Jin Gao1, Rodolfo G Gatto2, Richard Magin1, Andrew C Larson3, and Weiguo Li1,3,4
1Bioengineering, University of Illinois at Chicago, Chicago, IL, United States, 2Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, IL, United States, 3Radiology, Northwestern University, Chicago, IL, United States, 4Research Resource Center, University of Illinois at Chicago, Chicago, IL, United States
Synopsis
Amyotrophic lateral
sclerosis (ALS), a progressive motor neuron disease, is characterized by severe
cervical spinal cord damage caused by degeneration of the corticospinal tracts
and loss of lower motor neurons. Although MR imaging of spinal cord is
challenging, the ubiquity and non-invasive nature of MRI has supported its
continued development and a leading role in ALS biomarker discovery. In this
study, we investigated the feasibility of exploiting high b-value diffusion MRI
to evaluate alterations of the spinal cord in a mouse model of ALS.
PURPOSE
Amyotrophic lateral Sclerosis (ALS), characterized by
progressive motor neuron degeneration, occurs when the myelin sheath
becomes sufficiently damaged.1, 2 Myelin is a white fatty material, composed chiefly of lipids
and lipoproteins. The diffusion behavior of lipid protons has been investigated
by utilizing diffusion magnetic resonance spectroscopy to probe
intramyocellular lipid droplet size in vivo,3,4 For ALS patient, the damaged nerves lose their coating myelin sheath,
with these changes
potentially reflected in altered diffusion properties. The
objective of this preliminary study was to investigate the feasibility of using
high b-value diffusion-weighted MRI to evaluate alterations of the spinal cord in a
transgenic G93A-SOD1 mouse model of ALS.METHODS
All MRI studies were
performed using a 9.4 T MRI scanner (Agilent, Santa
Clara, CA). Two diseased mice (symptomatic
G93A-SOD1) and two control wild type (WT) mice were euthanized (approved by the
IACUC) before the MRI scans. For each measurement, one diseased mouse and one
control were carefully aligned in order to show the two spinal cords in the
same image. A diffusion weighted stimulated echo sequence was applied with
following acquisition parameters: TR/TE = 2000/30.5 ms, mixing time = 382 ms, δ = 11 ms, Δ = 400 ms, slice thickness = 1.5 mm, field of view
(FOV) = 36 mm × 50 mm, matrix = 64 × 96, average = 25, and 30 b-values ranging
from 0 to 858,022 s/mm2 with a maximal diffusion gradient strength
of 50 Gauss/cm. Two diffusion gradient directions were applied with one
direction parallel and the other perpendicular to the long axis of the spinal
cord. T2 weighted images were acquired using a fast spin echo
sequence with parameters: TR/TE = 1000/12 ms, echo train length = 8, matrix = 192
× 256, FOV = 36 × 50 mm, slice thickness = 1.5 mm, averages = 2. Image
post-processing was performed in Matlab (MathWorks). Signal-noise-ratios (SNRs)
were calculated from regions of interest (ROIs) manually drawn from spinal
cords of both diseased and control mice. A bi-exponential decay model5 fitting was applied to the ROIs and voxel-wisely. Axonal
fiber morphology and integrity of the each spinal cord was validated by
histological analysis.RESULTS
In T2-weighted images (Fig. 1A), similar
image intensities were observed in spinal cord regions of the diseased (arrow
pointed) and wild type animals. However, in the diffusion-weighted images (Fig.
1B, C, D, E), wild type animal showed relatively higher signals in the spinal
cord as b-value increased. The measured SNRs from an ROI drawn at the lumbar
level of the spinal cord were found to be much lower for the diseased mouse at all
the b values, when compared to those of the controls (Fig.2A). In addition,
the SNRs were much higher in both animals with the diffusion gradients applied
perpendicular to long axis of the spinal cord, when compared to those with
parallel diffusion-weighting direction (Fig. 2A). We further found a non-linear
relationship existed between the log-scaled SNRs and b-values (Fig. 2). The
bi-exponential model (Fig. 2B) showed a good fit to the SNRs measured at increasing b-values for the data with the diffusion-weighting direction
perpendicular to the spinal cord. The
extracted parameter maps indicated a possible higher fraction of the fast
diffusion components (Fig. 3A) and higher fast diffusion coefficient (Fig. 3B) at
the lumbar level of the diseased animals. The measured diffusion metrics from
an ROI drawn at the lumbar levels of the mice are shown in Table 1. Fluorescence
microscopy demonstrated a significant reduction in myelin density in G93A-SOD1
mice compared to wild type controls (Fig. 4).DISCUSSION
MRI techniques to assess progression of ALS
can be beneficial in clinical settings as a marker for patient prognosis and in
research settings as biological markers for assessing the efficacy of
experimental treatments. In this study, we demonstrated that signal intensity
differences existed in the high b-value diffusion-weighted images between the
spinal cords of G93A-SOD1 mice and wild type controls. The diffusion-weighted
signal decay showed a dependence on the diffusion weighting direction relative
to spinal nerve fiber orientation. We further found, from
the bi-exponential model analysis, that the fraction and diffusion coefficient
of the fast diffusion compartment might be utilized to differentiate and
quantify the progression of ALS in the G93A-SOD1 mouse model of ALS. CONCLUSION
In this preliminary study, we demonstrated the
feasibility of using high b-value diffusion-weighted MRI to evaluate
alterations of the spinal cord in a G93A-SOD1 mouse model of ALS. Further
preclinical and translational studies are needed to validate this method for monitoring
the progression of motor and non-motor neural diseases.Acknowledgements
No acknowledgement found.References
1. Foerster
BR, Welsh RC, Feldman EL. 25 years of neuroimaging in amyotrophic lateral
sclerosis. Nat Rev Neurol 2013;9(9):513-524.
2. Niebroj-Dobosz
I, Rafalowska J, Fidzianska A, Gadamski R, Grieb P. Myelin composition of
spinal cord in a model of amyotrophic lateral sclerosis (ALS) in SOD1G93A
transgenic rats. Folia Neuropathol 2007;45(4):236-241.
3. Xiao
L, Wu EX. Diffusion-weighted magnetic resonance spectroscopy: a novel approach
to investigate intramyocellular lipids. Magn Reson Med 2011;66(4):937-944.
4. Cao P,
Wu EX. In vivo diffusion MRS investigation of non-water molecules in biological
tissues. NMR Biomed 2016;10.1002/nbm.3481.
5. Hoff
BA, Chenevert TL, Bhojani MS, Kwee TC, Rehemtulla A, Le Bihan D, Ross BD,
Galbán CJ. Assessment of Multi-Exponential Diffusion Features as MRI Cancer
Therapy Response Metrics. Magn Reson Med 2010;64(5):1499-1509.