Tim Luo1, Shrushrita Sharma2, Mark Polivchuk3, Peng Zhai4, and Yunyan Zhang4
1Bachelor of Health Sciences, University of Calgary, Calgary, AB, Canada, 2Biomedical Engineering Program, University of Calgary, Calgary, AB, Canada, 3Computer Science, University of Calgary, Calgary, AB, Canada, 4Radiology and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
Synopsis
Changes in myelin integrity are associated with many
neurological diseases. We acquired 9.4T MRI from healthy mouse brain to
evaluate the utility of texture heterogeneity in T2-weighted MRI for assessing
myelin integrity, in comparing with proposed measures including magnetic
transfer ratio and myelin water fraction. Measurements were focused on the
corpus callosum, with both anatomical (genu, body, splenium) and hemispheric (left,
center, right) locations evaluated. All 3 methods showed the uniformity of myelin
in corpus callosum between hemispheres, and no significant differences between anatomical
locations were detected. Texture
heterogeneity showed the best consistency between animals and deserves further
verification.Purpose
To evaluate the utility of using texture heterogeneity
in T2-weighted MRI to assess myelin integrity as compared to magnetization
transfer ratio (MTR) and myelin water fraction (MWF), with validations by the corpus
callosum in healthy mouse brain.
Methods
We acquired brain MR images from a 9.4T scanner
(Brucker BioSpin, Ettlingen, Germany)
from 7 healthy mice in vivo. Whole
brain imaging was conducted for T2-weighted MRI using a RARE sequence (TR/TE = 4000/15ms;
slice thickness = 0.5mm, 12 averages; matrix = 256x256, 25 slices) and for MT
imaging (TR/TE =5000/15ms; MT power = 5 mT/m; pulse number = 60; matrix =
128x128; and slice thickness = 1mm). Single-slice multi-echo T2 MRI was
acquired from the central location of T2 imaging (TR/TE = 3000/6ms; matrix =
128x128; slice thickness = 1mm, 128 echoes). Our measurements were focused on the corpus
callosum (CC) as this is the largest inter-hemispheric white matter structure
with highly organized white matter tracts. MTR was measured as the signal
intensity ratio between images with and without off-resonance pulses [1], MWF
as the fraction of water content with relaxation equal to or shorter than 40 ms
using an open-source software [2] and texture heterogeneity as the similarity
of multi-scale MRI spectra localized at individual image voxels using a spatial
frequency-based approach [3]. Lower heterogeneity reflects greater coherency.
Imaging outcomes were recorded as per anatomy (genu,
body and splenium) and hemispheric locations (right, center, and left) of the
corpus callosum. Based on an established atlas [4] (Figure 1), we identified 5 slices
in T2-weighted MRI to examine the corpus callosum: 1 slice for the genu, 3 for
the body, and 1 for the splenium (Figure 2). Regions of interest (ROIs) were drawn
along the boundary of the corpus callosum using ImageJ (NIH, USA) in selected image
slices. Identified image and ROIs were then matched to the corresponding
locations in MTR and MWF images for quantification. Outcome differences were evaluated
using a mixed-effect modeling method that accommodated the variances both
between animals and between imaging slices within an animal. For MWF, only differences
between hemispheric locations were evaluated as only one slice was acquired to
minimize the imaging time.
Results
We assessed 35 images with 105 ROIs in T2-weighted MRI
that included 21 ROIs for the genu, 63 for the body, and 21 for the splenium. Of
the 35 images, 21 were corresponded to the MTR maps and that identified the
body and splenium only, due to differences in imaging protocols (Figures 3). We
found that there was no significant difference between left, central, and right
ROIs of the corpus callosum using any method (p>0.05). While MTR showed a
trend to difference between the body and splenium, it did not reach
significance and there was no difference between anatomical locations of the corpus
callosum in texture heterogeneity. Between animals, texture heterogeneity exhibited
the smallest variance between animals, with the mean and standard deviation
(bracket) ranged from 0.176 (0.06) to 0.192 (0.05). The range of MTR was intermediate,
from 0.473 (0.04) to 0.531 (0.02), and MWF had the largest variability, ranging
from 0.403 (0.02) to 0.913 (0.02) (Figure 4). There were no significant
outliers in any of these measurements or in any animal.
Discussions
Changes in myelin integrity are associated with many
neurological diseases that demand reliable assessment. MTR and MWF are two of
the most recognized measures of myelin content, but both need additional pulse
sequences for acquisition. Based on clinical scans, texture heterogeneity measures
the organization of tissue structure indicated by the distribution pattern (texture)
of MRI voxels. Previously, studies showed that texture heterogeneity derived from
T2-weighted MRI correlated with the severity of pathology in patients with
multiple sclerosis, and that the relationship was stronger with myelin content than
with axonal injury and inflammation. In this study, we found that texture
heterogeneity showed a similar trend as MTR but with less variability between
animals, consistent with the uniformity of myelin as expected in healthy white
matter. MWF showed a large variability between animals, likely due to the small
number of MRI slices or the quality of multi-echo images acquired that require
further confirmation.
Conclusion
All three methods confirmed
the uniformity of myelin structure in the corpus callosum between hemispheres. Given the advantage of having high consistency between animals, texture
heterogeneity deserves further verification as an alternative measure of myelin
integrity using standard MRI scans.
Acknowledgements
We
thank the Summer Studentship support (Luo) from the O’Brien Centre, Bachelar of
Health Sciences, University of Calgary, and the funding supports for the
project from the Natural Sciences and Engineering Council of Canada, MS Society
of Canada, and Alberta Innovates – Health Solutions, Alberta, Canada.References
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