Filiz Yetisir1, Esra Abaci Turk1,2, Elfar Adalsteinsson3,4,5, Patricia Ellen Grant1,2,6, and Lawrence L Wald4,7,8
1Fetal-Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Boston, MA, United States, 2Department of Pediatrics, Boston Children's Hospital, Boston, MA, United States, 3Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, United States, 4Harvard-MIT Health Sciences and Technology, Cambridge, MA, United States, 5Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Boston, MA, United States, 6Department of Radiology, Boston Children's Hospital, Boston, MA, United States, 7Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, MA, United States, 8Department of Radiology, Massachusetts General Hospital, Boston, MA, United States
Synopsis
RF
shimming (RFS) improves the transmit field for fetal MRI, however, fetal safety
is understudied. Previous simulations studied the SARlocal of the standard imaging mode (CP mode) of each
subject to inform the safety of RFS. We evaluated two local SAR management
strategies which utilize subject-specific models and use either the
individual’s CP mode SARlocal as a limit for RFS or the maximum CP mode SARlocal value across 7 subjects. We evaluated the B1+
performance inside the fetus for each strategy. Using the maximum CP mode SARlocal across the population as the SAR limit greatly improves
RFS performance.
Target audience
MR
physicists and clinicians interested in using RF shimming in fetal MRI at 3T.Introduction
RF shimming (RFS) can improve fetal
MRI excitation leading to increased signal and more uniform contrast at 3T.1–3 However, RFS can also
increase local SAR, raising safety concerns.1–3 The International
Electrotechnical Commission (IEC) recommends scanning pregnant subjects in
normal operating mode (maternal whole-body SAR=2W/kg) but otherwise do not
specify limits on fetal SAR.4 For this reason, previous fetal
RFS studies analyzed the effect on excitation metrics when SARlocal
was limited to that found in the standard mode of imaging, the circularly
polarized (CP) birdcage mode, in that individual’s body model.1,2 In this scenario, the
individual defines their own safety limit using the assumption that SAR
hotspots resulting from CP-mode imaging limited to SARwhole-body≤2W/kg is safe. This is
intrinsically different from SARlocal limits for RFS in nonpregnant
subjects since it results in a different SAR limit for each patient. Although acceptable,
this approach is conservative for subjects who happen to have low CP-mode SARlocal.
For example, if patient A’s model shows a CP mode SARlocal=15 W/kg
and patient B’s model shows 30 W/kg, the higher SARlocal would be
deemed safe in patient B but not A. A
less conservative approach would be to take the population worst-case CP-mode
SARlocal and conclude that this value is safe in all patients
because CP-mode imaging is widely used in a range of patients.
In this study, we evaluate two local
SAR management strategies for fetal RFS and calculate the resulting B1+
performance inside the fetus across 7 numerical pregnant body models. In both
strategies, fetal and maternal SARlocal is determined using
subject-specific modelling and used to constrain RFS. In the first strategy, we
use the individual’s CP-mode SARlocal as the SAR limit in RFS, as in
previous studies. For the second strategy, we use the maximum CP-mode SARlocal value
across the 7 models as the SAR limit in RFS. Finally, we run thermal
simulations to compare the temperature increase of CP-mode and RFS.Methods
EM simulations: We evaluate
the local SAR management strategies in seven numerical pregnant body
models5–7 (Fig.1) in a 2-port
32-rung high-pass birdcage coil model. Electromagnetic simulations were run in
Sim4Life (Zurich MedTech, Zurich, Switzerland)
to calculate B1+ and SAR in each model.
Local SAR management: Two
strategies, both of which constrain local SAR using subject-specific SAR models,
were evaluated for each ‘patient’ in terms of the resulting RFS |B1+|
average and variation inside the fetus. Strategy 1 (Individual CP-mode SARlocal
limit): uses each patient’s CP-mode SARlocal as their SARlocal
limit in RFS. Strategy 2 (population worst-case CP-mode SARlocal
limit): uses the maximum CP mode SARlocal value across the
population as the SARlocal limit in RFS. These strategies
were simulated by selecting one of the body models as the ‘patient’ and the
rest of the models as the population (for Strategy 2).
RF shimming: An exhaustive
search was carried out to find the best RF shim setting (without SAR
constraints) and the optimal RF shim settings for each Strategy. For the search
space, relative amplitude and phase of the two ports was varied from 0 to 2 and
-90°
to 270°
in steps of 0.1 and 10°, respectively. Maternal 10g average peak local SAR (pSAR10g),
fetal pSAR10g and fetal average SAR (aveSAR) was constrained in the local SAR
management process. Average |B1+| and coefficient
of variation (CV) of |B1+| inside the fetus were compared between
the CP mode, best shim settings and the optimal shim settings for Strategy 1
and 2. All values were normalized to 2W/kg maternal whole-body SAR (wbSAR).
Thermal simulations: We
compare maximum temperature increase (ΔT) across
models after 30 minutes of exposure to 2 W/kg wbSAR for CP mode and the optimal
shim settings resulting from Strategy 2. Results
Figure
3 shows fetal and maternal SAR for the CP mode across 7 models. Point
shape/colors depict the local SAR limits in Strategy 1 while the dashed lines
indicate the worst-case values used in Strategy 2. Figure 4 shows |B1+|
average and CV across all models for CP mode, best shim settings, and optimal shim
settings resulting from the 2 strategies. The average improvements across
models in |B1+| average and CV compared to CP mode are 15%
and 26% for best shim settings, 6% and 13% when RFS is constrained by Strategy 1,
and 13% and 25% when RFS is constrained by Strategy 2. Maximum ΔT observed with Strategy 2 is up to 18% higher
compared to CP mode as shown in Table 1. Discussion
This
study shows that using SARlocal limits from the maximum CP-mode
SARlocal values in the population instead of each patient’s own CP-mode
SARlocal greatly improves the transmit field performance of 2-channel
RF shimming. Thermal simulations show that maximum ΔT across the population is within 18% of those
in CP mode. Future work includes assessing the locations of maximum ΔT for different excitation modes and running
thermal simulations for realistic scan scenarios instead of constant 2 W/kg
exposure.Acknowledgements
This work was supported by R01HD100009, U01HD087211, R01EB017337, and R01EB006847.References
1. Yetisir F, Abaci Turk E, Guerin B, et al. Safety and imaging performance of two-channel RF shimming for fetal MRI at 3T. Magn Reson Med. 2021;86(5):2810-2821.
2. Murbach M, Neufeld E, Samaras T, et al. Pregnant women models analyzed for RF exposure and temperature increase in 3T RF shimmed birdcages. Magn Reson Med. 2017;77(5):2048-2056.
3. Filippi C, Johnson A, Nickerson J, Sussman B, Gonyea J, Andrews T. Fetal Imaging with Multitransmit MR at 3.0T: Preliminary Findings. In: Proceedings of the 18th Annual Meeting of ISMRM. Stockholm, Sweden. 2010, p2023.
4. International Electrotechnical Commission. IEC 60601-2-33: Medical electrical equipment-Particular requirements for the basic safety and essential performance of magnetic resonance equipment for medical diagnosis. https://webstore.iec.ch/publication/22705. Published 2015. Accessed April 22, 2021.
5. Abaci Turk E, Yetisir F, Adalsteinsson E, et al. Individual variation in simulated fetal SAR assessed in multiple body models. Magn Reson Med. 2020;83(4):1418-1428.
6. Christ A, Kainz W, Hahn EG, et al. The Virtual Family—development of surface-based anatomical models of two adults and two children for dosimetric simulations. Phys Med Biol. 2010;55(2):N23-N38.
7. Gosselin MC, Neufeld E, Moser H, et al. Development of a new generation of high-resolution anatomical models for medical device evaluation: the Virtual Population 3.0. Phys Med Biol. 2014;59(18):5287-5303.