were then
incorporated into a custom-written MATLABTM shim algorithm resembling the
one mentioned in [1] and tested by B0 shimming a
head-and-shoulder phantom. The shape of the volume-of-interest (VOI) could be
arbitrary and was not only restricted to a rectangle. We used the following
iterative algorithm to include the amplitude nonlinearities of each shim term:
1) Initialise field model
coefficients using the field measured (at 100mA).
2) Calculate the shim values.
3) Replace the field model coefficients
with an update rule.
4) If the shim currents do not
change then STOP, otherwise go to step 2.
Three different update rules were used (see fig. 1); firstly, the amplitudes were assumed to be linear and field coefficients
updated using a linearly regression model [2]; secondly, an iterative nearest-neighbour approach was used (the
field model used was the one closest to the amplitude of the shim term); lastly, an iterative linear-piecewise
approach for shimming; that is, the coefficients were interpolated between
adjacent amplitude fields (i.e. between -1.0A to -0.5A, then between -0.5 to
-0.2A and so forth).
The best suited real-field models were then
used to shim a whole-brain VOI in vivo
on 3 volunteers using 2nd, 3rd, 4th and partial 5th order. The resulting shim
quality was thereafter compared to the shim results obtained when assuming
perfect fields. The parameters for the B0 mapping scans were the
same as for the phantom (except with 0% distance factor).
Results and Discussion
All shim terms were found to behave linearly with respect to the amplitude (e.g. fig. 1) and so the linearly regressed model was used to characterise each term as input for the shim algorithm.
For 2nd order shimming, both the perfect-field
shims and real-field shims gave similar results indicating that the fields generated by the 2nd order shim coils were almost
pure (top images of fig. 2, 3). However, fig. 3 shows that assuming perfect-fields
for 3rd and higher order B0 shimming was not reasonable
and the real-field models need to be considered. Therefore for very high order
B0 shimming, real-field characterisation is undoubtedly required.
Furthermore, from fig. 4 and 5
we can see a constant improvement in the B0 homogeneity as we include higher order spherical harmonic shim
fields (the figure shows results when the real-field models are considered).
Fig. 5 shows a quantitative summary of the results from all 3 volunteers. Note
that higher order shimming showed better B0 homogeneity only when the
real-field models for each B0 shim term were used.
Conclusion
Higher-order B0 shimming at 9.4T
shows a noticeably better performance compared to low order B0 shimming
and consistently improves as more orders are used (as previously
shown [3]).
We also showed that there is a need to
model the real-fields produced by each shim term when shimming the B0 field [4]. The fields
were shown to be approximately linear with respect to the amplitude. Finally, the
field models were confirmed with in vivo
measurements.
Acknowledgements
We would like to acknowledge K. Metzemaeekers from Resonance Research Inc. (Billerica, MA, USA) for help with the insert shim.References
[1] A. Fillmer et al. (2015) MRM
[2] C. Juchem et al. (2010) Concepts in MR
Part B: MR Eng
[3] H. P. Hetherington et al. (2006) MRM
[4] J. L. Wilson et
al. (2002) NeuroImage