Objectives

Investigating the potential of myelin repair strategies in multiple sclerosis (MS) requires an understanding of myelin dynamics during lesion evolution. The objective of this study is to longitudinally measure myelin water fraction (MWF), an MRI biomarker of myelin, in new MS lesions and to identify factors that influence their subsequent myelin content.

Methods

Twenty-three MS patients were scanned with whole-brain Fast Acquisition with Spiral Trajectory and T2prep (FAST-T2) MWF mapping at baseline and median follow-up of 6 months. Eleven healthy controls (HC) confirmed the reproducibility of FAST-T2 in white matter regions of interests (ROIs) similar to a lesion size. A random-effect-model was implemented to determine the association between baseline clinical and lesion variables and the subsequent MWF.

Results

ROI-based measurements in HCs were highly correlated between scans [mean r = 0.893 (.764-.967)]. In MS patients, 38 gadolinium enhancing (Gd+) and 25 new non-enhancing (Gd-) T2 hyperintense lesions (5.7 months, ±3.8) were identified. Significant improvement in MWF was seen in Gd+ lesions (0.035 ± 0.029, p < 0.001) as compared to Gd- lesions (0.006 ± 0.017, p = 0.065). In the model, a higher baseline MWF (p < 0.001) and the presence of Gd (p < 0.001) were associated with higher subsequent MWF.

Conclusions

FAST T2 provides a clinically feasible method to quantify MWF in new MS lesions. The observed influence of baseline MWF, which represents a combined effect of both resolving edema and myelin change within acute lesions, suggests that the extent of initial inflammation impacts final myelin recovery.

A novel lesion-mask free method based on a gamma mixture model was applied to myelin water fraction (MWF) maps to estimate the association between cortical thickness and myelin content, and how it differs between relapsing-remitting (RRMS) and secondary-progressive multiple sclerosis (SPMS) groups (135 and 23 patients, respectively). It was compared to an approach based on lesion masks. The gamma mixture distribution of whole brain, white matter (WM) MWF was characterized with three variables: the mode (most frequent value) m₁ of the gamma component shown to relate to lesion, the mode m₂ of the component shown to be associated with normal appearing (NA) WM, and the mixing ratio (λ) between the two distributions. The lesion-mask approach relied on the mean MWF within lesion and within NAWM. A multivariate regression analysis was carried out to find the best predictors of cortical thickness for each group and for each approach. The gamma-mixture method was shown to outperform the lesion-mask approach in terms of adjusted R², both for the RRMS and SPMS groups. The predictors of the final gamma-mixture models were found to be m₁ (β = 1.56, p < 0.005), λ (β = -0.30, p < 0.0005) and age (β = -0.0031, p < 0.005) for the RRMS group (adjusted R² = 0.16), and m₂ (β = 4.72, p < 0.0005) for the SPMS group (adjusted R² = 0.45). Further, a DICE coefficient analysis demonstrated that the lesion mask had more overlap to an ROI associated with m₁, than to an ROI associated with m₂ (p < 0.00001), and vice versa for the NAWM mask (p < 0.00001). These results suggest that during the relapsing phase, focal WM damage is associated with cortical thinning, yet in SPMS patients, global WM deterioration has a much stronger influence on secondary degeneration. Through these findings, we demonstrate the potential contribution of myelin loss on neuronal degeneration at different disease stages and the usefulness of our statistical reduction technique which is not affected by the typical bias associated with approaches based on lesion masks.