Michael Mullen1 and Michael Garwood1
1Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN, United States
Synopsis
Clinical MRI sequences for imaging near metallic
implants are mainly multi-spectral approaches, with fast spin-echo acquisitions
to achieve clinically relevant scan times. Due to the large bandwidths
necessary for refocusing all off-resonance spins near metallic implants, usually
the refocusing pulse flip angles must be limited to a sub-optimal value to permit
a safe specific absorption rate. Here, a
low peak amplitude, radiofrequency refocused sequence is used to limit energy
deposition. Reversed encoding is employed, where two acquisitions are collected
with opposite frequency-encoding gradient polarity. An estimate of the
displacement field is found using a B-spline basis and the magnitude images.
Purpose
A small number of sequences are currently available
for MR imaging near metallic implants in a clinically relevant scan time [1]–[3] due to the large induced field inhomogeneities. While
the methods in [1]–[3] rely on multispectral imaging (MSI) approaches, Chang
& Fitzpatrick [4] previously proposed a self-consistency approach for
correcting image distortions by acquiring two images with opposite
frequency-encoding gradient polarity, hereafter referred to as reverse-encoding.
More recently, Skare & Andersson [5] demonstrated reverse-encoding near an aneurysm clip. Therein,
the excitation bandwidth was low (860 Hz) with a fixed frequency, artificially
reducing field inhomogeneity by imaging only a narrow band of frequencies.
Here, high-bandwidth (20 kHz) excitation pulses are used, and an estimate of the
displacement field is generated similarly to that in [5].Methods
The Missing Pulse Steady-State Free Precession (MP-SSFP)
[6] sequence was used, whereby a train of n small-flip angle pulses are applied to
achieve a steady-state. Data are acquired in place of the n+1 pulse, where an echo forms. This sequence achieves radiofrequency
(RF) refocusing with low peak amplitude. The reverse-encoding was implemented
such that acquisition of the same phase encoding line for each gradient
polarity was separated by a single TR (Figure 1) to limit motion artifacts. The
displacement field was estimated by aligning the intensity-corrected, resampled
magnitude images resulting from the opposing gradient polarities,
parameterizing the displacement in terms of 3D B-splines [5].
Phantom experiments were performed with a Varian
DirectDrive console (Agilent Technologies, Santa Clara, CA) interfaced to a 1.5T,
90-cm magnet (Oxford Magnet Technology, Oxfordshire, UK) with a clinical
gradient system (model SC72, Siemens, Erlangen, Germany). The magnet was
designed for use at 4T but, to achieve a more clinically relevant field, has
been ramped to 1.5T for these experiments. The phantom consisted of agar with
one stainless steel and one titanium screw embedded inside. A quadrature
transverse electromagnetic (TEM) RF coil (Virtumed, Minneapolis, USA) was used
for transmit and receive.
The MP-SSFP sequence used n = 3 pulses, TR = 25.86 ms,
and 250 kHz receiver bandwidth. Hyperbolic secant [7] pulses were used, with time-bandwidth product 10, 500
µs duration, 20 kHz
bandwidth, and 10˚
flip angle. The field-of-view (FOV) was 256x256x256 mm3 with 2 mm
resolution, and total scan time of 14.12 minutes. The reconstruction used 3 mm
spline knot spacing to estimate the displacement field, totaling 614,125 parameters to
estimate. In [5], an estimate of the Hessian is evaluated at each
update in part to account for the difference in magnitude of displacement and
motion parameters. Here, a first-order method, namely conjugate gradient, sufficed
as motion artifacts were mitigated in the sequence.
For comparison, the multi-acquisition
variable-resonance image combination (MAVRIC) sequence was implemented [1], and the different off-resonance images were
corrected prior to root-sum-of-squares combination to limit blurring [2]. Twenty frequency bins were separated by 1 kHz
with 2.25 kHz bandwidth, using approximately box-car excitation, 135° Gaussian refocusing, and TR = 3.07 s. One phase
encoded dimension was split into 8 segments, each with echo-train length 16. Identical
resolution, FOV, and receiver bandwidth was used as in the MP-SSFP technique,
with 52 minutes total scan time. As MP-SSFP was both faster and had visibly lower
signal-to-noise ratio (SNR), another scan was performed with 4 averages to
achieve a similar total scan time (56 minutes) to MAVRIC. A conventional 3D
fast spin-echo (FSE) was acquired for comparison.Results
A side-by-side comparison of a selected cross
section from each acquisition (MP-SSFP, MAVRIC and conventional FSE) is
presented in Figure 2. Both MP-SSFP and MAVRIC outperform FSE by retaining more
signal closer to the screws, despite large off-resonances. However, MP-SSFP
does not suffer from the ripple effect near the metal, as is the well-known
case with MAVRIC [8].
The SNR of MP-SSFP with one and four averages was 31.31
and 57.23, respectively, while the MAVRIC SNR was 130.97, as determined from a
region-of-interest analysis (ROI) – see Figure 2.Discussion
The primary disadvantage of the MP-SSFP technique described
here is the absence of slab selection, which would permit a shorter scan time.
While slab selection is possible, phase encoding remains necessary in the
spatially-selected dimension [2], [3] to resolve slab distortions. On the other hand, the short
TR of MP-SSFP alleviates the need for spatial selection.
Previous work [8], [9] has used reverse-encoding to correct images near
metallic implants, although MSI techniques were used in those works. Here, it
was demonstrated that reverse-encoding with broadband RF refocusing performs
well near metallic implants without resorting to MSI methods.
Future work will focus on achieving higher spatial
resolution within a fixed scan time. Additional emphasis will be placed on
complex image combination from the opposite polarity acquisitions to improve
SNR over magnitude image combination. This remains a challenge due to phase
differences between the two acquisitions.Acknowledgements
This work was supported by the National Institutes of
Health grants U01 EB025153 and P41 EB015894. The authors would like to thank Dr. Casey Johnson for providing the screws to embed in the phantom.References
[1] K. M. Koch, J. E. Lorbiecki, R. S. Hinks,
and K. F. King, “A multispectral three-dimensional acquisition technique for
imaging near metal implants,” Magn. Reson. Med., vol. 61, no. 2, pp. 381–390,
2009.
[2] K. M. Koch et al., “Imaging near
metal with a MAVRIC-SEMAC hybrid,” Magn. Reson. Med., vol. 65, no. 1,
pp. 71–82, 2011.
[3] W. Lu, K. B. Pauly, G. E. Gold, J. M.
Pauly, and B. A. Hargreaves, “SEMAC: Slice encoding for metal artifact
correction in MRI,” Magn. Reson. Med., vol. 62, no. 1, pp. 66–76, 2009.
[4] H. Chang and J. Fitzpatrick, “A Technique
for Accurate Magnetic Resonance Imaging in the Presence of Field
Inhomogeneities,” Ieee Tmi, vol. 11, no. 3, pp. 319–329, 1992.
[5] S. Skare and J. L. R. Andersson, “Correction
of MR image distortions induced by metallic objects using a 3D cubic B-spline
basis set: Application to stereotactic surgical planning,” Magn. Reson. Med.,
vol. 54, no. 1, pp. 169–181, 2005.
[6] S. Patz, S. T. S. Wong, and M. S. Roos, “Missing
pulse steady‐state free precession,” Magn. Reson. Med., vol. 10, no. 2,
pp. 194–209, 1989.
[7] M. . Silver, R. . Joseph, and D. . Hoult,
“Highly selective and π pulse generation,” J. Magn. Reson., vol. 59, no.
2, pp. 347–351, 1984.
[8] X. Shi, B. Quist, and B. Hargreaves, “Pile‐up
and ripple artifact correction near metallic implants by alternating
gradients.,” in Proceedings of the 25th Annual Meeting of ISMRM, Honolulu,
Hawaii, 2017, p. 574.
[9] K. Kwon, D. Kim, B. Kim, and H. Park, “Unsupervised
learning of a deep neural network for metal artifact correction using dual‐polarity
readout gradients,” Magn. Reson. Med., vol. 83, no. 1, pp. 124–138,
2020.