Christoph Stefan Aigner1, Sebastian Dietrich1, Tobias Schaeffter1,2, and Sebastian Schmitter1,3
1Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany, 2Division of Imaging Sciences and Biomedical Engineering, King's College London, London, United Kingdom, 3Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
Synopsis
We demonstrate the design and application of respiration-specific and respiration-robust
three-dimensional 4kT-point pTx pulses using respiration-resolved
3D B1+ maps. The subject-specific pulses were tested on 20 B1+ maps
(shallow/deep breathing) of 10 volunteers with different age and BMI and were
experimentally validated in the last three volunteers at 7T. Compared to
respiration-specific pulses, respiration-robust pulses resulted
in a negligible overall decrease of the FA homogeneity with clear benefits of
achieving homogeneous 3D FA across all respiration states.
Purpose
Parallel transmission
(pTx)1 in the human body is typically done for each subject
individually and thus, requires subject-specific B1+ information2,3.
For two-dimensional cardiac breath-hold imaging, however, a recent study
showed severe B1+ changes between deep inhale and exhale impacting conventional
slice-selective pTx spoke pulses. This impact was avoided by generating respiration-robust
spokes using breath-hold acquired B1+ maps from multiple respiration-states4.
However, the problems further increase for three-dimensional (3D) body
imaging, which is investigated in detail and successfully compensated in the
present work in multiple ways: First, we extend previous 3D kT-point body
pulses3 towards respiration-specific pulses using respiration-resolved
(RR) 3D B1+ maps2. Second, we investigate the use of RR and non-respiration-resolved
(NRR) B1+ maps for shallow and deep breathing. Finally, we apply the aforementioned respiration-robust
pulse-design principle4 to 3D respiration-robust kT-point pulses
and perform comprehensive tests on 20 B1+ maps (shallow/deep breathing) of 10
volunteers with different age and BMI. The optimized pulses were experimentally
validated in the last three volunteers at 7T.Methods
MRI was performed at 7T (Siemens Magnetom, Germany) according to an
approved IRB protocol in 10 healthy volunteers (4M/6F, mean:31y, range:24-56y)
with varying BMI (mean:23.5kg/m2, range:21-28kg/m2) using
a certified 32-element body coil array (MRI.TOOLS,
Germany) driven in 8TX/32RX mode. Local/global SAR limits in first level mode (IEC60601-2-33)
were complied by limiting each transmit channel's RF power. Relative 3D B1+-maps
of the thorax were acquired for each volunteer under free breathing2 with a
radial phase-encoding trajectory5 (nominal FA=20°, TE/TR=2.02/40ms,
FOV=250x312x312mm3, resolution = (4mm)3). All volunteers were
instructed via the intercom to perform deep breathing patterns and to breath
regularly otherwise. 256/512 RPE-lines were acquired in 205s/410s for shallow/deep
breathing, respectively. The B1+ maps were reconstructed NRR and RR for three
(shallow) and five (deep) respiration states2. Subject-specific 4kT-point
pulses were designed using the small-tip-angle approximation in MATLAB for the manually
selected NRR and RR 3D heart volumes to optimize respiration-specific
and respiration-robust 4kT-point pulses. The 4kT-point pulses (duration=0.96ms)
were computed in <30s online using an automatic regularization parameter update that
balances the root-mean-squared FA error in the heart ROI and the total RF power3,6.
The pulse performance was measured by the $$$\text{CV}=std(\text{FA})/mean(\text{FA})$$$ in the ROIs. High-resolution 3D
gradient-echo scans (nominal FA=10°, TE/TR=1.75/3.7ms, FOV=250x312x312mm3, resolution=(1.4mm)3,
256 RPE-lines, TA=333s) have been acquired in three volunteers to validate the respiration-robust
4kT-point pulses. Results and Discussion
Fig.1 illustrates the breathing amplitude of shallow
(a) and deep (b) breathing and the impact of respiratory motion on the 3D GRE
images from NRR and two RR reconstructions (inhale and exhale). Shallow
breathing primarily results here in similar NRR and RR reconstructions. Because
more data is available for the reconstruction, NRR reconstructions are
preferable due to an increased signal-to-noise (SNR) ratio and reduced
artifacts. For deep breathing, however, we see a clear difference between NRR
and RR reconstructions as a result of strong respiratory motion (HF~65mm, AP~12mm).
Here, the use of RR reconstructions and, thus, the use of respiration-specific
or respiration-robust pTx pulses for stronger breathing patterns is preferable.
Fig.2a shows one slice of the 3D heart ROI and the
schematic coil position. ROIs were selected manually for each respiration state.
Fig2.b-c show the relative B1+ magnitude and phase (relative to channel 4) of
one out of 8 channels (ch1) with a clear difference between the exhale and the inhale
state.
Fig.3 shows the resulting CVs in the heart ROIs of
subject 7 (exhale, intermediate and inhale state) for shallow (a) and deep (b)
breathing. Depicted are four optimization settings: exhale, intermediate,
inhale and respiration-robust. As expected, only small CV differences were
observed for shallow breathing (mean=9%, range=8-12%) with comparable FA
distributions, thus supporting the use of NRR reconstructions in the case of
shallow breathing3. For deep breathing, however, the CV
differences were more pronounced (mean=10%, range=7-17%). For instance, the
pulse optimized for inhale (CV=7%) resulted in a CV of 17% for exhale. As
expected, the respiration-robust optimization decreased the FA spread and even
more remarkably, the CVs of the respiration-robust pulse (8-9%) remained in the
same range as the CVs of the respiration-specific results (8-10%).
Fig.4. summarizes the CVs
of all 10 volunteers for the respiration-specific
and respiration-robust pulses for deep breathing patterns. Across all subjects,
the 3D respiration-robust pulses achieved mean CVs ranging from 8.5% (subject
1) to 16.9% (subject 6). This is much lower compared to respiration-specific
pulses with mean CVs ranging from 9% (subject 1) to unacceptable 36.3% (subject
2).
Fig.4a shows the 3D B1+ prediction using the subject-specific inhale (left) and the respiration-robust (right)
4kT-point pulse. Fig.4b shows the acquired, 3D GRE images (acquired
without cardiac gating) using the same pulses. The 3D GRE images are
reconstructed for the exhale state to demonstrate the advantages of the
respiration-robust pulse.Conclusion
While NRR B1+ maps are suitable for 7T 3D cardiac MR
imaging under shallow breathing, this in-vivo study demonstrates that RR maps
and respiration-robust 4kT pTx pulses are highly preferred to achieve 3D heart FA
homogenization at 7T when subjects perform strong breathing. Compared to
respiration-specific pulses, respiration-robust pulses resulted
in a negligible overall decrease of the FA homogeneity with clear benefits of achieving
homogeneous 3D FA across all respiration states. Acknowledgements
We gratefully
acknowledge funding from the German Research Foundation SCHM 2677/2-1 and
GRK2260, BIOQIC.References
1)
Padormo, F., Beqiri, A., Hajnal, J. V., and Malik,
S. J. (2016) Parallel transmission for ultrahigh‐field imaging. NMR Biomed.,
29: 1145– 1161. doi: 10.1002/nbm.3313
2) Dietrich, S., Aigner, C.S., Kolbitsch, C., et al. (2020) 3D Free-breathing Multi-channel absolute B1+ Mapping in the Human Body at 7T, Magn. Reson. Med., doi:10.1002/mrm.28602
3)
Aigner,
C.S., Dietrich, S. and Schmitter, S. (2020) Three-dimensional static and
dynamic parallel transmission of the human heart at 7T, NMR in Biomed.,
doi:10.1002/nbm.4450
4)
Schmitter, S., Wu, X., Uğurbil, K., Van de Moortele,
PF. (2015) Design of parallel transmission radiofrequency pulses robust against
respiration in cardiac MRI at 7 Tesla. Magn. Reson. Med., 74 doi:
10.1002/mrm.25512
5)
Prieto,
C., Uribe, S., Razavi, R., Atkinson, D. and Schaeffter, T., (2010) 3D
undersampled golden‐radial phase encoding for DCE‐MRA using inherently
regularized iterative SENSE. Magn. Reson. Med., 64, pp. 514-526,
doi:10.1002/mrm.22446
6)
Cao,
Z., Yan, X. and Grissom, W.A. (2016) Array‐compressed parallel transmit pulse
design. Magn. Reson. Med., 76, pp. 1158-1169., doi:10.1002/mrm.26020