Motor evoked potential: a reliable and objective measure to document the functional consequences of multiple sclerosis? Relation to disability and MRI.

OBJECTIVE: In an attempt to analyze whether MEP can serve as a valid measure for evaluating neurological dysfunction in multiple sclerosis (MS), we related MEP to clinical and MRI measures. METHODS: Transcranial magnetic stimulation was applied in 52 MS patients to determine the central motor conduction time (CMCT) to the extremities. We calculated Z-scores for each CMCT (Zcmct) corrected for height. All patients underwent two clinical measurements and a MRI scan, of which T1 and T2 brain lesion volumes, brain volume, spinal cord volume and the number of T2 spinal cord lesions were derived. RESULTS: The clinical measurements correlated significantly with various Zcmct (Spearman correlation coefficients ranged from 0.29 to 0.53; p<0.05). The number of spinal cord lesions, brain T1 and T2 lesion volume and spinal cord volume correlated with various Zcmct (r=0.31-0.53; p<0.05). Linear regression analysis revealed that the clinical measurements were explained by Zcmct left leg and T1 lesion volume (adjusted R(2)=0.38). For one clinical measurement the number of spinal cord lesions was also included (adjusted R(2)=0.43). CONCLUSION: We found a relation between MEP, brain and spinal cord MRI measures, and two clinical measures. Moreover, a model for explaining disability in MS revealed that MEP measures provide information in addition to MRI measures. SIGNIFICANCE: This study suggests that MEP is a measure that might adequately reflect pathology and neurological dysfunction in MS.

Can rate of brain atrophy in multiple sclerosis be explained by clinical and MRI characteristics?

INTRODUCTION: Multiple sclerosis (MS) is characterized, besides focal lesions, by brain atrophy. The determinants of atrophy rates in individual patients are poorly understood. AIM: This study investigated the predictive value of clinical and magnetic resonance imaging (MRI) factors, including short-term changes thereof, for concurrent and future atrophy evolution using Spearman's rank correlations and stepwise multiple linear regression. METHODS: We retrospectively identified a group of 115 active, early relapsing-remitting (RR) patients relatively homogeneous in terms of disease course and MRI activity compared to a second group of 96 patients with broader spectrum of MS phenotypes and inactive scans. All patients had undergone three MRI investigations with interscan intervals of at least 12 and 24 months, respectively. RESULTS: In the RR patients, 23% of variance in concurrent atrophy rates (over the first interval) could be explained by the combination of baseline T2 lesion volume and change in EDSS score over the first interval, whereas only 6% in future atrophy rates (over the second interval) was explained. In the heterogeneous group, 20.2% of the variance in future atrophy rates could be explained, but slightly less in concurrent atrophy rates (16.2%). CONCLUSION: We concluded that variance in brain atrophy rates can partially be explained by clinical and MRI measures of disease. Future atrophy rates in individual MS patients are difficult to predict even when including previous atrophy rates.