Yuxin Zhang1,2, Matthias Muhler1, Ruiqi Geng1,2, Arnaud Guidon3, and Diego Hernando1,2
1Radiology, University of Wisconsin Madison, Madison, WI, United States, 2Medical Physics, University of Wisconsin Madison, Madison, WI, United States, 3Applications and Workflow, GE Healthcare, Boston, MA, United States
Synopsis
Conventional liver diffusion MRI acquisitions suffer
from several challenges including low spatial resolution, B0-induced
distortions, and elastic motion-induced signal voids. In this work, motion-robust
and distortion-corrected liver diffusion-weighted imaging (DWI) was enabled by combining
optimized motion compensated diffusion waveforms with multi-shot EPI
acquisitions. Quantitative validation of distortions and ADC measurements was
performed in healthy volunteer to assess the robustness and reproducibility of
the combined techniques, as well as the synergistic effect of motion-robust gradient
waveform and multi-shot EPI acquisitions. Preliminary patient example demonstrated
the feasibility in patients with metastatic liver lesions.
Introduction
Diffusion-weighted (DW)-MRI of the abdomen has various
potential applications, including the detection, staging, and treatment
monitoring of cancer. However, DW-MRI has substantial technical challenges1-3. Central among these challenges
is the extreme sensitivity of DW-MRI to physiological motion, which leads to:
1) Signal voids in tissues that experience non-rigid
motion during the application of DW gradients (eg: the left lobe of the liver).
These signal voids complicate diagnostic image interpretation and introduce
bias in quantitative measures of diffusion (eg: ADC).
2) Unpredictable phase variations in the signal
acquired from each excitation, which result in the widespread use of single
shot echo-planar imaging (ssEPI) in DW-MRI. Unfortunately, ssEPI results in
substantial image distortions and limited resolution in DW-MRI, particularly in
complex magnetic susceptibility environments such as the abdomen.
In recent years, advanced techniques have been
proposed to address these challenges. Optimized motion-robust DW gradients
techniques6-8 have shown excellent promise to overcome the signal
voids present in tissues that experience substantial motion, leading to reliable
imaging and quantitative ADC mapping throughout the entire liver. In addition, phase-corrected
multi-shot reconstruction techniques4 has been proposed for reduced-distortion, high-resolution
multi-shot EPI (msEPI) based DW-MRI4-5. Further, we hypothesize that
a synergistic combination may be feasible between motion-robust DW gradient
waveforms (which may reduce the presence of motion-induced phase variations in
the acquired data) and msEPI techniques for liver DW-MRI. In this study, we
evaluated the robustness and reproducibility of combined motion-robust DW
waveforms and msEPI acquisitions.Methods
After IRB approval and informed written consent, eight
healthy volunteers and one patient with liver metastases from primary pancreatic
cancer were scanned on a 3T scanner (GE Signa Premier) with high-density receive
array coils (AIR coil, GE Healthcare, Waukesha, WI).
In comparison to the
conventional monopolar (MONO) gradient waveform, M1-Optimized Diffusion Imaging
(MODI) gradient waveform design8 was applied to achieve
motion-robust diffusion waveforms with a small first-moment to suppress blood
signal. For each DW waveform, two separate DW-MRI acquisitions
using ssEPI and msEPI, respectively, were obtained. Detailed parameters are in Table.1. msEPI was obtained with two shots, each shot had
acceleration factor=2 and reconstructed with a multiplexed sensitivity-encoding method4. DW-MRI acquisitions were performed during multiple breath-holding
periods.
Non-EPI T2-weighted (T2w) images were acquired with a
2D Fast Spin-Echo sequence as a reference of anatomic structure. The same
spatial resolution and prescribed locations were used to match the DW-MRI
acquisitions.
ADC maps were calculated for all DW-MRI series. Co-localized
ROIs were drawn on each ADC map in both the left and right liver lobes. The ADC
in the non-motion-corrupted right liver lobe was used as reference ADC value2,6-8.
Bland-Altman analysis was performed between the ADC measurements of the left
and right lobe for each diffusion sequence to evaluate the consistency of ADC
between the left and right lobes.
Distortion level was assessed using the normalized cross-correlation coefficient
(CCC)9, which quantifies
the geometric alignment between the T2w reference and the low b-value DW images
for each slice (Eq.1). Masks were selected from T2w references to remove the
background noises.
$$CCC=\frac{\sum_i{\sum_j{(T2_{ij}-\overline{T2})(DWI_{ij}-\overline{DWI})}}}{\sqrt{(\sum_i{\sum_j{(T2_{ij}-\overline{T2})^2}})(\sum_i{\sum_j{(DWI_{ij}-\overline{DWI})^2}})}}~~~Eq.1$$Results
Fig.1 shows DW images from two healthy
volunteers. The yellow curve in volunteer (a) depicts the contour of the liver
from the T2w reference. The misalignment between the contour and the liver
anatomy due to distortion in the DW images is indicated by yellow arrowheads.
Images with msEPI acquisition have substantially reduced distortion artifacts. Blue
arrowheads show the motion-induced signal voids and ADC bias in the left liver
lobe, which was reduced by MODI acquisition. The worm-hole artifacts indicated
by red arrows in the msEPI reconstruction with MONO acquisition were likely
due to motion-induced rapid spatial phase variations, which were mitigated
when combining msEPI with MODI.
CCC comparison in Fig.2(a) illustrates the synergy
between motion-robust diffusion waveform and msEPI acquisition. The alignment
between DW images from MONO-ssEPI and the T2w reference is higher than
MONO-msEPI (p=0.0051) even though the visually observed distortion artifact is
largely reduced in MONO-msEPI (Fig.1). This is likely due to the substantial
signal voids in the left liver lobe and the worm-hole artifacts. With MODI
waveform (ii), msEPI has significant improvement (p<0.0001) in terms of
alignment, which indicates significantly reduced distortion.
Bland-Altman analysis in Fig.2(b) demonstrates reduced
ADC bias of the left liver lobe due to the motion-robust MODI acquisition. The
ADC values in the left liver lobe of MONO-ssEPI and MONO-msEPI have significant
bias compared to the right lobe. With MODI acquisitions, no
significant bias was observed in both ssEPI and msEPI acquisitions.
Finally, Fig.3 demonstrates the clinical feasibility
of MODI-msEPI, which enabled high image quality with reduced distortions, in a
patient with multiple liver metastases. Discussion
In this study, we have investigated the feasibility
and reproducibility of motion-robust and distortion-corrected DW-MRI by
combining optimized motion-compensated diffusion waveforms (i.e. MODI) and msEPI
acquisition. Volunteer study showed promising image quality with reduced ADC
bias in the left lobe as well as reduced distortion. Importantly, this work demonstrated
the potential synergy of combining MODI and msEPI techniques. Future studies will
be focused on further evaluation in clinical patients.Conclusion
The synergetic
effects of combined motion-compensated diffusion waveforms and msEPI
acquisitions can enable reproducible and
robust liver DWI with motion-robustness and reduced distortion.Acknowledgements
The authors
acknowledge research support from GE Healthcare. References
[1] Naganawa, S., Kawai, H., Fukatsu, H., Sakurai, Y.,
AOKI, I., MIURA, S., MIMURA, T., KANAZAWA, H. and ISHIGAKI, T., 2005.
Diffusion-weighted imaging of the liver: technical challenges and prospects for
the future. Magnetic Resonance in Medical Sciences, 4(4), pp.175-186.
[2] Murphy, P., Wolfson, T., Gamst, A., Sirlin, C. and
Bydder, M., 2013. Error model for reduction of cardiac and respiratory motion
effects in quantitative liver DW‐MRI. Magnetic resonance in
medicine, 70(5), pp.1460-1469.
[3] Kwee, T.C., Takahara, T., Niwa, T., Ivancevic,
M.K., Herigault, G., Van Cauteren, M. and Luijten, P.R., 2009. Influence of
cardiac motion on diffusion-weighted magnetic resonance imaging of the
liver. Magnetic Resonance Materials in Physics, Biology and
Medicine, 22(5), pp.319-325.
[4] Chen, N.K., Guidon, A., Chang, H.C. and Song,
A.W., 2013. A robust multi-shot scan strategy for high-resolution diffusion
weighted MRI enabled by multiplexed sensitivity-encoding
(MUSE). Neuroimage, 72, pp.41-47.
[5] Zhang, Y., Holmes, J., Rabanillo, I., Guidon, A.,
Wells, S. and Hernando, D., 2018. Quantitative diffusion MRI using reduced
field-of-view and multi-shot acquisition techniques: Validation in phantoms and
prostate imaging. Magnetic resonance imaging, 51, pp.173-181.
[6] Aliotta, E., Wu, H.H. and Ennis, D.B., 2017.
Convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo
time and bulk motion–compensated diffusion‐weighted MRI. Magnetic
resonance in medicine, 77(2), pp.717-729.
[7] Peña‐Nogales, Ó., Zhang, Y.,
Wang, X., de Luis‐Garcia,
R., Aja‐Fernández,
S., Holmes, J. H., & Hernando, D. (2019). Optimized Diffusion‐Weighting Gradient
Waveform Design (ODGD) formulation for motion compensation and concomitant
gradient nulling. Magnetic resonance in medicine, 81(2), 989-1003
[8] Zhang Y, Peña‐Nogales Ó, Holmes JH,
Hernando D. Motion‐robust
and blood‐suppressed
M1‐optimized
diffusion MR imaging of the liver. Magnetic resonance in medicine. 2019
Jul;82(1):302-11.
[9] Hancu I, Lee SK, Hulsey K, et al. Distortion
correction in diffusion-weighted imaging of the breast: Performance assessment
of prospective, retrospective, and combined (prospective + retrospective)
approaches. Magn Reson Med. 2017;78(1):247-253. doi:10.1002/mrm.26328