Prognostic value of spinal cord lesion measures in early relapsing-remitting multiple sclerosis.

BACKGROUND: Spinal cord (SC) lesions have been associated with unfavourable clinical outcomes in multiple sclerosis (MS). However, the relation of whole SC lesion number (SCLN) and volume (SCLV) to the future occurrence and type of confirmed disability accumulation (CDA) remains largely unexplored. METHODS: In this monocentric retrospective study, SC lesions were manually delineated. Inclusion criteria were: age between 18 and 60 years, relapsing-remitting MS, disease duration under 2 years and clinical follow-up of 5 years. The first CDA event after baseline, determined by a sustained increase in the Expanded Disability Status Scale over 6 months, was classified as either progression independent of relapse activity (PIRA) or relapse-associated worsening (RAW). SCLN and SCLV were compared between different (sub)groups to assess their prospective value. RESULTS: 204 patients were included, 148 of which had at least one SC lesion and 59 experienced CDA. Patients without any SC lesions experienced significantly less CDA (OR 5.8, 95% CI 2.1 to 19.8). SCLN and SCLV were closely correlated (rs=0.91, p<0.001) and were both significantly associated with CDA on follow-up (p<0.001). Subgroup analyses confirmed this association for patients with PIRA on CDA (34 events, p<0.001 for both SC lesion measures) but not for RAW (25 events, p=0.077 and p=0.22). CONCLUSION: Patients without any SC lesions are notably less likely to experience CDA. Both the number and volume of SC lesions on MRI are associated with future accumulation of disability largely independent of relapses.

Cognitive impairment in early MS: contribution of white matter lesions, deep grey matter atrophy, and cortical atrophy.

BACKGROUND: Cognitive impairment (CI) is a frequent and debilitating symptom in MS. To better understand the neural bases of CI in MS, this magnetic resonance imaging (MRI) study aimed to identify and quantify related structural brain changes and to investigate their relation to each other. METHODS: We studied 51 patients with CI and 391 patients with cognitive preservation (CP). We analyzed three-dimensional T1-weighted and FLAIR scans at 3 Tesla. We determined mean cortical thickness as well as volumes of cortical grey matter (GM), deep GM including thalamus, cerebellar cortex, white matter, corpus callosum, and white matter lesions (WML). We also analyzed GM across the whole brain by voxel-wise and surface-based techniques. RESULTS: Mean disease duration was 5 years. Comparing MS patients with CI and CP, we found higher volumes of WML, lower volumes of deep and cortical GM structures, and lower volumes of the corpus callosum (all corrected p values < 0.05). Effect sizes were largest for WML and thalamic volume (standardized ß values 0.25 and - 0.25). By logistic regression analysis including both WML and thalamic volume, we found a significant effect only for WML volume. Inclusion of the interaction term of WML and thalamic volume increased the model fit and revealed a highly significant interaction of WML and thalamic volume. Moreover, voxel-wise and surface-based comparisons of MS patients with CI and CP showed regional atrophy of both deep and cortical GM independent of WML volume and overall disability, but effect sizes were lower. CONCLUSION: Although several mechanisms contribute to CI already in the early stage of MS, WML seem to be the main driver with thalamic atrophy primarily intensifying this effect.

Atrophy and structural variability of the upper cervical cord in early multiple sclerosis.

BACKGROUND: Despite agreement about spinal cord atrophy in progressive forms of multiple sclerosis (MS), data on clinically isolated syndrome (CIS) and relapsing-remitting MS (RRMS) are conflicting. OBJECTIVE: To determine the onset of spinal cord atrophy in the disease course of MS. METHODS: Structural brain magnetic resonance imaging (MRI) was acquired from 267 patients with CIS (85) or RRMS (182) and 64 healthy controls (HCs). The upper cervical cord cross-sectional area (UCCA) was determined at the level of C2/C3 by a segmentation tool and adjusted for focal MS lesions. The coefficient of variation (CV) was calculated from all measurements between C2/C3 and 13 mm above as a measure of structural variability. RESULTS: Compared to HCs (76.1±6.9 mm(2)), UCCA was significantly reduced in CIS patients (73.5±5.8 mm(2), p=0.018) and RRMS patients (72.4±7.0 mm(2), p<0.001). Structural variability was higher in patients than in HCs, particularly but not exclusively in case of focal lesions (mean CV HCs/patients without/with lesions: 2.13%/2.55%/3.32%, all p-values<0.007). UCCA and CV correlated with Expanded Disability Status Scale (EDSS) scores (r =-0.131/0.192, p=0.044/<0.001) and disease duration (r=-0.134/0.300, p=0.039/< 0.001). CV additionally correlated with hand and arm function (r=0.180, p=0.014). CONCLUSION: In MS, cervical cord atrophy already occurs in CIS. In early stages, structural variability may be a more meaningful marker of spinal cord pathology than atrophy.

Spinal cord atrophy in early Huntington's disease.

Despite evidence for spinal cord involvement, it remains unclear whether spinal cord atrophy exists in early Huntington's disease. We studied magnetic resonance images, covering both brain and upper cervical cord, in two cohorts of Huntington's patients and in one cohort of Alzheimer's patients. All cohorts included healthy controls comparable with regard to age and gender. We found significant spinal cord atrophy in both cohorts of Huntington's patients but not in the cohort of Alzheimer's patients. Furthermore, spinal cord atrophy correlated with motor symptoms indicating that spinal cord atrophy occurs in the clinical stages and does not result from abnormal development.

Brain size and white matter content of cerebrospinal tracts determine the upper cervical cord area: evidence from structural brain MRI.

INTRODUCTION: Measurement of the upper cervical cord area (UCCA) from brain MRI may be an effective way to quantify spinal cord involvement in neurological disorders such as multiple sclerosis. However, knowledge on the determinants of UCCA in healthy controls (HCs) is limited. METHODS: In two cohorts of 133 and 285 HCs, we studied the influence of different demographic, body-related, and brain-related parameters on UCCA by simple and partial correlation analyses as well as by voxel-based morphometry (VBM) across both cerebral gray matter (GM) and white matter (WM). RESULTS: First, we confirmed the known but moderate effect of age on UCCA in the older cohort. Second, we studied the correlation of UCCA with sex, body height, and total intracranial volume (TIV). TIV was the only variable that correlated significantly with UCCA after correction for the other variables. Third, we studied the correlation of UCCA with brain-related parameters. Brain volume correlated stronger with UCCA than TIV. Both volumes of the brain tissue compartments GM and WM correlated with UCCA significantly. WM volume explained variance of UCCA after correction for GM volume, whilst the opposite was not observed. Correspondingly, VBM did not yield any brain region, whose GM content correlated significantly with UCCA, whilst cerebral WM content of cerebrospinal tracts strongly correlated with UCCA. This latter effect increased along a craniocaudal gradient. CONCLUSION: UCCA is mainly determined by brain volume as well as by WM content of cerebrospinal tracts.