Using diffusion MRI to study demyelination in cortex and deep gray matter in animal model of multiple sclerosis
Tina Pavlin1,2, Vanja Flatberg3, Renate Gruner2,4, Erlend Hodneland5,6, and Stig Wergeland7,8

1Molecular Imaging Center, Department of Biomedicine, University of Bergen, Bergen, Norway, 2Department of Radiology, Haukeland University Hospital, Bergen, Norway, 3Department of Physics, University of Bergen, Bergen, Norway, 4Department of Physics and Technology, University of Bergen, Bergen, Norway, 5Christian Michelsen Research, Bergen, Norway, 6MedViz Research Cluster, Bergen, Norway, 7KG Jebsen Centre for MS-Research, Department of Clinical Medicine, University of Bergen, Bergen, Norway, 8The Norwegian Multiple Sclerosis Competence Centre, Department of Neurology, Haukeland University Hospital, Bergen, Norway

Synopsis

We have applied a biophysical model of diffusion to study dendrite density and diffusion in cortex and deep gray matter in an animal model of MS. We have performed DTI on mice brains ex-vivo at baseline, after 3 and 5 weeks of cuprizone exposure, and 4 weeks after termination of exposure. We observed a significant drop in neurite density and an increase in intra-axonal diffusion at 3 and 5 weeks of exposure, and a recovery to baseline values after remyelination. Our study shows the potential of DTI to detect subtle changes in myelin content in gray matter, thereby improving out understanding of the disease.

Purpose

Conventional MRI techniques have a very low sensitivity to gray matter demyelination. However, novel MRI techniques, such as magnetization transfer imaging, show potential to detect myelin content in gray matter1. In this work we investigate whether diffusion-weighted MRI that is based on biophysical models of tissue microstructure2,3 can detect demyelination in deep gray matter and cortex in the curpizone mouse model of MS.

Methods

Animals: A total of 20 female c57Bl/6 mice were divided randomly into 4 groups of 5 mice each. Three of the groups were exposed to cuprizone rich diet by adding 0.2% cuprizone to milled mouse chow and then sacrificed after 3 and 5 weeks of cuprizone exposure, and 4 weeks after ending the 5-week cuprizone exposure. The control mice were sacrificed at the end of the experimental period. Mice were euthanized by CO2 asphyxiation, followed by intracardial perfusion with 4% formalin in PBS (phosphate-buffered saline). Brains were extracted, stored at 4oC in 4% formalin, and then transferred to PBS 48 hours before scanning to remove formalin which degrades T2 relaxation time. Finally, brains were placed into a custom-made acrylic holder and transferred to a 15 ml plastic tube that was filled with Fomblin oil (perfluoropolyether Y04 grade fluid).

MRI: Scanning was performed on a 7T horizontal-bore magnet using a head (23 mm ID) quadrature volume resonator (both from Bruker Corporation, Germany). Diffusion-weighted EPIs were acquired using a Stejskal-Tanner spin-echo diffusion preparation. Imaging parameters were: 128x128 data matrix, resolution 98μmx98μm, slice thickness 0.75 mm, TR/TE=3s/33.49 ms, Navg=6. Total scan time was 3 hours 18 min. Diffusion parameters were: δ/Δ = 6 ms/20 ms. Sixteen b-factors ranging linearly from 880 to 14080 s/mm2, 10 diffusion directions, and five A0 images were acquired.

Analysis: Images were analysed in MATLAB (R_2013a, MathWorks) using Jespersen’s et al.2,3 dendrite density model of gray matter. Their biophysical model of tissue microstructure assumes that the MR diffusion signal originates from two components: (i) the dendrites and axons (i.e. neurites), modeled as long cylinders with one diffusion coefficient parallel (DL) to the cylindrical axis (DT=0 due to the diffusion resolution limit), and (ii) an isotropic mono-exponential diffusion component (Dext) describing water diffusion within extracellular space. The results of the fit were parametric maps of neurite density, DL and Dext. Region-of-interest (ROI) analysis was performed by selecting ROIs in the right CX and in DGM within a slice which was the same for all animals. Mean values within the ROIs were recorded and used to compute the population mean and standard error. Wilcoxon rank sum test was used to compute significant differences between groups.

Results

Figure 1 shows parameteric maps of relative neurite density for one representative animal within each group. There is a visible reduction in neurite density in DGM and CX after 5 weeks of exposure, and remyelination 4 weeks after terminating the exposure. Figure 2 shows mean values of neurite density, Dext and DL from ROI analysis of CX and DGM for 5 animals in each of the groups and 95% confidence intervals. We detected significant differences (p<0.05) in the values of neurite density and DL between baseline and at 3 and 5 weeks of cuprizone exposure in both DGM and CX. After 3 weeks of exposure, neurite density decreased by 16% and DL increased by app 20%. There were no significant differences in values between 3 and 5 weeks of exposure. Both, the neurite density and DL returned to the baseline values (0.5 and 0.8-1.0 μm2/ms, respectively) after remyelination. Extracellular diffusion in DGM and CX did not change significantly as a result of cuprizone exposure and had mean values between 0.27 and 0.35 μm2/ms for all experimental groups.

Discussion

Our measurements showed that the neurite volume fraction decreased while the longitudinal diffusion coefficient increased with cuprizone exposure. Myelin presents a barrier to spin motion so when myelin is lost, spins can move more freely in all directions, decreasing diffusion anisotropy and increasing diffusion coefficient. On the contrary, the extracellular diffusivity did not change significantly with cuprizone exposure. This could be understood in light of the fact that the extracellular space and cell bodies occupy only approximately 18% of mouse cortex, so any changes in extracellular diffusion coefficient, which is in addition small due to highly restricted extracellular space, will not be easily detectable.

Conclusion

In this work we have demonstrated that the degree of demyelination in the cuprizone mouse model of MS correlates well with the neurite density and intra-axonal diffusion parameter of the Jespersen's dendrite density model and therefore could serve as markers of demyelination.

Acknowledgements

We would like to thank Sune Nørhøy Jespersen and Brian Hansen (Aarhus University, Denmark) for providing their Matlab script with the neurite density model and for advising us on various aspects of data analysis.

References

1. Fjær S, Bø L, Lundervold A, Myhr K-M, Pavlin T, Torkildsen O, et al. Deep gray matter demyelination detected by magnetization transfer ratio in the cuprizone model. PLoS ONE. 2013; 8(12):e84162.

2. Jespersen SN, Kroenke CD, Østergaard L, Ackerman JJH, Yablonskiy DA. Modeling dendrite density from magnetic resonance diffusion measurements. Neuroimage. 2007; 34(4):1473–86.

3. Jespersen SN, Bjarkam CR, Nyengaard JR, Chakravarty MM, Hansen B, Vosegaard T, et al. Neurite density from magnetic resonance diffusion measurements at ultrahigh field: comparison with light microscopy and electron microscopy. Neuroimage. 2010; 49(1):205–16.

Figures

Figure 1: Neurite density maps. Top left: control; top right: 3 weeks of exposure; bottom left: 5 weeks of exposure; bottom right: after remyelination.

Figure 2: Group mean values and 95% confidence intervals for relative neurite density (left), extracellular diffusion coefficient (in μm2/ms, middle), and longitudinal diffusion coefficient (in μm2/ms, right) in deep gray matter. The four groups are 1) controls, 2) 3 weeks of exposure, 3) 5 weeks of exposure, 4) after remyelination.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
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