Maggie M Fung1, Pauline Worters2, Ek Tsoon Tan3, Arnaud Guidon4, and Ersin Bayram5
1Applications & Workflow, GE Healthcare, New York, NY, United States, 2Applications & Workflow, GE Healthcare, Menlo Park, CA, United States, 3Global Research Center, GE, Niskayuna, NY, United States, 4Applications & Workflow, GE Healthcare, Boston, MA, United States, 5Applications & Workflow, GE Healthcare, Houston, TX, United States
Synopsis
Prostate
Diffusion Weighted Echo Planar imaging (DW-EPI) routinely suffers from nonlinear
geometric distortion due to B0 inhomogeneity. Although reverse phase-encoding
polarity-based distortion correction method works well in the brain, the same technique causes
artifacts in prostate DWI due to the low SNR nature of body DWI scans, and the
inconsistency of image content between the reverse and forward polarity images.
In this study, we showed that a hybrid weighting metric method could improve
the distortion correction performance in prostate DWI.
Purpose
Diffusion
Weighted Echo Planar imaging (DW-EPI) routinely suffers from nonlinear
geometric distortion due to B0 inhomogeneity1. Artifacts are most
pronounced at air-tissue interfaces, such as the rectum, in prostate diffusion
images. One of the distortion correction methods, reverse phase-encoding polarity gradient
(RPG) method2, has been successfully applied to brain DWI. However, directly
applying the same technique to prostate DWI resulted in wavy artifacts(Fig.1). In this study, we proposed a hybrid weighting metric as
part of the optimization to improve the RPG performance. Theory
Standard RPG method uses a multi-tier biconjugate
gradients stabilized method (Bi-CGSTAB)3 to perform non-linear
registration on the reverse and forward images to find the undistorted solution (Fig
2). However, while this method worked well in brain DWI with high SNR, this
method resulted in wavy artifacts and over-correction when applied to body
imaging. The wavy artifact was caused by the incorrect attempt of the algorithm
to match the noise speckles, and the over-correction was caused by the
anatomical mis-match between the reverse and forward images (Fig 1). We had explored
using a weak diffusion gradient to remove this effect, however, even at B=50,
there were still some differences in the vessel appearances, so that alone
could not fully address the artifacts.
As a result, we introduced a metric to
represent the pixel-by-pixel similarity between the reverse and forward image sets
and used this metric as a weighting factor during the Bi-CGSTAB optimization.
The rationale was that if the pixels do not correlate well (due to anatomical
differences or due to noise), the algorithm should weight less in that
area during the cost function minimization.
However, in regions where the B0
inhomogeneity was severe and not surrounded by other high SNR anatomies (e.g.
rectal wall), since the reverse and forward images will not match due to distortion,
those areas were not heavily weighted using the fore-mentioned metric. As a
result, we had to rely on a second metric (defined by the shim volume location)
to ensure those areas were included in the registration. The optimized
algorithm flow chart is shown in figure 2. Method
Axial
DWI were performed on 8 healthy volunteers on a 3T 70cm bore scanner (Signa Premier,
GE Healthcare, USA) using the GEM anterior andposterior array. DWI
parameters were: FOV:24cmx24cm, Matrix: 120x120,
TR/TE:3866ms/53.3ms, single spin echo, BW:250kHz, slice thickness:4mm, #
slices:22, Fat Sat, b-value=0s/mm2(1 nex), 50s/mm2 (4
nex), 800s/mmÂ2 (12nex), diffusion encoding: ALL, anterior and posterior sat bands, scan time: 3:17min. In 5 cases, reference T2 FSE was also
acquired with these parameters: FOV:24cmx24cm,
Matrix: 256x224, TR/TE:4985ms/77.6ms, BW:31.3kHz, Slice thickness:4mm, #
slices:22, nex: 3, scan time: 3:05min. We compared the undistorted image qualitatively
in all 8 cases. In 5 cases where T2 FSE reference were acquired, mutual
information(MI) between the T2 and DWI image (standard vs new RPG) were
calculated globally (in the entire slice) and locally (in the prostate area)
and compared using a two-sample t-test. Results and Discussions
Qualitative visual comparison between the algorithms showed that wavy artifacts were not
observed in the optimized RPG cases. In 7/8 cases, the two algorithms showed
similar spatial distortion correction in the prostate and seminal vesicle areas,
while in 6/8 cases, the two algorithms showed similar distortion correction rectal
wall area. Fig.3 shows a comparison between no RPG, original and optimized RPG
algorithm. The optimized RPG algorithm corrected for the prostate and rectum
but did not over-correct the vessels. The wavy artifacts in the original RPG
algorithm was especially pronounced at high b-value images, and the optimized RPG
algorithm greatly improved that(Fig.4). In the quantitative analysis, the MI
metric improved as expected when either of the RPG algorithms were employed
(Fig.5). There were no statistical significant differences between the MI
metric of the original vs optimized methods (0.4513±0.1055 vs 0.4383±0.1070 (p=0.4286) for global MI, 0.8225±0.1588 vs 0.8151±0.1641 (p=0.7638) for local MI). In general, the new algorithm maintained the correction performance at the prostate and does not generate wavy artifacts. Conclusion
We have demonstrated an optimized RPG technique in prostate imaging using a hybrid
weighting metric. This approach considered the SNR and similarity between the
forward and reverse images and therefore provided a more constrained solution
to the distortion correction optimization. Future direction will include
expanding this to other anatomies such as breast and liver. Acknowledgements
The author acknowledged Andres Dales (UCSD) for the useful discussion.References
[1] Bernstein, et
al. 2004b. Handbook of MRI Pulse Sequences.
[2]
Holland, Dale et al, NeuroImage 50 (2010) 175–183
[3] van der Vorst, et al, Cambridge
University Press, Cambridge. (April 2003).