Onur Afacan1, W. Scott Hoge2, Tess E. Wallace1, Tobias Kober3,4,5, Daniel Nicolas Splitthoff6, Ali Gholipour1, Sila Kurugol1, Camilo J. Cobos1, Richard L. Robertson1, and Simon K. Warfield1
1Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, United States, 2Brigham and Women's Hospital and Harvard Medical School, Boston, MA, United States, 3Advanced Clinical Imaging Technology, Siemens Healthcare, Lausanne, Switzerland, 4Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland, 5École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland, 6Siemens Healthcare, Erlangen, Germany
Synopsis
Large head motion induces different local magnetic-field
inhomogeneities, even if the field of view is corrected prospectively. In this
work, we implemented and evaluated a diffusion-weighted dual-echo EPI sequence
that prospectively corrects for motion using real-time measurements from an
optical tracker and uses echoes acquired with reversed phase-encoding to
correct for the distortions resulting from the induced local magnetic field
inhomogeneities. We evaluated our motion and distortion correction framework in
volunteer experiments undergoing controlled motion, and in pediatric patients
undergoing routine MRI. Prospective motion correction using our proposed method produced high-quality diffusion parameter
maps in all volunteer and patient scans.
Introduction
Head motion during MRI acquisition
reduces image quality and increases the overall cost of MRI1,2. This
is a particularly challenging problem in diffusion weighted MRI (DW-MRI) as DW-MRI relies on encoding the amount
and direction of the movement of water molecules, which is highly sensitive to patient motion. Many retrospective3,4,5 and prospective6,7,8,9 methods
have been proposed to tackle this problem but the adaptation of these
techniques to clinical practice has been limited, especially in the case of
uncooperative populations such as young children. Most of these methods suffer
from either slow pose update rates, and/or uncorrected local magnetic field
changes that are exacerbated by large motion. In this work, we propose and evaluate a
solution that uses highly accurate and fast motion measurements from an optical
tracker to prospectively update the FOV, and acquires a second echo10
with opposing phase-encoding direction to enable the estimation and correction
of motion-induced field changes.Methods
All the sequence development and
MR image acquisition was performed at 3T (MAGNETOM Prisma, Siemens Healthcare,
Erlangen, Germany) with an in-bore optical tracking system (Kineticor Inc). A
product spin-echo EPI sequence was modified to add a second readout matching
the first readout in terms of resolution, FOV and bandwidth, but with reversed
k-space traversal in the phase-encoding direction.
Optical tracking motion
measurements were used to update the FOV using a motion-correction (MoCo) module in
the sequence. The FOV was updated continuously during the scan except during
the EPI readouts. The sequence was tested on controlled-motion volunteer
studies and pediatric patients undergoing clinical MRI.
All subjects provided
written informed consent.
Volunteer studies: Four volunteers (age 28-38; 2
females, 2 males) were scanned. For all the volunteer studies, a standard
30-direction single shell diffusion weighting with a b-value of 1000s/mm2 (b1000) and five images without any diffusion
encoding gradients (b0) were acquired. Sequence parameters were TE1/TE2=72/108
ms, GRAPPA=2, TR=12000 ms, FOV=256 mm, 2-mm isotropic
resolution with 70 slices, resulting in a scan time of 6 minutes. For comparison,
a single echo acquisition would have TR=9300ms with these settings. A
T2-weighted FSE sequence was also acquired to provide a structural reference. Four sets of data were acquired on each volunteer: 1) No motion with noMoCo,
2) No motion with MoCo, 3) Motion with noMoCo and 4) Motion with MoCo. For the
motion cases, volunteers were asked to move their head to a different position
using audio cues every minute.
Patient studies: Five pediatric patients (age
7-17, 1 female 4 males) were scanned. In addition to the clinical fast
diffusion protocol, a dual-echo prospectively corrected scan with matching
sequence parameters was acquired. Six-direction diffusion tensor imaging with a
b-value of 1000s/mm2 and one image without any diffusion
encoding gradients were acquired. Sequence parameters were TE1=72ms, TE2=108ms, GRAPPA=2, TR=8000 ms, 2 mm in plane
resolution with forty 4-mm slices, resulting in a scan time of 1:40 minutes.
Images were reconstructed offline
and fed into a distortion correction algorithm using FSL’s topup11.
Fractional anisotropy (FA) maps were calculated for each diffusion scan using
in-house developed software.Results
Figure 1 shows an example from a volunteer study, where
axial slices for the first echo are shown from the first b1000 volume and the
last b1000 volume. Figure 2 shows the same data for the second echo. Motion
correction did not produce additional artifacts when the subject was not moving
and improved the results significantly when the subject was moving. Figure
3 shows the resulting FA maps from each set, with and without the proposed
distortion correction strategy. The RMSE between the ground truth (no motion; noMoCo) and the other three sets were 2.56±1.21 (no motion; MoCo), 8.44±3.21 (motion;
noMoCo) and 3.21±1.55 (motion; MoCo) percent over the 4 volunteers in the distorted corrected set. The
maximum motion was 6mm/deg and mean motion was 1.8mm/deg over all 4 volunteer
motion scans. Figure 4 shows the brain boundary, calculated from a structural
scan overlaid on DW-MRI images. Motion and distortion corrected images show a
much better alignment when the subject is moving. Figure 5 shows example diffusion
parameter maps from an 11-year-old male patient, with the motion trace. Our
correction resulted in reliable parameter estimates even when the subject moved
up to 8mm/deg.Discussion and Conclusion
Our results demonstrate that prospective motion correction
worked reliably on all the volunteer cases. When there was no motion, the
results were equivalent to the no correction scans. When there was motion the
RMSE was substantially improved compared to no motion-correction. As can be
seen from Figure 3, the distortion correction further improves the results of
the prospective motion-correction algorithm. Although the prospective motion-correction
algorithm reliably moves the FOV to the correct position, due to the different
local magnetic field changes, different head positions inside the bore result
in different distortion, creating artifactual changes in FA. This effect is most
clearly visible in the areas close to
large susceptibility changes, such as in the frontal lobes near the sinuses.
Our initial results in patients also show that this technique is promising and
can be used to improve the clinical diffusion MRI acquisitions in pediatric
populations. More clinical validation is needed to establish the efficacy of
the method.Acknowledgements
This research was supported in part by the following grants: NIH-R01EB019483, NIH-R01NS079788, NIH-R01EB018988, and a pilot grant (PP-1905-34002) from National Multiple Sclerosis Society.References
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