Jaume Coll-Font1,2, Onur Afacan1,2, Scott Hoge2,3, Bahram Marami4, Ali Gholipour1,2, Jeanne Chow1,2, Simon Warfield1,2, and Sila Kurugol1,2
1Radiology, Boston Children's Hospital, Boston, MA, United States, 2Harvard Medical School, Boston, MA, United States, 3Radiology, Brigham and Women's Hospital, Boston, MA, United States, 4Icahn School of Medicine at Mount Sinai, New York, NY, United States
Synopsis
Diffusion-weighted MRI (DW-MRI) has been
increasingly used in abdominal applications. However, unavoidable respiratory
motion, as well as B0 field inhomogeneities reduce the accuracy of the quantitative
parameters and hinders clinical applicability. In this work, we present a dual
echo EPI DW-MRI and
slice-to-volume registration method to jointly correct for geometric distortion
and motion of the kidneys. The results show that our method effectively reduced
geometric distortions, improved alignment of the DW-MR volumes and increased the
precision of the estimated quantitative parameters.
Introduction
Diffusion-weighted MRI
(DW-MRI) has been increasingly used in abdominal applications, especially in
pediatric populations, because it is free of contrast agent and ionizing
radiation. It has been successfully applied to kidneys, bowel, spleen and
liver. DW-MR images are acquired at multiple b-values and directions and
quantitative parameters are estimated by fitting a signal decay model such as a
diffusion tensor (DTI) or intravoxel incoherent motion (IVIM) model [5].
However, physiological motion (such as respiration, bowel motility) and large
geometric distortions due to inhomogeneities in the B0 field during EPI
acquisition degrade the image quality and reduce the accuracy of quantitative
parameters for diagnosis and assessing response-to-therapy and impede the
clinical applicability. In the absence of motion, the geometric distortions can
be corrected by first estimating the distortion field from two EPI volumes
acquired with opposite phase encoding sweep direction (Left (L)->Right(R)
and R->L) and then using the estimated field to correct the entire set of
volumes [6]. In the presence of unavoidable motion in abdominal imaging,
changes in position of the organs create a different distortion field for each
acquisition and this method can no longer be used reliably. Moreover, due to the
displacement of the underlying tissue, motion also deteriorates the estimation
of quantitative parameters. We introduce a method for simultaneous geometric
distortion (Di) and motion compensation (MoCo) for DiMoCo-DW-MRI of the abdomen
[7]. Our method employs a dual-echo readout after each excitation, to obtain
two EPI images with opposite phase encoding direction with only 30-50 ms
between each echo, which effectively freezees the motion in between. A field
map derived from each readout is then used to correct distortions in each
slice. We then employ a slice-to-volume registration technique [3] to
compensate for motion before DW-MRI model fitting and parameter estimation.Methods
We implemented a dual-echo EPI
sequence and acquired coronal abdominal DW-MR images from 4 healthy subjects (ages
29-38, 3 females). The sequence consisted on 168 DW-MR volumes (10 b-values and
17 directions) acquired on a 3T Siemens Prisma scanner with TE1/TE2/TR 72ms/108ms/7000ms, 18 coronal
slices, voxel size= 2.81x2.81x4 mm, b-values 0, 10, 30, 50, 80,120, 200, 400,
600 and 800 s/mm2). We also acquired a T2 HASTE volume as a
reference structural image.
In the Di step, we used each pair
of R->L/L->R images in TOPUP to estimate the distortion field of each slice
[8].
Afterwards, we used the estimated distortion field to create a distortion
corrected image. In the MoCo step, we used a slice-to-volume registration method
[9]
which estimates a transformation to align each slice to a reference volume and
uses a Kalman filter for improving the estimated transformations of
consecutively acquired slices. We applied this method to each kidney
separately, after applying a rectangular mask. Finally, we fitted an IVIM model
to the DW-MRI volumes.
We evaluate our DiMoCo method
based on the improvements in the quality of the images and in the precision of
the IVIM model parameters. To evaluate the distortion correction method, we compared
the resulting DW-MR volumes against the original R->L volumes (i.e.
uncorrected) and reference T2 HASTE volumes.
For the MoCo, we compare the change in position of the original R->L
volumes versus the corrected volume. Finally, for the IVIM fit, we numerically
evaluate the improvement in the precision parameters by computing their coefficient of
variation (CV) over 100 wild-bootstrap repetitions [10].Results
Figures 1 and 2 compare
the reference HASTE image against the original R->L, L->R images, as well
as the distortion corrected R->L image. The original R->L and L->R
images present large geometric distortions in the direction of the phase
encoding (left to right) that warp the kidneys, particularly the upper half.
After distortion correction, the kidneys are in better alignment with the
reference image. We illustrate the motion of the kidneys in time over 168 DW-MR
images in Figure 3. A line of voxels (indicated by the red line) for each
kidney is plotted across all DW-MR images for the original L->R image
(without Di-correction) and Di-corrected image and DiMo-Corrected image. Before
Di-Mo-Correction, the plots show oscillatory motion of the kidneys due to
breathing as well as increased artifacts due to distortion. After
Di-correction, the geometric distortion is reduced and after Di-MoCo, the
oscillations due to breathing motion is reduced and the kidneys are aligned in
all DW-MR images. The precision of the IVIM model parameters increased when
using the Di-MoCo technique (Table 1). The CV of the perfusion fraction reduced
from 0.42 +/- 8.3 to 0.075 +/-0.8 when applying the proposed Di-MoCo-DW-MRI.
Finally, we show an example map of the estimated IVIM and DTI parameters in
Figure 4.Conclusions
We presented a method for
simultaneous geometric distortion (Di) and motion compensation (MoCo) for DiMoCo-DW-MRI
of the abdomen. Our method corrects for the B0 field inhomogeneity
related geometric distortions and the misalignments due to breathing motion. Our
results indicate that the proposed method successfully corrected for distortion
and compensated the motion of the kidneys. Consequently, the image quality and
the precision of the estimated IVIM model parameters improved with a reduction
of the CV with the DiMoCo-DW-MRI technique.Acknowledgements
This work was supported partially by the Boston
Children's Hospital Translational Research Program Pilot Grant 2018, Society
of Pediatric Radiology Multi-center Research Grant 2019, Crohn’s and
Colitis Foundation of America’s (CCFA) Career Development
Award and AGA-Boston Scientific Technology and Innovation Award
2018 and by NIDDK of the National Institutes of Health under award number
R01DK100404.References
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