Suryanarayanan Sivaram Kaushik1, Ajeet Gaddipati2, Brian Hargreaves3, Dawei Gui4, Robert Peters2, Tugan Muftuler5, and Kevin Koch1
1Radiology, Medical College of Wisconsin, Milwaukee, WI, United States, 2GE Healthcare, Waukesha, WI, United States, 3Radiology, Stanford University, Stanford, CA, United States, 4GE Healthcare, Waukesh, WI, United States, 5Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
Synopsis
While FSE-based
multi-spectral imaging (MSI) sequences help overcome the artifacts caused by
metallic hardware, diffusion-weighted imaging remains a challenge. The non-CPMG
artifacts caused by adding diffusion lobes to an FSE train can be mitigated by
modulating the phase of the refocusing pulses. Another solution involves
splitting the contribution made by the spin and stimulated echoes (DUO
acquisition). Here, we combine a 2D version of MSI with a PROPELLER-DUO
sequence to obtain clinically-feasible, artifact-minimized, diffusion-weighted
images in subjects that have cancerous lesions in close proximity to metallic
hardware. Purpose
Spin-echo multi-spectral imaging (MSI) sequences can overcome the severe
susceptibility artifacts caused by metallic hardware [1,2]. While proton
density, T
1, T
2, and inversion recovery MSI sequences are
now used clinically, diffusion weighting remains challenging. In the presence
of metallic hardware, conventional single-shot EPI diffusion sequences
experience severe geometric distortions. While these artifacts can be mitigated
using FSE-based MSI sequences, the addition of diffusion lobes to an FSE sequence
violates the CPMG condition, resulting in a rapid decay of the amplitude of the
echo train [3]. In conjunction with a PROPELLER acquisition, echo train stability
can be improved by modulating the phase of the refocusing pulses along the X-Y
axes [3,4]. Recently, this method was used to create diffusion-weighted images
around metal [5]. Alternatively, this stability can also be improved by
separating the spin and stimulated echoes [6, 7], which can be efficiently
accomplished using the PROPELLER DUO acquisition strategy [8]. Given its
scan-time benefits, the work presented here uses the DUO acquisition for the
clinical translation of 2D-MSI diffusion-weighted imaging.
Methods
The PROPELLER-DUO sequence was extended to perform MSI metal artifact imaging
by dynamically changing transmit and receive frequencies of the RF pulses to
sample multiple spectral-bins. Additionally, the amplitude of the slice-select
gradient was flipped relative to the refocusing gradient to excite spatially and
spectrally selective bins – which then becomes the 2D MSI approach [9]. To enable
additional phase correction of odd and even echoes within the train,
alternating echoes were split into orthogonal blades [4,10]. While the split-echo
approach can both be acquired using an elongated readout [7], in PROPELLER-DUO
they are acquired using two separate readout lobes and split into orthogonal
blades. Diffusion weighting was achieved using unipolar trapezoidal gradients
around the refocusing pulse. The final pulse sequence is shown in the Figure 1 below.
In-vivo data was acquired in subjects with sarcoma in close proximity to
metallic hardware. Utilized sequence parameters are: 128 points, ETL =
24 – 32, TE/TR = 55/600-1500ms, BW = 62.5 kHz, NEX = 8 – 10, b-value = 100 –
300 s/mm2, single spin-echo diffusion preparation, centric-blade phase
encoding, sinc RF pulse bandwidth = 1.2 kHz, MSI spectral bins = 8 – 10,
spectral bin separation = 600 Hz. The PROPELLER raw-data for every bin was
reconstructed as detailed by Pipe et al. [3]. Individual bins were subject to a
wavelet de-noising procedure and combined in a sum of squares fashion to yield
the final artifact minimized 2D-MSI image.
Results
With a DUO acquisition mode, the echo train remained largely stable.
However, as the spin and stimulated echoes are separated, this mode suffers a ~50%
reduction in each echo amplitude. The split-echo mode was insensitive to
non-CPMG effects and the images showed few FSE ghosts. Figure 2A shows the
different spectral bins acquired for a single-slice, and the corresponding
diffusion-weighted images. These different spectral bin images were combined to
yield the MSI sum-of-squares (SOS) images shown in Figure 2B. Figure 3 shows
the current gold-standard clinical diffusion-weighted image, and the lesion is partially
obscured by the artifact caused by the metal implant. Figure 4 shows multiple
slices of the final MSI images obtained in a subject with lesion near a total
hip replacement. Both subjects had bone lesions proximal to the metallic
hardware that show an elevated ADC, suggesting possible necrosis [11]. The 2D MSI
approach substantially reduced susceptibility artifacts, allowing robust
diffusion weighting around metal implants.
Discussion and Conclusions
Historically, while the XY modulation approach was stable for larger
flip-angles, typical MSI acquisitions operate at lower flip-angles (~110°)
and also encounter substantial B
1 inhomogeneity near metal implant
interfaces. Hence, in spite of a loss in signal amplitude, the echo train
stability offered by the DUO mode madeĀ it the preferred choice for MSI-based diffusion
imaging. Additionally, as the DUO mode
acquires two echoes for every refocusing pulse, the resulting acquisition time
was reduced. However, this scan-time improvement was partially negated with the
need for multiple averages to improve the SNR. As a result, the acquisition
time was typically between 4 - 7 min. To shorten the scan time, it is
anticipated that future clinical implementations of this approach will
significantly benefit from simultaneous multi-slice imaging. Additionally, this
scan time can be shortened further, by calibrating the spectral coverage needed
for every subject [12].
Acknowledgements
The authors would like to thank Cathy Marszalkowski for subject recruitment.References
1) Koch et al., MRM 65: 71-82, 2011. 2)
Lu et al., MRM 62: 66-76, 2009. 3) Pipe et al., MRM 47: 42-52, 2002. 4) J.
Pipe, Proc. of ISMRM 2003, p2126. 5) Koch et al., Proc of ISMRM 2014, p106. 6)
Norris et al., MRM 27:142-164 1992. 7) Deng et al., MRM 59: 947-953, 2008. 8) Zhao
et al, Proc ISMRM 2009, p3517. 9) Hargreaves et al., Proc. of ISMRM 2014, p615.
10) Zhao et al, US 8384384, 11) Koh et
al., AJR 188:1622-1635, 2007. 12) Kaushik et al., MRM 2015 (in press).