Secondary Progressive and Relapsing Remitting Multiple Sclerosis Leads to Motor-Related Decreased Anatomical Connectivity

Abstract

Multiple sclerosis (MS) damages central white matter pathways which has considerable impact on disease-related disability. To identify disease-related alterations in anatomical connectivity, 34 patients (19 with relapsing remitting MS (RR-MS), 15 with secondary progressive MS (SP-MS) and 20 healthy subjects underwent diffusion magnetic resonance imaging (dMRI) of the brain. Based on the dMRI, anatomical connectivity mapping (ACM) yielded a voxel-based metric reflecting the connectivity shared between each individual voxel and all other brain voxels. To avoid biases caused by inter-individual brain-shape differences, they were estimated in a spatially normalized space. Voxel-based statistical analyses using ACM were compared with analyses based on the localized microstructural indices of fractional anisotropy (FA). In both RR-MS and SP-MS patients, considerable portions of the motor-related white matter revealed decreases in ACM and FA when compared with healthy subjects. Patients with SP-MS exhibited reduced ACM values relative to RR-MS in the motor-related tracts, whereas there were no consistent decreases in FA between SP-MS and RR-MS patients. Regional ACM statistics exhibited moderate correlation with clinical disability as reflected by the expanded disability status scale (EDSS). The correlation between these statistics and EDSS was either similar to or stronger than the correlation between FA statistics and the EDSS. Together, the results reveal an improved relationship between ACM, the clinical phenotype, and impairment. This highlights the potential of the ACM connectivity indices to be used as a marker which can identify disease related-alterations due to MS which may not be seen using localized microstructural indices.

Cortical sources of resting state electroencephalographic rhythms differ in relapsing–remitting and secondary progressive multiple sclerosis

“…Keeping in mind these data, the present results show that individually-determined delta cortical sources were more abnormally lower in amplitude in the SP than in the RR sub-group. These EEG results complement recent neuroimaging findings mapping a reduced anatomical connectivity in motor-related brain tracts in a sub-group of SP compared to a sub-group of RR patients (Lyksborg et al, 2014). Also, fMRI evidence showed extensive sub-cortical and cortical atrophy in MS patients (especially in frontal and temporal regions) with a distinction between the RR and the SP sub-group; namely, abnormality in white matter tracts statistically explained both sub-cortical and cortical atrophy in RR patients, while SP patients showed only abnormality in sub-cortical atrophy (Steenwijk et al, 2015).…”

“…On one hand, structural and functional MRI studies showed vascular lesions and abnormal BOLD activity in MS patients compared to healthy control (HC) subjects, as a function of disease onset and cognitive impairment (Swirsky-Sacchetti et al, 1992;Arnett et al, 1994;Morgen et al, 2006;Calabrese et al, 2010). Other MRI evidence unveiled differences between RR and SP sub-groups of MS patients by anatomical connectivity mapping (Lyksborg et al, 2014). Furthermore, there were differences as revealed by functional connectivity mapping in sensory-motor network (SMN) and default-mode network (DMN) in MS patients compared to HC subjects (Basile et al, 2013).…”

Disability in progressive MS is associated with T2 lesion changes

“…To assess a more sensitive and discriminative measure of localized tissue pathology and relation to specific functional disability, tract-based analyses with anatomical connectivity mapping would be preferable, but we found it to be beyond the scope of the present study to perform these analyses (30).…”

Quantification of voxel-wise total fibre density: Investigating the problems associated with track-count mapping

“…Similarly, anatomical connectivity mapping (Bozzali et al, 2011) and fibre density mapping (Stadlbauer et al, 2010) are two techniques that are essentially similar to TDI at native resolution (i.e. without super-resolution; Calamante et al, 2011), and have been used quantitatively in numerous applications; these include to investigate Alzheimer's disease (Bozzali et al, 2013a(Bozzali et al, , 2011, multiple sclerosis (Bozzali et al, 2013b;Lyksborg et al, 2014), gliomas (Stadlbauer et al, 2012(Stadlbauer et al, , 2011(Stadlbauer et al, , 2010, and age-related brain changes (Stadlbauer et al, 2012). Therefore, although TDI maps were not initially intended as quantitative maps, there is interest in using such an approach to attempt to provide useful quantitative information.…”