Early disturbances in multimodal evoked potentials as a prognostic factor for long-term disability in relapsing-remitting multiple sclerosis patients

Evoked potentials after autologous hematopoietic stem cell transplantation for multiple sclerosis

OBJECTIVE

To investigate the effect of autologous hematopoietic stem cell transplantation (AHSCT) on functional aspects of the nervous system assessed by visual (VEP), somatosensory (SEP), and motor (MEP) evoked potentials in patients with relapsing-remitting multiple sclerosis.

BACKGROUND

Several studies have demonstrated the efficacy of AHSCT on inflammatory activity and disability progression in patients with multiple sclerosis. However, the impact of AHSCT on evoked potentials has not been evaluated before.

METHODS

Twelve AHSCT-treated patients from Uppsala University Hospital were consecutively recruited. Evoked potentials (EP) were collected at baseline and two follow-up visits, 3 and 12 months post-AHSCT. We calculated a composite EP score for each participant and compared it between different time points.

RESULTS

The median total EP score decreased from 5 at baseline, to 2.5 at 12 months post-ASHCT (p = 0.008). A significant improvement in tibial SEP (tSEP) latencies was observed (42.7 vs 41.5 ms, p < 0.001), with a similar trend for MEP latencies 12 months post-ASHCT. No significant changes in median SEP or VEP latencies were observed.

CONCLUSIONS

Treatment with AHSCT was associated with improved transmission in some central nervous system pathways in multiple sclerosis patients.

Prognostic Role of Visual Evoked Potentials in Non-Neuritic Eyes at Multiple Sclerosis Diagnosis

Introduction: This study aimed to assess the prognostic role of visual evoked potentials (VEPs) of the non-neuritic eye at the diagnosis of multiple sclerosis (MS). Patients and methods: We enrolled 181 MS patients (62% females, mean age at diagnosis: 38 years, standard deviation: 12) at the time of the first diagnostic work-up, including VEPs. We collected P100 latency and N75-P100 amplitude of non-neuritic eyes at diagnosis, and then we calculated the mean values in 127 patients with no history of optic neuritis (ON) or considered the unaffected eye in the remaining. At last follow-up (minimum: one year), disability was evaluated according to MS Severity Score or MSSS (median: 2.44, range: 0.18-9.63). Statistical analysis included Mann-Whitney descriptive analysis, Spearman correlation for independent samples, and linear regression for significant predictors of MSSS. Results: 38/181 patients had P100 latency >115 ms, and 63/181 showed N75-P100 amplitude < 5 microV in the unaffected eyes at MS diagnosis. At last follow-up, MSSS correlated with P100 latency (rho = 0.21, p = 0.004) and N75-P100 amplitude (rho = 0.19, p = 0.009) collected at diagnosis. P100 latency (not N75-P100 amplitude) resulted in a predictor for disability over time (MSSS) in the regression model (along with age at onset, MS course, and disease-modifying treatments). Conclusions: Our study showed a prognostic value of VEPs in clinically unaffected eyes at MS diagnosis to predict future disability, independently from a history of ON.

Somatosensory evoked potentials and magnetic resonance imaging of the central nervous system in early multiple sclerosis

BACKGROUND

Somatosensory evoked potentials (SSEP) are still broadly used, although not explicitly recommended, for the diagnostic work-up of suspected multiple sclerosis (MS).

OBJECTIVE

To relate disability, SSEP, and lesions on T2-weighted magnetic resonance imaging (MRI) in patients with early MS.

METHODS

In this monocentric retrospective study, we analyzed a cohort of patients with relapsing-remitting MS or clinically isolated syndrome, with a maximum disease duration of two years, as well as with available data on the score at the expanded disability status scale (EDSS), on SSEP, on whole spinal cord (SC) MRI, and on brain MRI.

RESULTS

Complete data of 161 patients were available. Tibial nerve SSEP (tSSEP) were less frequently abnormal than SC MRI (22% vs. 68%, p < 0.001). However, higher EDSS scores were significantly associated with abnormal tSSEP (median, 2.0 vs. 1.0; p = 0.001) but not with abnormal SC MRI (i.e., at least one lesion; median, 1.5 vs. 1.5; p = 0.7). Of the 35 patients with abnormal tSSEP, 32 had lesions on SC MRI, and 2 had corresponding lesions on brain MRI.

CONCLUSION

Compared to tSSEP, SC MRI is the more sensitive diagnostic biomarker regarding SC involvement. In early MS, lesions as detectable by T2-weighted MRI are the main driver of abnormal tSSEP. However, tSSEP were more closely associated with disability, which is compatible with a potential role of tSSEP as prognostic biomarker in complementation of MRI.

Individual differences in visual evoked potential latency are associated with variance in brain tissue volume in people with multiple sclerosis: An analysis of brain function-structure correlates

Visual evoked potentials (VEP) index visual pathway functioning, and are often used for clinical assessment and as outcome measures in people with multiple sclerosis (PwMS). VEPs may also reflect broader neural disturbances that extend beyond the visual system, but this possibility requires further investigation. In the present study, we examined the hypothesis that delayed latency of the P100 component of the VEP would be associated with broader structural changes in the brain in PwMS. We obtained VEP latency for a standard pattern-reversal checkerboard stimulus paradigm, in addition to Magnetic Resonance Imaging (MRI) measures of whole brain volume (WBV), gray matter volume (GMV), white matter volume (WMV), and T2-weighted fluid attenuated inversion recovery (FLAIR) white matter lesion volume (FLV). Correlation analyses indicated that prolonged VEP latency was significantly associated with lower WBV, GMV, and WMV, and greater FLV. VEP latency remained significantly associated with WBV, GMV, and WMV even after controlling for the variance associated with inter-ocular latency, age, time between VEP and MRI assessments, and other MRI variables. VEP latency delays were most pronounced in PwMS that exhibited low volume in both white and gray matter simultaneously. Furthermore, PwMS that had delayed VEP latency based on a clinically relevant cutoff (VEP latency ≥ 113 ms) in both eyes had lower WBV, GMV, and WMV and greater FLV in comparison to PwMS that had normal VEP latency in one or both eyes. The findings suggest that PwMS that have delayed latency in both eyes may be particularly at risk for exhibiting greater brain atrophy and lesion volume. These analyses also indicate that VEP latency may index combined gray matter and white matter disturbances, and therefore broader network connectivity and efficiency. VEP latency may therefore provide a surrogate marker of broader structural disturbances in the brain in MS.

Motor evoked potentials for multiple sclerosis, a multiyear follow-up dataset

Multiple sclerosis (MS) is a chronic disease affecting millions of people worldwide. Through the demyelinating and axonal pathology of MS, the signal conduction in the central nervous system is affected. Evoked potential measurements allow clinicians to monitor this process and can be used for decision support. We share a dataset that contains motor evoked potential (MEP) measurements, in which the brain is stimulated and the resulting signal is measured in the hands and feet. This results in time series of 100 milliseconds long. Typically, both hands and feet are measured in one hospital visit. The dataset contains 5586 visits of 963 patients, performed in day-to-day clinical care over a period of 6 years. The dataset consists of approximately 100,000 MEP. Clinical metadata such as the expanded disability status scale, sex, and age is also available. This dataset can be used to explore the role of evoked potentials in MS research and patient care. It may also be used as a benchmark for time series analysis and predictive modelling.

Measurement(s)	Abnormal upper-limb motor evoked potentials • Abnormal lower-limb motor evoked potentials • Kurtzke Expanded Disability Status Scale Clinical Classification
Technology Type(s)	Transcranial Magnetic Stimulation • performing a clinical assessment
Factor Type(s)	Date of birth • Sex • Measurement date
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Location	Belgium

Evozierte Potenziale – Reminder und Update

Mit Hilfe der evozierten Potenziale und der magnetisch evozierten motorischen Potenziale können verlängerte Latenzen zentraler Leitungsbahnen und peripherer Nerven nachgewiesen oder ausgeschlossen werden. Somit können Symptome objektiviert und quantifiziert sowie Läsionen lokalisiert werden. In diesem Beitrag werden Durchführung und Indikationen der einzelnen Modalitäten zusammengefasst und Neuerungen berichtet.

Multimodal Evoked Potentials as Candidate Prognostic and Response Biomarkers in Clinical Trials of Multiple Sclerosis

SUMMARY

Evoked potentials (EPs) measure quantitatively and objectively the alterations of central signal propagation in multiple sclerosis and have long been used for diagnosis. More recently, their utility for prognosis has been demonstrated in several studies, summarizing multiple EP modalities in a single score. In particular, visual, somatosensory, and motor EPs are useful because of their sensitivity to pathology in the frequently affected optic nerve, somatosensory tract, and pyramidal system. Quantitative EP scores show higher sensitivity to change than clinical assessment and may be used to monitor disease progression. Visual EP and the visual system have served as a model to study remyelinating therapies in the setting of acute and chronic optic neuritis. This review presents rationale and evidence for using multimodal EP as prognostic and response biomarkers in clinical trials, targeting remyelination or halting disease progression in multiple sclerosis.

The Use of Motor-Evoked Potentials in Clinical Trials in Multiple Sclerosis

SUMMARY

Motor-evoked potentials (MEPs) can be used to assess the integrity of the descending corticospinal tract in the laboratory. Evoked potentials (EPs) have been widely used in the past for the diagnosis of multiple sclerosis (MS), but they are now becoming more useful in assessing the prognosis of the disease. Motor-evoked potentials have been included in EP scales that have demonstrated good correlations with clinical disability. Soon after the onset of MS, it is possible to detect an ongoing process of neurodegeneration and axonal loss. Axonal loss is probably responsible for the disability and disease progression that occurs in MS. Given the good correlations of EPs in detecting disease progression in MS, they have been used to monitor the effects of drugs used to treat the disease. Several clinical trials used MEPs as part of their EP evaluation, but MEPs have never been used as a measure of efficacy in clinical trials testing neuroprotective agents, although MEPs could be a very promising tool to measure neuroprotection and remyelination resulting from these drugs. To be used in multicenter clinical trials, MEP readings should be comparable between centers. Standardized multicenter EP assessment with central reading has been demonstrated to be feasible and reliable. Although MEP measurements have been correlated with clinical scores and other measures of neurodegeneration, further validation of MEP amplitude measurements is needed regarding their validity, reliability, and sensitivity before they can be routinely used in clinical drug trials in MS.

Cognitive Event-Related Potentials-The P300 Wave Is a Prognostic Factor of Long-Term Disability Progression in Patients With Multiple Sclerosis

PURPOSE

Multiple sclerosis (MS) is a chronic disorder with a variable course. The aim of our study was to find out whether cognitive event-related potentials are prognostic for patient disability at the 15-year follow-up.

METHODS

In the observed cohort of patients with MS, we examined the event-related potentials at baseline (2003). Functional status (Expanded Disability Status Scale score) was then assessed 15 years later, and the prognostic model was developed using binary logistic regression analysis. The independent variables included demographic (age, sex, and education), clinical (disability in 2003), radiologic (MRI lesion load), and event-related potentials parameters. The prognostic accuracy of the proposed model was evaluated by calculating the area under the receiver-operating characteristics curve.

RESULTS

The study sample consisted of 85 patients with MS. The mean age was 35.5 (SD, 11.2) years, and the median disability score was 3.0 (1-7) in 2003 and 5.0 (1.5-9.5) in 2018. The significant prognostic factors of poor Expanded Disability Status Scale are higher baseline Expanded Disability Status Scale, longer MS duration, and prolonged P300 latency. The sensitivity and specificity of the cutoff at 5.0 for the disability score were 94% and 89%, respectively, with the area under the receiver-operating characteristics curve 0.94 (95% confidence interval, 0.889-0.984; P < 0.001).

CONCLUSIONS

The results show that out of event-related potentials, the P300 wave latency is a prognostic of long-term disability progression in patients with MS.

Deciphering the Morphology of Motor Evoked Potentials

Motor Evoked Potentials (MEPs) are used to monitor disability progression in multiple sclerosis (MS). Their morphology plays an important role in this process. Currently, however, there is no clear definition of what constitutes a normal or abnormal morphology. To address this, five experts independently labeled the morphology (normal or abnormal) of the same set of 1,000 MEPs. The intra- and inter-rater agreement between the experts indicates they agree on the concept of morphology, but differ in their choice of threshold between normal and abnormal morphology. We subsequently performed an automated extraction of 5,943 time series features from the MEPs to identify a valid proxy for morphology, based on the provided labels. To do this, we compared the cross-validation performances of one-dimensional logistic regression models fitted to each of the features individually. We find that the approximate entropy (ApEn) feature can accurately reproduce the majority-vote labels. The performance of this feature is evaluated on an independent test set by comparing to the majority vote of the neurologists, obtaining an AUC score of 0.92. The model slightly outperforms the average neurologist at reproducing the neurologists consensus-vote labels. We can conclude that MEP morphology can be consistently defined by pooling the interpretations from multiple neurologists and that ApEn is a valid continuous score for this. Having an objective and reproducible MEP morphological abnormality score will allow researchers to include this feature in their models, without manual annotation becoming a bottleneck. This is crucial for large-scale, multi-center datasets. An exploratory analysis on a large single-center dataset shows that ApEn is potentially clinically useful. Introducing an automated, objective, and reproducible definition of morphology could help overcome some of the barriers that are currently obstructing broad adoption of evoked potentials in daily care and patient follow-up, such as standardization of measurements between different centers, and formulating guidelines for clinical use.

Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis

Background

Evoked potentials (EPs) are a measure of the conductivity of the central nervous system. They are used to monitor disease progression of multiple sclerosis patients. Previous studies only extracted a few variables from the EPs, which are often further condensed into a single variable: the EP score. We perform a machine learning analysis of motor EP that uses the whole time series, instead of a few variables, to predict disability progression after two years. Obtaining realistic performance estimates of this task has been difficult because of small data set sizes. We recently extracted a dataset of EPs from the Rehabiliation & MS Center in Overpelt, Belgium. Our data set is large enough to obtain, for the first time, a performance estimate on an independent test set containing different patients.

Methods

We extracted a large number of time series features from the motor EPs with the highly comparative time series analysis software package. Mutual information with the target and the Boruta method are used to find features which contain information not included in the features studied in the literature. We use random forests (RF) and logistic regression (LR) classifiers to predict disability progression after two years. Statistical significance of the performance increase when adding extra features is checked.

Results

Including extra time series features in motor EPs leads to a statistically significant improvement compared to using only the known features, although the effect is limited in magnitude (ΔAUC = 0.02 for RF and ΔAUC = 0.05 for LR). RF with extra time series features obtains the best performance (AUC = 0.75±0.07 (mean and standard deviation)), which is good considering the limited number of biomarkers in the model. RF (a nonlinear classifier) outperforms LR (a linear classifier).

Conclusions

Using machine learning methods on EPs shows promising predictive performance. Using additional EP time series features beyond those already in use leads to a modest increase in performance. Larger datasets, preferably multi-center, are needed for further research. Given a large enough dataset, these models may be used to support clinicians in their decision making process regarding future treatment.

Phase-synchrony evaluation of EEG signals for Multiple Sclerosis diagnosis based on bivariate empirical mode decomposition during a visual task

BACKGROUND AND OBJECTIVE

Despite the widespread prevalence of Multiple Sclerosis (MS), the study of brain interactions is still poorly understood. Moreover, there has always been a great need to automate the MS diagnosis procedure to eliminate the evaluation errors thereby improving its consistency and reliability. To address these issues, in this work, we proposed a robust pattern recognition algorithm as a computer-aided diagnosis system. This method is based on calculating the pairwise phase-synchrony of EEG recordings during a visual task. Initially, the bivariate empirical mode decomposition (BEMD) was applied to extract the intrinsic mode functions (IMFs). The phases of these IMFs were then obtained using the Hilbert transform to be utilized in the mean phase coherence (MPC), a measure for phase-synchrony calculation. After the construction of the feature space using MPC values, the ReliefF algorithm was applied for dimension reduction. Finally, the best distinguishing features were input to a k-nearest neighbor (KNN) classifier. The results revealed a higher level of network synchronization in the posterior regions of the brain and desynchronization in the anterior regions among the MS group as compared with the normal subjects. In the validation phase, the leave-one-subject-out cross-validation (LOOCV) method was used to assess the validity of the proposed algorithm. We achieved an accuracy, sensitivity, and specificity of 93.09%, 91.07%, and 95.24% for red-green, 90.44%, 88.39%, and 92.62% for luminance, and 87.44%, 87.05%, and 87.86% for blue-yellow tasks, respectively. The experimental results demonstrated the reliability of the presented method to be generalized in the field of automated MS diagnosis systems.

Multicentre assessment of motor and sensory evoked potentials in multiple sclerosis: reliability and implications for clinical trials

Background

Motor and sensory evoked potentials (EP) are potential candidate biomarkers for clinical trials in multiple sclerosis.

Objective

To determine test -retest reliability of motor EP (MEP) and sensory EP (SEP) and associated EP-scores in patients with multiple sclerosis.

Methods

In three centres, 16 relapsing and five progressive multiple sclerosis patients had MEPs and SEPs 1-29 days apart. Five neurophysiologists independently marked latencies by central reading. By variance component analysis, we estimated the critical difference (absolute reliability) for cross-sectional group comparison, comparison of longitudinal group changes, within-subject minimal detectable change and defined within-subject improvement.

Results

Cortical SEP responses and cortico-muscular MEP latencies were more reliable than central conduction times. For comparison of 20 subjects per arm, cross-sectional group difference ranged from 0.7 to 3.9 ms and 1.1 to 1.7, group difference in longitudinal changes from 0.4 to 1.8 ms and 0.36 to 0.62, within-subject minimal detectable change from 1.2 to 5.8 ms and 1.2 to 2.0, within-subject improvement from 0.8 to 3.8ms and 0.8 to 1.3, for single EP modalities and EP scores, respectively.

Conclusions

Multicentre EP assessment with central EP reading is feasible and reliable. The critical difference is reasonably low to detect significant group changes and to define responders. The results support the concept of using EP and EP-scores as candidate response biomarkers for quantification of disease progression and for studying remyelination in multiple sclerosis.

Impairment of frequency-specific responses associated with altered electrical activity patterns in auditory thalamus following focal and general demyelination

Multiple sclerosis is characterized by intermingled episodes of de- and remyelination and the occurrence of white- and grey-matter damage. To mimic the randomly distributed pathophysiological brain lesions observed in MS, we assessed the impact of focal white and grey matter demyelination on thalamic function by directing targeted lysolecithin-induced lesions to the capsula interna (CI), the auditory cortex (A1), or the ventral medial geniculate nucleus (vMGN) in mice. Pathophysiological consequences were compared with those of cuprizone treatment at different stages of demyelination and remyelination. Combining single unit recordings and auditory stimulation in freely behaving mice revealed changes in auditory response profile and electrical activity pattern in the thalamus, depending on the region of the initial insult and the state of remyelination. Cuprizone-induced general demyelination significantly diminished vMGN neuronal activity and frequency-specific responses. Targeted lysolecithin-induced lesions directed either to A1 or to vMGN revealed a permanent impairment of frequency-specific responses, an increase in latency of auditory responses and a reduction in occurrence of burst firing in vMGN neurons. These findings indicate that demyelination of grey matter areas in the thalamocortical system permanently affects vMGN frequency specificity and the prevalence of bursting in the auditory thalamus.

A new role for evoked potentials in MS? Repurposing evoked potentials as biomarkers for clinical trials in MS

Evoked potentials (EP) characterize signal conduction in selected tracts of the central nervous system in a quantifiable way. Since alteration of signal conduction is the main mechanism of symptoms and signs in multiple sclerosis (MS), multimodal EP may serve as a representative measure of the functional impairment in MS. Moreover, EP have been shown to be predictive for disease course, and thus might help to select patient groups at high risk of progression for clinical trials. EP can detect deterioration, as well as improvement of impulse propagation, independently from the mechanism causing the change. Therefore, they are candidates for biomarkers with application in clinical phase-II trials. Applicability of EP in multicenter trials has been limited by different standards of registration and assessment.