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Ultrashort echo time magnetization transfer (UTE-MT) imaging in the cuprizone mouse model of multiple sclerosis
Caroline Guglielmetti1,2, Tanguy Boucneau2, Peng Cao2, Annemie Van der Linden3, Peder E.Z Larson2,4, and Myriam M. Chaumeil1,2

1Physical Therapy and Rehabilitation Science, University of California San Francisco, San Francisco, CA, United States, 2Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States, 3Pharmaceutical, Veterinary and Biomedical Sciences, Bio-Imaging Laboratory, Antwerp, Belgium, 4Berkeley and University of California, UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, CA, United States

Synopsis

We first evaluated the potential of ultrashort echo time magnetization transfer (UTE-MT) and MT imaging to generate high contrast images of the healthy mouse brain.

Next, we conducted a longitudinal study to examine the temporal changes of UTE-MT ratio (UTE-MTR) and MTR following cuprizone (CPZ)-mediated demyelination, gliosis, and remyelination. UTE-MTR detected CPZ-induced alterations in white matter, subcortical, and cortical grey matter during demyelination, and persistent tissue microstructure changes in grey matter. Furthermore, UTE-MTR changes correlated significantly with myelin levels.

Altogether, we showed that UTE-MT imaging holds great potential to improve characterization of brain lesions in MS at clinical field strength.

Introduction

Alterations in myelin integrity are involved in many neurological disorders, including multiple sclerosis (MS)1. Although magnetic resonance imaging (MRI) is the gold standard method to diagnose and monitor MS patients, most MRI protocols show limited specificity for myelin detection, notably in grey matter2,3. In this study, we implemented two imaging sequences that have demonstrated sensitivity to myelin content, namely magnetization transfer imaging (MT) and ultrashort echo MT (UTE-MT)4-8, on a clinical 7Tesla MRI scanner. We applied these methods to the cuprizone (CPZ) mouse model9-11, and evaluated their potential to assess brain myelin following demyelination with high level of gliosis, and subsequent remyelination.

Methods

Experimental setup: Adult C57/BL6J mice (n=30) received a CPZ diet (0.2%) for six weeks to induce brain demyelination/neuroinflammation, then normal chow for six weeks. Six mice underwent longitudinal MRI prior CPZ administration (W0), after four weeks (W4 CPZ), six weeks (W6 CPZ) of CPZ diet, and six weeks of recovery (W6 CPZ + W6 recovery). Separate mice (n=24) were euthanized at each time point for immunofluorescence analyses.

MR acquisitions: MR acquisitions were performed on a GE 7T system. 3D UTE was acquired using: TR=20ms, TE1=76µs (UTE), TE2=3000µs, NA=4, voxel sixe=200*200*500µm3, with (saturated) and without (unsaturated) a magnetization transfer RF preparation pulse (-1800Hz offset frequency).

MR analyses: UTE-MT ratio (UTE-MTR, TE1=76μs) and MTR (TE2=3000μs) maps were reconstructed using the following formula: MMTR=(|Munsaturated|-|Msaturated|)/|Munsaturated|.

Regions of interest (ROI) were delineated on the corresponding maps, and include: I) White matter tracts: splenium, genu, internal capsule; II) Subcortical areas: thalamus, caudate/putamen, hippocampus; III) Cortical areas: retro-spinal, somatosensory, motor cortices, Figure 1.A.

Immunofluorescence: Immunofluorescence was performed for myelin basic protein (MBP) and gliosis (GFAP).

Statistics: Results are expressed as mean±SD. Statistical significance was evaluated using a One-Way or repeated measures ANOVA, (post-hoc Tukey correction). MR parameters correlation to myelin or gliosis was assessed using linear regression (*p<0.05, **p<0.01, ***p<0.001, ****p<0.0001).

Results

First, we evaluated the potential of UTE-MTR and MTR to detect cerebral substructures in the healthy mouse brain (Figure 1.B). UTE-MTR and MTR detected differences within substructures presenting different MBP content (Figure 1.C-F). Importantly, UTE-MTR could detect differences between a higher number of subregions, including: genu and internal capsule (p=0.0002), caudate/putamen and thalamus (p<0.0001) and cortical areas (p≤0.0089).

Next, we investigated whether UTE-MTR and MTR could detect dynamic changes following CPZ-induced demyelination and after recovery/remyelination (Figure 2.A). UTE-MTR maps clearly showed the hypointense splenium at W4 CPZ compared to W0, and its increased contrast back to hyperintense at W6 CPZ and after recovery, mirroring the myelin changes observed with immunofluorescence (Figure 2.B-C).

Quantitative analyses revealed that UTE-MTR detected demyelination in the splenium (p<0.0001 at W4 CPZ), genu and internal capsule, and remyelination, while MTR detected demyelination of the splenium (p=0.0491 at W4 CPZ) and genu, but only remyelination of the splenium (Figure 2.D-L).

In the subcortical areas, myelin levels were decreased following CPZ diet and recovery (p≤0.0017 thalamus, p≤0.0003 caudate/putamen). UTE-MTR were decreased in thalamus and caudate/putamen (p≤0.0477, p≤0.0490, respectively). MTR was decreased only in the caudate/putamen. No changes were detected for the hippocampus despite demyelination (Figure 3).

In the cortical areas, severe demyelination was observed, reaching its maximum at W6 CPZ (p<0.0001). Only UTE-MTR were decreased following CPZ administration. Interestingly, UTE-MTR remained lower after recovery, indicating long-lasting changes (Figure 4).

Last, we evaluated the association of UTE-MTR with the underlying tissue pathology (Figure 5). A significant correlation was observed between UTE-MTR and MBP for white matter (r2=0.21-0.78), subcortical (r2=0.35-0.51) and cortical (r2=0.19-0.28) regions. In contrast, UTE-MTR were correlated to GFAP only in white matter (r2=0.18-0.61) and subcortical areas (r2=0.17-0.47) (Figure 5, Table 1).

MTR were correlated to MBP and GFAP in white matter (r2=0.2-0.42 and r2=0.3, respectively), and subcortical areas (r2=0.23-0.5, r2=0.19-0.41, respectively) (Figure 5, Table 2).

Discussion

We demonstrated that UTE-MTR and MTR changes correlated with myelin loss, and to a lesser extent gliosis. The UTE-MTR contrast can be a combination of direct saturation of bound protons in the myelin membranes detectable by UTE12 and indirect MT effect on free water protons. We speculate that the major contribution comes from indirect MT saturation since we measured bound myelin protons T2*≈0.2ms in vivo at 7T and is thus challenging to image. The UTE-MTR has an advantage over MTR because it is more sensitive to MT saturation of the myelin water.

Altogether, we showed that UTE-MT imaging can detect brain tissue alterations in white and grey matter that correlate with changes in myelination, thus appearing as a clinically translatable sequence that may improve characterization of damaged brain tissue in neurological disorders.

Acknowledgements

This work was supported by research grants: NIH R21NS089004, R01NS102156, NMSS research grants PP3360 and RG-1701-26630, fellowship from the NMSS (FG-1507-05297) and from the Flemish Institute for Science and Technology.

References

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Figures

Figure 1. (A) ROIs delineations of white matter tracts (orange), subcortical (blue) and cortical (green) areas. (B) UTE-MTR and MTR maps from a control (W0) brain. White matter tracts are displayed as hyper-intense structures. (C) MBP immunofluorescence images from a healthy mouse brain and (D) corresponding percent coverage of MBP staining. UTE-MTR (E) and MTR (F) can detect differences between ROIs of different myelin content, however only UTE-MTR can differentiate between genu and internal capsule (p≤0.0269), caudate/putamen and thalamus (p<0.0001), and cortical motor cortex/somatosensory cortex and retro-spinal cortex (p=0.0089, and p=0.0065, respectively), thus more closely reflecting the MBP coverage results.

Figure 2. (A) Experimental outline indicating MRI and immunofluorescence timepoints. (B) UTE-MTR maps show loss of contrast from the splenium at W4 CPZ, followed by reappearance of contrast at W6 CPZ and after recovery, mirroring the demyelination/remyelination pattern shown by (C) MBP immunofluorescence staining (inverted grayscale). (D) MBP, (E) UTE-MTR and (F) MTR of the splenium, showing decreased UTE-MTR and MTR, mirroring demyelination/remyelination. (G) MBP, (H) UTE-MTR and (I) MTR of the genu indicating demyelination and remyelination. (J) MBP, (K) UTE-MTR and (L) MTR of the internal capsule. Only UTE-MTR was decreased at W6 CPZ, time point of maximal demyelination.

Figure 3. (A) MBP and (B) UTE-MTR of the thalamus were significantly decreased after W4 CPZ, W6 CPZ and W6 CPZ + W6 recovery while (C) MTR remained unchanged. (D) MBP, (E) UTE-MTR and (F) MTR from the caudate/putamen were reduced following CPZ diet, but only MBP and UTE-MTR remained lower after recovery period, indicating persistent demyelination despite the removal of CPZ. (G) MBP of the hippocampus revealed demyelination following CPZ diet, and remyelination upon withdrawal of CPZ. However, despite myelin alterations, (H) UTE-MTR and (I) from the hippocampus remained unchanged.

Figure 4. (A) MBP and (B) UTE-MTR of the retro spinal cortex were significantly decreased after W4 CPZ, W6 CPZ and W6 CPZ + W6 recovery, while (C) MTR of the retro spinal cortex remained unchanged. (D) MBP and (E) UTE-MTR from the somatosensory cortex were reduced after W6 CPZ diet and W6 CPZ + W6 recovery, indicating CPZ-induced long lasting cortical damages. (F) MTR of the somatosensory cortex remained unchanged. (G) MBP and (H) UTE-MTR of the motor cortex revealed demyelination following CPZ diet and incomplete remyelination after recovery and (I) MTR of the motor cortex remained unchanged.

Figure 5. (A) Significant correlations between UTE-MTR and myelin (MBP, red) or between UTE-MTR and gliosis (GFAP, grey) immunofluorescence, was observed for the splenium (r2=0.78 and r2=0.18, respectively). (B) Significant correlation between UTE-MTR and MBP and GFAP was found for the thalamus (r2=0.51 and r2=0.47, respectively). (C) For the retro spinal cortex, a significant correlation was found only between UTE-MTR and MBP (r2=0.28). Table 1 shows UTE-MTR – MBP and UTE-MTR – GFAP correlation parameters, and Table 2 shows MTR – MBP and MTR – GFAP correlation parameters, for every ROI.

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)
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