Miha Fuderer1, Hongyan Liu1, Oscar van der Heide1, Cornelis A.T. van den Berg1, and Alessandro Sbrizzi1
1Division Imaging and Oncology, University Medical Center Utrecht, Utrecht, Netherlands
Synopsis
Keywords: MR Fingerprinting/Synthetic MR, Relaxometry
We applied optimized phase modulation to the RF sequence in MR-STAT. We
observe that applying optimized phase is beneficial towards the accuracy of T1
and T2 maps, particularly under constrained conditions. In particular, when comparing
sequences with and without an initial inversion pulse we observe that the difference vanishes when applying
optimized RF phase modulation. Thus optimized phase modulation allows to omit the
initial inversion pulse. We hypothesize that the same holds for other
multi-parametric qMRI techniques such as MRF.
Introduction
Modern multi-parametric quantitative MRI
methods include MR-STAT1, MR
Fingerprinting (MRF)2, QTI3 and Hybrid-state imaging4.
In these methods, flip angle
trains are usually time-varying. This gives many degrees of freedom to optimize
sequences of flip angles,
which is a non-trivial task. Many optimization approaches focus on single-voxel
optimization3,5-10, which have been shown to be sub-optimal11
in spatio-temporal techniques such as MR-STAT. Moreover, many optimization
approaches are limited to the amplitude of RF pulses3,8-10,12,
while it has been shown that appropriate application of phase modulation is beneficial4,13-15.
Interestingly, almost all of these methods1-12,14-15 apply an
initial inversion pulse – which brings additional power deposition, imperfections of its own and a need for magnetization-relaxation before the
pulse17.
In this work, we applied the recently
proposed analytical framework BLAKJac16 to optimize amplitude and
phase of the RF pulses. This is accomplished by acting on the
second derivative (or quadratic component) of the phase
component (“quadratic phase cycling”). We show
that this is particularly beneficial under constrained conditions, such as the
absence of an initial inversion pulse, contiguous cyclic application of a
sequence17, or when constraining power deposition.Methods
In our experiments, we used a non-balanced Cartesian MR-STAT
sequence on a 3T scanner (Philips Elition), with TR=10ms, TE=5ms, voxel size
1mm x 1mm, slice thickness of 5mm, with a Field Of View of 224mm, requiring 224
phase-encoding steps. The set of phase-encoding steps was repeated 6 times,
allowing MR-STAT reconstruction of maps of proton density, T1 and T2. In total, 1344 readout-lines were
acquired.
RF flip angles were optimized using BLAKJac.
BLAKJac is a framework that allows for fast approximation, via the Cramer-Rao
Bound, of the noise level in the reconstructed maps, given a flip angle and
gradient encoding sequence; this allows for fast optimization of flip-angle trains sequences,
while taking into
account the gradient encoding strategy. Two scenarios were considered: (A) Amplitude-only:
the phase of the pulses was zero; (B) Amplitude+Phase: phase modulation was
optimized based on its 2nd time-derivative. This is analogous to
applying a (locally) quadratically increasing phase whereby the quadratic
component slowly changes over time. See figure 1 for the resulting sequences.
Both scenarios (Amplitude-only) and (Amplitude+Phase)
were investigated in four different conditions:
1) initial inversion pulse
2) no initial inversion
3) cyclic repetition of the sequence without
pauses nor inversion
4) very stringent SAR limit, with root-mean-squared flip-angle < 10 degrees
and no inversion.
In order to estimate the standard deviations
in the resulting maps, each scenario was re-scanned and reconstructed 10 times.
The aforementioned set of scans was applied
on a Eurospin II phantom set18 (fig. 2) and on the knee of a human
volunteer (fig. 3).Results
In the images (figs. 2 and 3) we observe a
substantial difference in noise level between the Amplitude+Phase and the
Amplitude-only scenario. This is consistent with the BLAKJac
analysis, which predicts
that Amplitude+Phase sequences systematically result in lower noise levels than
Amplitude-only sequences. For both scenarios, BLAKJac predicts $$$\sigma_4>\sigma_3>\sigma_2>\sigma_1$$$ (where $$$\sigma_i$$$ has to be read as "the noise expected in condition $$$i$$$"). BLAKJac also indicates that the benefit of Amplitude+Phase over
Amplitude-only is particularly present for no-inversion, cyclic-repetition, or
low SAR conditions (first row of figure 4).
The BLAKJac theoretical analysis is confirmed by noise levels measured
in a phantom (see second row of fig. 4) and to a lesser degree by the noise
levels in-vivo (third row). The figure particularly shows that, when phase is
applied, the effect of an inversion pulse is negligible, as shown in fig. 5, thereby
suggesting that inversion pulses are not necessary. Contrarily, without phase,
those differences are substantial.Discussion
Each constrained condition has its
relevance: reducing the power deposition (condition 4) is of interest for high-field
applications. The removal of the (adiabatic) inversion pulse (condition 2) serves the
same purpose; moreover, imperfections of this pulse especially at strong B1
inhomogeneities often contribute to quantitative biases. The cyclic repetition condition
(3) is of particular interest if repetitive instances of the sequence are to be
applied, as e.g. in dynamic imaging or 3D imaging17.
Our experiments were conducted with MR-STAT,
but the observations likely hold for MRF as well as for other multi-parametric
MRI methods.Conclusion
Applying an optimized RF phase modulation to
multi-parametric qMRI sequence is particularly beneficial especially under constrained
conditions; examples hereof are sequences without an inversion-prepulse,
contiguous cyclic application of the sequence, and sequences exhibiting very
stringent SAR restrictions. More importantly, when applying Amplitude+Phase,
there is practically no benefit in applying the inversion pulse, which thus can be
omitted.Acknowledgements
This work has been financed by NWO grant number 17986References
1.
A. Sbrizzi, et al, “Fast quantitative MRI as a nonlinear tomography problem”, Magnetic
Resonance Imaging 46(2018): 56-63 O. van der Heide et al, NMR in Biomedicine, 202;33:e4251
2.
D. Ma, et al. Magnetic resonance fingerprinting. Nature,
2013;495187–495192.
3.
P. Gómez et al. Designing contrasts for rapid, simultaneous
parameter quantification and flow visualization with quantitative
transient-state imaging. ScientificReports (2019) 9:8468,
https://doi.org/10.1038/s41598-019-44832-w
4.
J. Assländer et al. Hybrid-state free precession in nuclear
magnetic resonance. COMMUNICATIONS PHYSICS (2019) 2:73
5.
K. Sommer, et al. Towards predicting the encoding capability of MR fingerprinting sequences. Magnetic Resonance Imaging, Volume 41, September 2017, Pages 7-14.
6.
B. Zhao, et al. Optimal Experiment Design for Magnetic Resonance
Fingerprinting. Conf Proc IEEE Eng Med Biol Soc. 2016 August ; 2016: 453–456.
7.
B. Zhao, et al. Maximum Likelihood Reconstruction for Magnetic
Resonance Fingerprinting. IEEE transactions
on medical imaging 1812-1823 (2016).
8.
O. Cohen, M. Rosen. Algorithm comparison for schedule optimization in MR
fingerprinting. Magnetic Resonance Imaging, Volume 41, September 2017, Pages 15-21
9.
N. Mickevicius, A. Nencka, E. Paulson. Reducing the Dimensionality of Optimal Experiment
Design for Magnetic Resonance Fingerprinting. https://ui.adsabs.harvard.edu/abs/2020arXiv201000674M/abstract
10. P.K. Lee et al. Flexible
and efficient optimization of
quantitative sequences using automatic differentiation of Bloch simulations.
Magn Reson Med. 2019;82:1438–1451
11. M
Fuderer, et al. Non-steady-state sequences for multi-parametric MRI need
to be evaluated in the context of gradient-encoding, Proc. Intl. Soc. Mag. Reson. Med. (2022), 2786
12. Hu,
McGivney, Griswold, Ma. Optimal experimental design of MR Fingerprinting for
simultaneous quantification of T1, T2, and ADC. Proc. Intl. Soc. Mag. Reson. Med. (2022), 4802
13. C. Wang, et al. Magnetic
resonance fingerprinting with quadratic RF phase for measurement of T2*
simultaneously with δf, T1, and T2, Mag. Reson. Med. 2019; 81(3): 1849.
14. X. Wang,
D. Hernando, S.B. Reeder. Phase-based T2 mapping with gradient echo imaging.
Magnetic resonance in medicine 84.2 (2020): 609-619.
15. H. Liu, et
al. Increasing the T2 sensitivity of MR-STAT sequences by small quadratic
RF phase increments, Proc.
Intl. Soc. Mag. Reson. Med. (2022), 0625
16. M. Fuderer, et al. Efficient
performance analysis and optimization of transient-state sequences for
multi-parametric MRI, NMR in Biomedicine (2022, in press).
17. T. Amthor
et al. Magnetic Resonance Fingerprinting with short relaxation
intervals.
18.
TO5, Eurospin II test system, Scotland