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Advanced MRI in subtypes of multiple sclerosis: T1, T2, water content and diffusion basis spectrum imaging
Irene M Vavasour1, Carina Graf2,3, Shannon H Kolind1,2,3,4,5, Peng Sun6, Robert L Carruthers4, Anthony Traboulsee4,5, GR Wayne Moore3,7, Sheng-Kwei Song6, David KB Li1,4,5, and Cornelia Laule1,2,3,7

1Radiology, University of British Columbia, Vancouver, BC, Canada, 2Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, 3International Collaboration on Repair Discoveries, University of British Columbia, Vancouver, BC, Canada, 4Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada, 5MS/MRI Research Group, University of British Columbia, Vancouver, BC, Canada, 6Radiology, Washington University, St. Louis, MO, United States, 7Pathology & Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada

Synopsis

T1, T2, water content (WC) and diffusion basis spectrum metrics were compared from the normal appearing white matter (NAWM) of 10 clinically isolated syndrome (CIS), 27 relapsing-remitting multiple sclerosis (RRMS), 14 secondary progressive multiple sclerosis (SPMS) and 5 primary progressive multiple sclerosis (PPMS) subjects. SPMS showed higher WC, longer geometric mean T2 and a larger hindered fraction than CIS indicating increased oedema. Fibre fraction (apparent axonal density) was lower in RRMS and SPMS than CIS thought to reflect loss of axons or increased oedema. Advanced imaging can show differences between MS subtypes related to the underlying tissue damage.

Introduction

Although the normal appearing white matter (NAWM) in multiple sclerosis (MS) appears normal on conventional MRI, subtle changes in tissue structure (such as demyelination, axonal loss and gliosis) are present histologically1,2,3.

A number of advanced MRI techniques exist that are sensitive to changes in myelin, axons, oedema and inflammation which may give more information about the underlying tissue pathology in MS. The fraction of water within the myelin bilayers (myelin water fraction, MWF4) has been histopathologically validated as a marker for myelin5. T1 relaxation is closely related to water content (WC)6 and geometric mean T2 (GMT2) relaxation is related to tissue structure. Diffusion basis spectrum imaging (DBSI) models myelinated and unmyelinated axons as anisotropic diffusion tensors, and models cells and extracellular space as isotropic diffusion tensors to simultaneously quantify axonal injury, myelination, inflammation and oedema in the central nervous system7. Numerous measurements can be derived from the DBSI data including: axial diffusivity (related to axonal integrity), radial diffusivity (modulated by myelin8), fibre fraction (a measure of the density of axons9), isotropic restricted diffusion fraction (changes in cellularity resulting from inflammation) and the isotropic hindered diffusion fraction (increases with vasogenic oedema9).

Reduced MWF10, increased T111 and T212, and increased diffusivity13 are well described in MS NAWM, although the majority of MWF reports are from relapsing remitting (RRMS) subjects. Studies examining differences between MS subtypes demonstrate that NAWM abnormalities detected with standard DTI (fractional anisotropy and diffusivities), magnetization transfer and MR spectroscopy are larger in progressive MS than RRMS14,15. Atrophy also varies between MS subtypes with the largest degree found in primary progressive (PPMS), followed by secondary progressive (SPMS), and RRMS16. In this study, we used advanced imaging techniques to compare measures of myelin, axons, oedema and inflammation in the different MS subtypes.

Objective

To compare MWF, T1, GMT2, WC and DBSI-derived metrics in different MS subtypes.

Methods

Subjects and MR Experiments: 56 participants (10 clinically isolated syndrome (CIS), 27 RRMS, 14 SPMS, 5 PPMS) were scanned on a 3T Philips scanner (patient demographics in Table 1). Scanning sequences included 48-echo GRASE T2 relaxation (TR=1073ms, TE=8ms, 1x1x2.5mm3, 40 slices)17, inversion recovery T1 (TIs=150, 400, 750, 1200, 2100ms, TR=3000ms, 1x1x2.5mm3, 40 slices), DBSI (99 directions, range of b values=0-1500, TE=79ms, TR=4798ms, 2x2x2mm3, 40 slices)9, and structural proton-density (PD)/ T2-weighted (TR=2900ms, TE=8.42/80ms, 1x1x3mm3), and 3D T1-MPRAGE (TR=3000ms, TE=3.5ms, TI=926, 1x1x1mm3).

Data Analysis: Voxel-wise T2 distributions were calculated using a modified Extended Phase Graph algorithm combined with regularized non-negative least squares and flip angle optimization18,19. MWF was defined as the fraction of signal with T2<40ms and GMT2 of the intra/extracellular water pool was calculated for T2s between 40 and 200ms. T1 was fit to a single exponential using in-house software. DBSI data was analysed to calculate diffusivities, fibre fraction, hindered isotropic diffusion fraction and restricted isotropic diffusion fraction maps7. WC was calculated using the reference method20. MWF, GMT2, T1, DBSI-derived metrics and 3DT1 images were registered to PD images using FLIRT (FSL toolbox)21. NAWM masks were created using FAST22 on the registered 3DT1 and overlaid onto registered MWF, GMT2, T1, WC and DBSI-derived maps to obtain mean measurements. Comparisons were done using an unpaired t-test.

Results

Results are shown in Table 2 and Figure 1. WC was higher in SPMS compared to CIS (p=0.04). GMT2 was increased in SPMS (p=0.02) and PPMS (p=0.005) compared to CIS. Fibre fraction was lower in RRMS and SPMS than CIS (p=0.01, p=0.02). Hindered fraction was larger and restricted fraction was lower in SPMS than CIS (p=0.03, p=0.003). MWF, T1 and axial and radial diffusivity showed no significant difference between subtypes. Fibre fraction was negatively correlated with age (r=0.31, p=0.02) and GMT2 was correlated with EDSS (r=0.48, p=0.0002) (Figure 2).

Conclusion

As expected, progressive stages of MS showed greater abnormalities in the MR measures than RRMS and CIS. Histologically, progressive MS shows fewer axons23, which, in vivo, is demonstrated by a smaller fibre fraction, and an increase in water content and hindered fraction due to axonal volume loss being replaced by water. Inflammation is also known to be less in SPMS supported by our lower restricted fraction. Advanced imaging can show differences between MS subtypes related to the underlying tissue damage.

Acknowledgements

We would like to thank the MS volunteers and their families as well as the technologists at our centre. This study was sponsored by the Multiple Sclerosis Society of Canada. CG is the recipient of an endMS Master's Studentship funded by the MS Society of Canada.

References

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Figures

Table 1: Participant Demographics. Mean (Range) are listed (median for EDSS).

Table 2: Mean (standard error) for the MR measures averaged over the normal appearing white matter from different MS subtypes: clinically isolated syndrome (CIS), relapsing-remitting multiple sclerosis (RRMS), secondary progressive multiple sclerosis (SPMS) and primary progressive multiple sclerosis (PPMS).

Figure 1: Plots of the mean MR metric over the normal appearing white matter for each participant divided into their MS subtypes. Black lines between datasets show significant differences (p<0.05).

Figure 2: Correlation between (A) Fibre fraction and age and (B) GMT2 and EDSS for the different MS subtypes. Each point represents the average over the normal appearing white matter for a subject. Fibre fraction was negatively correlated with age (r=0.31, p=0.02) and GMT2 was correlated with EDSS (r=0.48, p=0.0002).

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