Rapid Myelin Water Imaging in Human Cervical Spinal Cord
Emil Ljungberg1, Irene Vavasour2, Roger Tam2,3, Youngjin Yoo3, Alexander Rauscher4, David Li2, Anthony Traboulsee5, Alex MacKay1,2, and Shannon Kolind5

1Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada, 2Radiology, University of British Columbia, Vancouver, BC, Canada, 3Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada, 4Pediatrics, University of British Columbia, Vancouver, BC, Canada, 5Medicine, University of British Columbia, Vancouver, BC, Canada

Synopsis

Myelin water imaging can quantify myelin in the cervical cord in vivo. However, the established 3D Turbo Spin Echo (TSE) approach has a lengthy scan time. We used a 3D Gradient Spin Echo (GRASE) sequence to speed up cervical cord myelin water acquisition by a factor of three. Average GRASE and TSE myelin water estimates were similar (GRASE: 23±1.5%; TSE: 24±3%) and significantly correlated (R2=0.69, p<0.001). 3D-GRASE showed good reproducibility with an average myelin water coefficient of variation of 6%. Our findings demonstrate that cervical cord myelin water data can reliably be collected in clinical feasible scan times.

Introduction

Myelin Water Imaging (MWI) is a quantitative T2 relaxation-based magnetic resonance imaging technique1, which has been validated as a viable biomarker for myelin in the central nervous system (CNS)2. The MR signal from tissue in the CNS originates from three main water pools: water trapped between myelin bilayers (T2≈20ms), intra/extra-cellular water (T2≈80ms) and cerebrospinal fluid (T2≈2s). The signal fraction originating from each water pool is determined by analysing the T2-decay curve using a non-negative least squares (NNLS) fitting-algorithm1. From this analysis the myelin water fraction (MWF) is obtained as the ratio of the signal originating from water within the myelin bilayers to the total MR signal.

The acquisition time for MWI has improved significantly over the last 20 years, most recently with the implementation of a 3D Gradient Spin Echo (3D-GRASE) sequence enabling full cerebral coverage in 15min3. However, multi-slice MWI in spinal cord (SC) has thus far only employed a 3D Turbo Spin Echo (3D-TSE) sequence with a significantly longer acquisition time4. The purpose of this study was to investigate the reliability of using a high resolution 3D-GRASE sequence for MWI in cervical spinal cord in vivo to speed up data acquisition by a factor of three.

Method

MR Experiments: Seven healthy volunteers underwent imaging on a Philips Achieva 3T scanner using a 6-channel spine coil. Scans were centered at the C2/C3 disc and aligned perpendicular to the cord. The scanning protocol included:

(1) 3D-GRASE (32 echoes, echo spacing 10ms, TEmin=10ms, TEmax=320ms, TR=1500ms, refocusing flip angle αrefocus=180°, acquired resolution=1x1x5mm3, FOV=180x40x150mm3 (AP, FH, RL), reconstructed resolution=0.625x0.625x2.5mm3, SENSE factor 2 Right-Left, scan time=8.6min)

(2) 3D-TSE (all parameters matched to 3D-GRASE except for αrefocus=135°, FOV=180x40x135mm3, no SENSE, and reconstructed resolution=0.7x0.7x5mm3, scan time=23.3min)

(3) T2 weighted multi-echo fast gradient echo (mFFE) (5 echoes, echo spacing 8.2ms, TEmin=6.6ms, TEmax=39.4ms, TR=814ms, acquired resolution=0.8x0.8x2.75mm3, FOV=150x43.75x150mm3, reconstructed resolution=0.3x0.3x2.75mm3, for anatomical segmentation).

To assess reproducibility, the 3D-GRASE sequence was collected twice, at the beginning and end of the scanning protocol.

Image Analysis: Voxel-wise MWF maps were calculated by analyzing the 3D-GRASE and 3D-TSE T2-decay data using in-house software, with corrections for stimulated echo artifacts as well as regularizing the data in both spatial and T2 space5. Regions of interest (ROIs) were obtained by registering the mFFE scan to the MNI-POLY-AMU spinal cord template from the Spinal Cord Toolbox6 and then registering the 3D-GRASE and 3D-TSE scans to the mFFE. Four ROIs from the template (full cord, gray matter (GM), the dorsal column (DC), and the lateral corticospinal tract (LCT)) were registered to mFFE space and MWF within each ROI was determined (Figure 1).

Statistical Analysis: MWF estimates obtain by 3D-GRASE and 3D-TSE were compared using linear regression and Bland-Altman analysis. Reproducibility of the 3D-GRASE sequence was evaluated by calculating the coefficient of variation (COV) in MWF between the two 3D-GRASE experiments.

Results

One subject was excluded from the results due to severe motion artifacts rendering ROI registration unreliable. 3D-GRASE and 3D-TSE MWF maps were qualitatively similar (Figure 2) and linear regression demonstrated a strong positive correlation between 3D-GRASE and 3D-TSE MWF (Figure 3, R2=0.69, p<0.001). A Bland-Altman plot showed no biases for the various ROIs (Figure 4). Average whole cord segment MWF was 23% (SD=1.5%) for 3D-GRASE and 24% (SD=3%) for 3D-TSE. 3D-GRASE showed good scan-rescan reproducibility with average COV’s ranging from 6.2% in whole cord to 12.8% in GM (Table 1).

Discussion

The MWF results obtained in this study are in agreement with previous studies investigating cervical spinal cord MWF with values between 21.8-26.4%7.Bland-Altman analysis (Figure 4) of 3D-GRASE and 3D-TSE showed that the 95% confidence intervals for the mean difference overlaps zero, indicating there is no significant difference between the 3D-GRASE and 3D-TSE results. Regression analysis (Figure 3) also shows that the unity line, i.e. the one-to-one correlation, falls within the 95% confidence interval of the linear fit, further supporting the hypothesis that these techniques produce comparable results.

Conclusions

Our study is the first successful implementation of a 3D-GRASE sequence for human cervical spinal cord MWI in vivo. 3D-GRASE MWF is reproducible and in good agreement with MWF values reported in previous studies. Using 3D-GRASE for MWI significantly reduces the acquisition time compared to the matched 3D-TSE sequence. Our findings demonstrate that cervical cord myelin water data can reliably be collected in clinically feasible scan times.

Acknowledgements

No acknowledgement found.

References

1. MacKay et al., In vivo visualization of myelin water in brain by magnetic resonance. MRM 1994;31(6):673-677.

2. Laule et al., Myelin water imaging in multiple sclerosis: quantitative correlations with histopathology. MS 2006;12(6):747-753.

3. Prasloski T, Rauscher A, MacKay AL, et al. Rapid whole cerebrum myelin water imaging using a 3D GRASE sequence. NeuroImage 2012;63:533-539.

4. MacMillan et al., Myelin water and T2 relaxation measurements in the healthy cervical spinal cord at 3.0T: Repeatability and changes with age. NeuroImage 2011;54(2):1083-1090.

5. Yoo et al., Non-Local Spatial Regularization of MRI T2 Relaxation Images for Myelin Water Quantification. MICCAI 2013;LNCS 8149:614-621.

6. Cohen-Adad et al., Spinal Cord Toolbox: an open-source framework for processing spinal cord MRI data. OHBM 2014:3633.

7. Minty et al., Myelin water measurements in the spinal cord. MRM 2009;61(4):883-892.

Figures

Figure 1: Overview of the image analysis pipeline using tools from the Spinal Cord Toolbox together with the ROIs used in the analysis.


Figure 2: Comparison of MWF maps from the 3D-TSE and the two 3D-GRASE scans for the same slice.

Figure 3: A significant correlation between 3D-GRASE and 3D-TSE MWF. MWFTSE = 0.89 · MWFGRASE + 0.037, (R2=0.69, p<0.001, (95% conf.interval slope [0.57, 1.2], y-int [-0.04, 0.11])

Figure 4: Bland-Altman plot comparing 3D-TSE and 3D-GRASE MWF.

Table 1: COVs of scan-rescan reproducibility for 3D-GRASE MWF.



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