Evidence of early microstructural white matter abnormalities in multiple sclerosis from multi-shell diffusion MRI

Abstract

Irreversible white matter (WM) damage, including severe demyelination and axonal loss, is a main determinant of long-term disability in multiple sclerosis (MS). Non-invasive detection of changes in microstructural WM integrity in the disease is challenging since commonly used imaging metrics lack the necessary sensitivity, especially in the early phase of the disease. This study aims at assessing microstructural WM abnormalities in early-stage MS by using ultra-high gradient strength multi-shell diffusion MRI and the restricted signal fraction (FR) from the Composite Hindered and Restricted Model of Diffusion (CHARMED), a metric sensitive to the volume fraction of axons. In 22 early MS subjects (disease duration ≤5 years) and 15 age-matched healthy controls, restricted fraction estimates were obtained through the CHARMED model along with conventional Diffusion Tensor Imaging (DTI) metrics. All imaging parameters were compared cross-sectionally between the MS subjects and controls both in WM lesions and normal-appearing white matter (NAWM). We found a significant reduction in FR focally in WM lesions and widespread in the NAWM in MS patients relative to controls (corrected p < .05). Signal fraction changes in NAWM were not driven by perilesional tissue, nor were they influenced by proximity to the ventricles, challenging the hypothesis of an outside-in pathological process driven by CSF-mediated immune cytotoxic factors. No significant differences were found in conventional DTI parameters. In a cross-validated classification task, FR showed the largest effect size and outperformed all other diffusion imaging metrics in discerning lesions from contralateral NAWM. Taken together, our data provide evidence for the presence of widespread microstructural changes in the NAWM in early MS stages that are, at least in part, unrelated to focal demyelinating lesions. Interestingly, these pathological changes were not yet detectable by conventional diffusion imaging at this early disease stage, highlighting the sensitivity and value of multi-shell diffusion imaging for better characterizing axonal microstructure in MS.

Keywords: Axonal pathology; Multi-shell diffusion MRI; Multiple sclerosis; Normal-appearing white matter.

Fig. 1

Hindered and restricted signal in the CHARMED model.

Fig. 2

CHARMED-FR reductions in multiple sclerosis normal appearing white matter. Regions (highlighted in blue) in which TBSS found significantly lower FR in multiple sclerosis NAWM compared to healthy controls. Abbreviations: FR = restricted fraction; NAWM = normal-appearing white matter. The skeleton generated by TBSS analysis is highlighted in green

Fig. 3

CHARMED-FR reductions in multiple sclerosis normal appearing white matter excluding perilesional tissue. Example of the lesion mask expansion by one and two voxels (panel A). Right: Results (highlighted in blue) in which TBSS found a significant reduction of the FR in multiple sclerosis NAWM compared to healthy controls for the original lesion masks (panel B), for the masks expanded by one voxel (panel C, volumetric overlap of regions with significant differences as compared to analysis b: 98%), and for the masks expanded by two voxels (panel D, volumetric overlap of regions with significant differences as compared to analysis b: 96%), are shown. Abbreviations: FR = restricted fraction; NAWM = normal-appearing white matter; TBSS = Tract Based Spatial Statistics.

Fig. 4

Restricted fraction in periventricular area. Example of the ventricle mask as well as surrounding concentric periventricular masks (overlaid on fractional anisotropy map) at perpendicular distances from the ventricles ranging from 1 to 6 voxels (panel a). Panel b shows box[HYPHEN]whisker plots of restricted fraction values in each layer (distance from ventricles: from 2 to 6 voxels; the first layer was excluded in order to minimize cerebrospinal fluid contamination). Boxes represent quartiles, whiskers represent extremes, crosses represent outliers. Repeated measures analysis of variance found an effect of both group (p<0.001) and distance (p<0.001), but not of group*distance interaction (p=0.78).

Fig. 5

Asymmetry index in MS vs NAWM. Box-whisker plots depicting the asymmetry index NIA between MS lesions and contralateral NAWM (1: maximum asymmetry towards the lesion, −1: maximum asymmetry towards contralateral NAWM or healthy controls) across patients. Red: positive NIA (** = p < .01, Bonferroni corrected). Blue: negative NIA (** = p < .01, Bonferroni corrected). Boxes represent quartiles, whiskers represent extremes, dots represent outliers. Abbreviations: FR = restricted fraction; NAWM = normal-appearing white matter; NIA = normalized index of asymmetry

Fig. 6

Receiver operating characteristic curves. ROC curves for the performance of parameters FA, MD, AD, RD and FR in discriminating lesions from contralateral NAWM. Dashed black line indicates no predictive power above chance discrimination. Abbreviations: ROC = receiver operating characteristic; AD = axial diffusivity; FA = fractional anisotropy; FR = restricted fraction; MD = mean diffusivity; NAWM = normal-appearing white matter; RD = radial diffusivity

Fig. 7

Average coefficient of variation for diffusion metrics. The averaged CoV, calculated on the WM skeleton, and the corresponding standard deviation are shown as percentage for the diffusion metrics FA, MD, AD, RD and FR. Abbreviations: CoV = coefficient of variation; FA = fractional anisotropy; MD = mean diffusivity; AD = axial diffusivity; RD = radial diffusivity; FR = restricted fraction; WM = white matter