Dataset Information

Motor Imagery as a Function of Disease Severity in Multiple Sclerosis: An fMRI Study.

ABSTRACT: Motor imagery (MI) is defined as mental execution without any actual movement. While healthy adults usually show temporal equivalence, i.e., isochrony, between the mental simulation of an action and its actual performance, neurological disorders are associated with anisochrony. Unlike in patients with stroke and Parkinson disease, only a few studies have investigated differences of MI ability in multiple sclerosis (MS). However, the relationship among disease severity, anisochrony and brain activation patterns during MI has not been investigated yet. Here, we propose to investigate MI in MS patients using fMRI during a behavioral task executed with dominant/non-dominant hand and to evaluate whether anisochrony is associated with disease severity. Thirty-seven right-handed MS patients, 17 with clinically isolated syndrome (CIS) suggestive of MS and 20 with relapsing-remitting MS (RR-MS) and 20 right-handed healthy controls (HC) underwent fMRI during a motor task consisting in the actual or imaged movement of squeezing a foam ball with the dominant and non-dominant hand. The same tasks were performed outside the MRI room to record the number of actual and imagined ball squeezes, and calculate an Index of performance (IP) based on the ratio between actual and imagined movements. IP showed that a progressive loss of ability in simulating actions (i.e., anisochrony) more pronounced for non-dominant hand, was found as function of the disease course. Moreover, anisochrony was associated with activation of occipito-parieto-frontal areas that were more extensive at the early stages of the disease, probably in order to counteract the changes due to MS. However, the neural engagement of compensatory brain areas becomes more difficult with more challenging tasks, i.e., dominant vs. non-dominant hand, with a consequent deficit in behavioral performance. These results show a strict association between MI performance and disease severity, suggesting that, at early stages of the disease, anisochrony in MI could be considered as surrogate behavioral marker of MS severity.

SUBMITTER: Tacchino A

PROVIDER: S-EPMC5768615 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Motor Imagery as a Function of Disease Severity in Multiple Sclerosis: An fMRI Study.

Tacchino Andrea A Saiote Catarina C Brichetto Giampaolo G Bommarito Giulia G Roccatagliata Luca L Cordano Christian C Battaglia Mario A MA Mancardi Gian L GL Inglese Matilde M

Frontiers in human neuroscience 20180111

Motor imagery (MI) is defined as mental execution without any actual movement. While healthy adults usually show temporal equivalence, i.e., isochrony, between the mental simulation of an action and its actual performance, neurological disorders are associated with anisochrony. Unlike in patients with stroke and Parkinson disease, only a few studies have investigated differences of MI ability in multiple sclerosis (MS). However, the relationship among disease severity, anisochrony and brain acti ...[more]

PMID: 29375340

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Project description:Background:Motor imagery (MI) is increasingly used in neurorehabilitation to facilitate motor performance. Our previous study results demonstrated significantly improved walking after rhythmic-cued MI in people with multiple sclerosis (pwMS). The present feasibility study was aimed to obtain preliminary information of changes in walking, fatigue, quality of life (QoL) and MI ability following cued and non-cued MI in pwMS. The study further investigated the feasibility of a larger study and examined the reliability of a two-dimensional gait analysis system. Methods:At the MS-Clinic, Department of Neurology, Medical University of Innsbruck, Austria, 15 adult pwMS (1.5-4.5 on the Expanded Disability Status Scale, 13 females) were randomised to one of three groups: 24 sessions of 17 min of MI with music and verbal cueing (MVMI), with music alone (MMI), or non-cued (MI). Descriptive statistics were reported for all outcomes. Primary outcomes were walking speed (Timed 25-Foot Walk) and walking distance (6-Minute Walk Test). Secondary outcomes were recruitment rate, retention, adherence, acceptability, adverse events, MI ability (Kinaesthetic and Visual Imagery Questionnaire, Time-Dependent MI test), fatigue (Modified Fatigue Impact Scale) and QoL (Multiple Sclerosis Impact Scale-29). The reliability of a gait analysis system used to assess gait synchronisation with music beat was tested. Results:Participants showed adequate MI abilities. Post-intervention, improvements in walking speed, walking distance, fatigue, QoL and MI ability were observed in all groups. Success of the feasibility criteria was demonstrated by recruitment and retention rates of 8.6% (95% confidence interval, CI 5.2, 13.8%) and 100% (95% CI 76.4, 100%), which exceeded the target rates of 5.7% and 80%. Additionally, the 83% (95% CI 0.42, 0.99) adherence rate surpassed the 67% target rate. Intra-rater reliability analysis of the gait measurement instruments demonstrated excellent Intra-Class Correlation coefficients for step length of 0.978 (95% CI 0.973, 0.982) and step time of 0.880 (95% CI 0.855, 0.902). Conclusion:Results from our study suggest that cued and non-cued MI are valuable interventions in pwMS who were able to imagine movements. A larger study appears feasible, however, substantial improvements to the methods are required such as stratified randomisation using a computer-generated sequence and blinding of the assessors. Trial registration:ISRCTN ISRCTN92351899. Registered 10 December 2015.

Project description:ObjectiveTo optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of principle, we showcased how to leverage routinely collected EHR data to identify patients with a complex neurological disorder and derive an important surrogate measure of disease severity heretofore only available in research settings.MethodsIn a cross-sectional observational study, 5,495 MS patients were identified from the EHR systems of two major referral hospitals using an algorithm that includes codified and narrative information extracted using natural language processing. In the subset of patients who receive neurological care at a MS Center where disease measures have been collected, we used routinely collected EHR data to extract two aggregate indicators of MS severity of clinical relevance multiple sclerosis severity score (MSSS) and brain parenchymal fraction (BPF, a measure of whole brain volume).ResultsThe EHR algorithm that identifies MS patients has an area under the curve of 0.958, 83% sensitivity, 92% positive predictive value, and 89% negative predictive value when a 95% specificity threshold is used. The correlation between EHR-derived and true MSSS has a mean R(2) = 0.38±0.05, and that between EHR-derived and true BPF has a mean R(2) = 0.22±0.08. To illustrate its clinical relevance, derived MSSS captures the expected difference in disease severity between relapsing-remitting and progressive MS patients after adjusting for sex, age of symptom onset and disease duration (p = 1.56×10(-12)).ConclusionIncorporation of sophisticated codified and narrative EHR data accurately identifies MS patients and provides estimation of a well-accepted indicator of MS severity that is widely used in research settings but not part of the routine medical records. Similar approaches could be applied to other complex neurological disorders.

Dataset Information

Motor Imagery as a Function of Disease Severity in Multiple Sclerosis: An fMRI Study.

Publications

Motor Imagery as a Function of Disease Severity in Multiple Sclerosis: An fMRI Study.

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