Kamyar Taheri1, Irene M. Vavasour1, Shawna Abel1, Lisa Eunyoung Lee1, Poljanka Johnson1, Stephen Ristow1, Roger Tam1, Cornelia Laule1, Nathalie Ackermans1, Alice J. Schabas1, Jillian Chan1, Ana-Luiza Sayao1, Virginia Devonshire1, Robert Carruthers1, Anthony Traboulsee1, Shannon H. Kolind1, and Adam V. Dvorak1
1University of British Columbia, Vancouver, BC, Canada
Synopsis
Multiple
Sclerosis (MS) is a demyelinating disease of the central nervous system, with
MRI routinely performed for brain but often neglected in spinal cord. When cord
imaging IS performed, atrophy is usually assessed at the C2/3 segment. We aimed
to validate cord cross-sectional-area (CSA) measurements using T1-weighted whole-brain
images. In controls, strong correlations were seen between C1 CSA from cord and
brain images, and between C1 and C2/3 CSA from cord images.
In MS, C1 CSA from brain
images and C2/3 CSA from cord images correlated. We showed that metrics obtained
from brain images could provide relevant cord atrophy measures.
Introduction
Multiple sclerosis
(MS) is an inflammatory, demyelinating disease that causes degeneration of the
central nervous system. Spinal cord lesions are visible in over 80% of MS
patients and correlate with clinical disability1. Spinal cord
atrophy has also been associated with disability, especially for the
progressive phenotypes of MS2. Therefore, cord atrophy measurements
could provide a valuable, clinically relevant metric for the monitoring and
prognosis of MS. The C2/3 segment
of the cervical cord is traditionally used to assess atrophy in MS3.
However, the spinal cord is imaged far less frequently than the brain due to
the artifacts caused by cerebrospinal fluid flow, an inhomogeneous magnetic
environment, small cord cross-sectional area (CSA), and cardiorespiratory motion4.
Furthermore, coil changes are often required when collecting both brain and
cervical cord images, creating practical limitations and hence de-prioritizing
cord imaging2. Fortuitously,
high-resolution T1-weighted brain imaging, which is frequently obtained for MS
brain for volumetric assessment, typically captures the upper cervical C1 cord
region. If C1 CSA accurately reflects C2/C3 CSA, which has been
established as clinically relevant, spinal cord area measures could be obtained
using only a standard T1-weighted brain image. This would dramatically expand
access to information about the spinal cord.
Our objectives
were to compare:
(1) C1 CSA from brain MRI to C1 CSA from cord MRI and
(2) C1
CSA to C2/C3 CSA from cord MRI in healthy controls and MS. Methods
Data were collected from 28
healthy controls and 73 MS participants at 3.0T (Achieva, Philips, Best, The
Netherlands).
Brain imaging
T1-weighted 3D
magnetization-prepared rapid gradient-echo (MPRAGE) (TR/TE/TI=8.1/3.5/1052ms,
shot interval 3000ms, acquired at 1mm isotropic, field-of-view=256x256x165mm3)
using an 8-channel head coil.
Spinal cord imaging
T2*-weighted multi-echo fast
gradient echo (mFFE) centred at the level of the C2/C3 disc (16 slices,
TR/TE1/TE2-5=815/6.6/8.2ms, acquired at 0.8x0.8x2.5mm3,
field-of-view=150x150x44mm3) using a 6-channel spine coil.
Representative images are
shown in Figure 1.
Analysis
Spinal Cord Toolbox5-7 was used to (1) perform automated segmentation of the spinal cord;
(2) label cord levels based on a manually identified C2/C3 disc, vertebral column and intervertebral disc intensities, and a template reference; (3) extract
CSA averaged across C1 and C2/3 levels. Quality of the automated whole-cord
segmentations was not affected by the presence of lesions. Spearman correlation
coefficients (r) and 95% confidence intervals were calculated for relationships
between CSA, based on cord or brain images, at different levels. A group
comparison between brain image C1 CSA and cord image C1 CSA is presented as a mean
with 95% confidence interval and analyzed using Wilcoxon paired t-tests.Results
C1 CSA from brain images versus C1 CSA from cord
images for healthy controls
C1 CSA derived from cord was
positively correlated with brain image-derived C1 CSA (r=0.89 (0.78-0.95), p<0.0001, Figure 2). A non-parametric paired t-test showed a small
but significant mean difference between cord-derived and brain-derived C1 CSA
of 2.41mm2 (1.00-3.82mm2 , p=0.004) (Figure 3).
C1 CSA versus C2/3 CSA from cord images for healthy
controls
C1 CSA was positively
correlated with C2/3 CSA (r=0.94 (0.89-0.97), p<0.0001, Figure 4).
C1 CSA from brain images versus C2/3 CSA from cord
images for MS participants
C1 CSA derived from brain
images was positively correlated with C2/3 CSA from cord images (r=0.81
(0.70-0.88), p<0.0001, Figure 5). Discussion
There was a strong
correlation between C1 CSA obtained from brain and cord images, which supports
the feasibility of acquiring an accurate C1 CSA measurement using T1-weighted
brain images alone. The small bias between brain and
cord image CSA may be due to a consistent difference between the
cord/cerebrospinal-fluid segmentation boundary of T1 and T2* weighted images.
A positive
correlation was seen between C1 and C2/3 CSA using spinal cord scans. Although
C2/3 is traditionally used for CSA analysis, our study indicates that C1 may
also be used. Finally, a strong
correlation was observed between C1 CSA from MS brain images when compared to
their C2/3 CSA using spinal cord images. This further supports the feasibility
of acquiring cord area measurements with brain images in the presence of MS
pathology, reflecting an established and clinically relevant measure of cord
area at C2/C3.
Our data suggests that valuable spinal cord area
information can be obtained using standard 3DT1 brain scans alone. This falls
in line with previous studies done by Liu et al., who showed that
measurement at 2.5cm below the pons in brain images is an appropriate
surrogate for upper cord atrophy8, and Papinutto et al., who
showed excellent C2-C3 area reliability when derived from brain scans9.
Brain imaging also generally acquires a larger field-of-view with higher
resolution and more-isotropic voxels, making it preferable for quantifying
atrophy from a technical perspective. Furthermore, this opens the possibility
to perform retrospective spinal cord atrophy studies on cohorts without spinal
cord imaging. This could help shed light on progression in MS, which is thought
to be closely related to spinal cord atrophy.Conclusion
CSA at the C1 level
calculated from brain scans is strongly correlated with CSA at C2/3 calculated
from separate spinal cord imaging. Measures derived from high-quality brain
imaging could potentially provide convenient, clinically relevant measures of spinal cord
area.Acknowledgements
We would like to thank the
participants for volunteering their time for this study, and the UBC MRI
Research Centre. Funding support for this study was provided by the MS Society
of Canada and an
Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant [F17-05113].
Adam Dvorak is in receipt of a 4-Year Doctoral
Fellowship from the University of British Columbia. References
1. Bot, J.C.,
et al., Spinal cord abnormalities in
recently diagnosed MS patients: added value of spinal MRI examination.
Neurology, 2004. 62(2): p. 226-33.
2. Kearney,
H., D.H. Miller, and O. Ciccarelli, Spinal
cord MRI in multiple sclerosis--diagnostic, prognostic and clinical value.
Nat Rev Neurol, 2015. 11(6): p.
327-38.
3. Healy,
B.C., et al., Approaches to Normalization
of Spinal Cord Volume: Application to Multiple Sclerosis. Journal of
Neuroimaging, 2012. 22(3): p.
E12-E19.
4. Stroman,
P.W., et al., The current
state-of-the-art of spinal cord imaging: Methods. Neuroimage, 2014. 84: p. 1070-1081.
5. Gros, C.,
et al., Automatic segmentation of the
spinal cord and intramedullary multiple sclerosis lesions with convolutional
neural networks. Neuroimage, 2018. 184:
p. 901-915.
6. De Leener,
B., et al., SCT: Spinal Cord Toolbox, an
open-source software for processing spinal cord MRI data. Neuroimage, 2017.
145(Pt A): p. 24-43.
7. Cohen-Adad,
J., et al. Spinal Cord Toolbox: an
open-source framework for processing spinal cord MRI data. in Proceedings of the 20th Annual Meeting of
OHBM, Hamburg, Germany. 2014.
8. Liu Z, Yaldizli Ö, Pardini M, et al.
Cervical cord area measurement using volumetric brain magnetic resonance
imaging in multiple sclerosis. Mult Scler Relat Disord. 2015;4(1):52-57.
9. Papinutto N, Bakshi R, Bischof A, et al.
Gradient nonlinearity effects on upper cervical spinal cord area measurement
from 3D T1 -weighted brain MRI acquisitions. Magn Reson Med.
2018;79(3):1595-1601.