Seungeun Lee1, Seung Yun Lee1, and Joon-Yong Jung1
1Radiology, Seoul St.Mary's Hospital, Seoul, Korea, Republic of
Synopsis
Keywords: Bone, Artifacts
Motivation: Metal artifact reduction techniques needs longer scan time and shows incomplete MRI visibility for postoperative spinal evaluation.
Goal(s): We assessed the reliability of localizer sequence image factors for predicting the metal artifact range in MRI.
Approach: Multivariate ordinal logistic regression models were generated using prosthesis information and imaging factors measured on localizer images, to verify the factors correlated to the visibility of spinal canal and neural foramen on MRI.
Results: Metal artifact degree at midline and foramen level of sagittal plane and inter-screw distance of coronal plane in localizer images were significant factors affecting metal artifact range of MRI.
Impact: We found that the
metal artifact degree in localizer sequence image can be correlated with the
metal artifact range of diagnostic sequence image, and used to screen proper
patients to apply metal artifact reduction sequence in postoperative spinal MRI.
Introduction
Metal artifact on postoperative spine magnetic resonance
imaging (MRI) has been a common concern, so several
MR techniques to reduce these artifacts have been clinically attempted,
including conventional metal artifact reduction (MAR) strategy using
high-readout bandwidth, view-angle tilting (VAT) and slice-encoding for metal
artifact correction (SEMAC) (1, 2). However, a substantial proportion of
metal-induced artifacts persists and disrupts the image interpretation in
spinal imaging (3, 4). Localizer sequence of MRI accounts for the small proportion
of entire data set, but it can provide adequate information relevant with image
findings on diagnostic sequence (5, 6). In this study, we assessed whether localizer
sequence image (MR-L) factors can be reliably correlated with metal artifact range
in conventional diagnostic sequence MRI (MR-D).
Methods
Patient inclusion
Patients with lumbar
spinal fusion surgery and postoperative MRI between January 2019 and April 2022
were included. The clinical information including the type of interbody graft, transpedicular
screw diameter and level of rod length were reviewed.
MRI scans
Lumbar spinal MRI was
acquired by three 3-Tesla scanners. MR-L was based on gradient-echo (GRE) sequence
(TR/TE=8/3.69ms, thickness=6mm, FOV=350x350, matrix=256x205) and composed of
less than 5 sagittal and 5 coronal plane images. MR-D was consisted of two-dimensional
fast spin-echo (FSE) T2-weighted image in sagittal (TR/TE=3300/99ms,
thickness=3mm, FOV=280x280, matrix=320~512, readout bandwidth=200~450) and
axial planes (TR/TE=4000/95ms, thickness=3~7mm, FOV=160x160, matrix=256~512,
readout bandwidth=180~500).
Imaging evaluation
Two radiologists (R1,
R2) evaluated the MR-L and MR-D according to following criteria, respectively. On
MR-L, metal artifact degree was evaluated in 3-scale grading system on sagittal
plane at midline (sag-midline) and neural foramen (sag-foramen) levels. Also,
we measured the distance between bilateral transpedicular screws (cor-distance)
and the diameter of unilateral screw-derived artifact (cor-diameter) at foramen
level on the coronal plane. Lastly, scoliosis degree was measured using Cobb’s
angle. On MR-D, the visibility of spinal canal and neural foramen was graded in
5-scale confidence score at the axial and sagittal image, respectively.
Statistics
Two multivariate
ordinal logistic regression models were generated to respectively predict the
visibility of spinal canal and neural foramen, after the selection of statistically
significant clinical and MR-L factors using univariate ordinal logistic
regression. The inter-machine and intra-machine reliability of MR-L factors were evaluated using kappa analysis and intraclass correlation
coefficient, using the MRI of the patients who scanned on the same or different
MRI scanner more than once.
Results
Total 163 patients
were included, and 14 and 26 patients had two follow-up MRIs scanned on same
and different MRI scanner, respectively. Also, 6 patients had follow-up MRIs
with conventional MAR sequence. The median value of screw diameter and rod
level length were 6.5mm and 2 vertebral body levels, respectively. The most
frequently inserted interbody graft was TLIF.
The level of rod
length (p<0.001 in R1 and R2), sag-midline score (p=0.009 and 0.03 in R1 and
R2) and cor-distance score (p=0.001, p<0.001 in R1 and R2) were significant MR-L
factors to predict the visibility of spinal canal on MR-D in both radiologists.
Also, transpedicular screw diameter (p=0.005 and 0.6 in R1 and R2), sag-foramen
score (p=0.001 and 0.04 in R1 and R2) and cor-distance score (p=.0.004 and
0.001 in R1 and R2) were significant MR-L factors to predict the visibility of
neural foramen on MR-D in R1, and the result of R2 analysis was same except for
the transpedicular screw diameter (Fig.1 and 2, Table 1).
Intra-machine and
inter-machine reliability of MR-L factors were moderate and substantial in
sag-midline score (κ=0.45,
0.69), moderate and slight in sag-foramen score (κ=0.51,
0.16), and moderate and good in cor-distance score (ICC=0.67, 0.86),
respectively (Fig.3 and 4). In 6 MAR sequence MRIs, 2 and 5 patients showed
improved visibility in spinal canal (average confidence score from 1.8 to 1.5)
and neural foramen (average confidence score from 2.3 to 1.2), respectively.
Discussion
Metal artifact
degree on MR-L can be correlated with the metal artifact range on MR-D. Despite
the MAR with FSE sequence over GRE sequence, the basic information from GRE
sequence image can help predicting the metal artifact degree on FSE sequence
image, regardless of the variable MR-D parameter settings. By evaluating
several MAR sequence MRIs, we found that adjusting detailed MAR
parameters can reduce metal artifact in MR-D. Therefore, evaluation of the
metal artifact range on MR-L would be helpful to choose the proper patients to
apply the MAR technique and reduce the scanning workload.
Conclusion
Metal artifact
degree in sagittal and coronal planes of localizer sequence image can
predict the metal artifact range of diagnostic sequence image and screen the proper
patients to apply MAR sequence. Acknowledgements
No acknowledgement found.References
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