The utility of multimodal evoked potentials in multiple sclerosis prognostication

MRI features and disability in multiple sclerosis: A systematic review and meta-analysis

BACKGROUND

In this systematic review and meta-analysis, we aimed to investigate the correlation between disability in patients with Multiple sclerosis (MS) measured by the Expanded Disability Status Scale (EDSS) and brain Magnetic Resonance Imaging (MRI) features to provide reliable results on which characteristics in the MRI can predict disability and prognosis of the disease.

METHODS

A systematic literature search was performed using three databases including PubMed, Scopus, and Web of Science. The selected peer-reviewed studies must report a correlation between EDSS scores and MRI features. The correlation coefficients of included studies were converted to the Fisher's z scale, and the results were pooled.

RESULTS

Overall, 105 studies A total of 16,613 patients with MS entered our study. We found no significant correlation between total brain volume and EDSS assessment (95 % CI: -0.37 to 0.08; z-score: -0.15). We examined the potential correlation between the volume of T1 and T2 lesions and the level of disability. A positive significant correlation was found (95 % CI: 0.19 to 0.43; z-score: 0.31), (95 % CI: 0.17 to 0.33; z-score: 0.25). We observed a significant correlation between white matter volume and EDSS score in patients with MS (95 % CI: -0.37 to -0.03; z-score: -0.21). Moreover, there was a significant negative correlation between gray matter volume and disability (95 % CI: -0.025 to -0.07; z-score: -0.16).

CONCLUSION

In conclusion, this systematic review and meta-analysis revealed that disability in patients with MS is linked to extensive changes in different brain regions, encompassing gray and white matter, as well as T1 and T2 weighted MRI lesions.

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.

Somatosensory evoked potentials and their relation to microstructural damage in patients with multiple sclerosis—A whole brain DTI study

Introduction

Somatosensory evoked potentials (SSEP) play a pivotal role in the diagnosis and disease monitoring of multiple sclerosis (MS). Delayed latencies are a surrogate for demyelination along the sensory afference. This study aimed to evaluate if SSEP latencies are representative of demyelination of the brain overall, by correlating with cerebral microstructural integrity as measured by Magnetic resonance (MR) diffusion tensor imaging (DTI). Analysis was performed in a hypothesis-free whole brain approach using tract-based spatial statistics (TBSS).

Material and methods

A total of 46 patients with MS or clinically isolated syndrome were included in the study. Bilateral SSEPs of the median nerve measuring mean N20 latencies (mN20) and Central Conduction Time (CCT), were acquired. MRI scans were performed at 3T. DTI acquisition was done with a single-shot echoplanar imaging technique with 80 diffusion directions. The FSL software package was used to process the DTI datasets and to calculate maps of fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD). These maps were then further analyzed using the TBSS module. The mean N20 and CCT and the right- and left-sided N20 and CCT were separately correlated to FA, AD, and RD, controlled for age, gender, and EDSS as variables of non-interest.

Results

Widespread negative correlations of SSEP latencies with FA (p = 0.0005) and positive correlations with RD (p = 0.0003) were measured in distinct white matter tracts, especially the optic tracts, corpus callosum, and posterior corona radiata. No correlation with AD was found in any white matter tract.

Conclusion

Highly significant correlations of FA and RD to SSEPs suggest that their latency is representative of widespread microstructural change, and especially demyelination in patients suffering from MS, reaching beyond the classic somatosensory regions. This points to the usefulness of SSEPs as a non-invasive tool in the evaluation of microstructural damage to the brain.

Somatosensory evoked potentials in clinical practice: a review

The authors present a review of the current use of somatosensory evoked potentials (SSEPs) in neurological practice as a non-invasive neurophysiological technique. For this purpose we have reviewed articles published in English or Portuguese in the PubMed and LILACS databases. In this review, we address the role of SSEPs in neurological diseases that affect the central nervous system and the peripheral nervous system, especially in demyelinating diseases, for monitoring coma, trauma and the functioning of sensory pathways during surgical procedures. The latter, along with new areas of research, has become one of the most important applications of SSEPs.

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.

Early diagnosis of secondary progressive multiple sclerosis: focus on fluid and neurophysiological biomarkers

BACKGROUND AND AIMS

Most patients with multiple sclerosis presenting with a relapsing-remitting disease course at diagnosis transition to secondary progressive multiple sclerosis (SPMS) 1-2 decades after onset. SPMS is characterized by predominant neurodegeneration and atrophy. These pathogenic hallmarks result in unsatisfactory treatment response in SPMS patients. Therefore, early diagnosis of SPMS is necessary for prompt treatment decisions. The aim of this review was to assess neurophysiological and fluid biomarkers that have the potential to monitor disease progression and support early SPMS diagnosis.

METHODS

We performed a systematic review of studies that analyzed the role of neurophysiological techniques and fluid biomarkers in supporting SPMS diagnosis using the preferred reporting items for systematic reviews and meta-analyses statement.

RESULTS

From our initial search, we selected 24 relevant articles on neurophysiological biomarkers and 55 articles on fluid biomarkers.

CONCLUSION

To date, no neurophysiological or fluid biomarker is sufficiently validated to support the early diagnosis of SPMS. Neurophysiological measurements, including short interval intracortical inhibition and somatosensory temporal discrimination threshold, and the neurofilament light chain fluid biomarker seem to be the most promising. Cross-sectional studies on an adequate number of patients followed by longitudinal studies are needed to confirm the diagnostic and prognostic value of these biomarkers. A combination of neurophysiological and fluid biomarkers may be more sensitive in detecting SPMS conversion.

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.

The clinical perspective: How to personalise treatment in MS and how may biomarkers including imaging contribute to this?

BACKGROUND

Multiple sclerosis (MS) is a highly heterogeneous disease, both in its course and in its response to treatments. Effective biomarkers may help predict disability progression and monitor patients' treatment responses.

OBJECTIVE

The aim of this review was to focus on how biomarkers may contribute to treatment individualisation in MS patients.

METHODS

This review reflects the content of presentations, polling results and discussions on the clinical perspective of MS during the first and second Pan-European MS Multi-stakeholder Colloquia in Brussels in May 2014 and 2015.

RESULTS

In clinical practice, magnetic resonance imaging (MRI) measures play a significant role in the diagnosis and follow-up of MS patients. Together with clinical markers, the rate of MRI-visible lesion accrual once a patient has started treatment may also help to predict subsequent treatment responsiveness. In addition, several molecular (immunological, genetic) biomarkers have been established that may play a role in predictive models of MS relapses and progression. To reach personalised treatment decisions, estimates of disability progression and likely treatment response should be carefully considered alongside the risk of serious adverse events, together with the patient's treatment expectations.

CONCLUSION

Although biomarkers may be very useful for individualised decision making in MS, many are still research tools and need to be validated before implementation in clinical practice.

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.

Do evoked potentials contribute to the functional follow-up and clinical prognosis of multiple sclerosis?

The clinical variability and complexity of multiple sclerosis (MS) challenges the individual clinical course prognostication. This study aimed to find out whether multimodal evoked potentials (EP) correlate with the motor components of multiple sclerosis functional composite (MSFCm) and predict clinically relevant motor functional deterioration. One hundred MS patients were assessed at baseline (T ₀) and about 7.5 years later (T ₁), with visual, somatosensory and motor EP and rated on the Expanded Disability Status Scale (EDSS) and the MSFCm, including the 9 Hole Peg Test and the Timed 25 Foot Walk (T25FW). The Spearman correlation coefficient (r _S) was used to evaluate the cross-sectional and longitudinal relationship between EP Z scores and clinical findings. The predictive value of baseline electrophysiological data for clinical worsening (EDSS, 9-HPT, T25FW, MSFCm) during follow-up was assessed by logistic regression analysis. Unlike longitudinal correlations, cross-sectional correlations between EP Z scores and clinical outcomes were all significant and ranged between 0.22 and 0.67 (p < 0.05). The global EP Z score was systematically predictive of EDSS and MSFCm worsening over time (all p < 0.05). EP latency was a better predictor than amplitude, although weaker than latency and amplitude aggregation in the global EP Z score. The study demonstrates that EP numerical scores can be used for motor function monitoring and outcome prediction in patients with MS.

Multimodal evoked potentials for functional quantification and prognosis in multiple sclerosis

BACKGROUND

Functional biomarkers able to identify multiple sclerosis (MS) patients at high risk of fast disability progression are lacking. The aim of this study was to evaluate the ability of multimodal (upper and lower limbs motor, visual, lower limbs somatosensory) evoked potentials (EP) to monitor disease course and identify patients exposed to unfavourable evolution.

METHODS

One hundred MS patients were assessed with visual, somatosensory and motor EP and rated on the Expanded Disability Status Scale (EDSS) at baseline (T0) and about 6 years later (T1). The Spearman correlation (rS) was used to evaluate the relationship between conventional EP scores and clinical findings. Multiple (logistic) regression analysis estimated the predictive value of baseline electrophysiological data for three clinical outcomes: EDSS, annual EDSS progression, and the risk of EDSS worsening.

RESULTS

In contrast to longitudinal correlations, cross-sectional correlations between the different EP scores and EDSS were all significant (0.33 ≤ rS < 0.67, p < 0.001). Baseline global EP score and EDSS were highly significant predictors (p < 0.0001) of EDSS progression 6 years later. The baseline global EP score was found to be an independent predictor of the EDSS annual progression rate (p < 0.001), and of the risk of disability progression over time (p < 0.005). Based on a ROC curve determination, we defined a Global EP Score cut off point (17/30) to identify patients at high risk of disability progression illustrated by a positive predictive value of 70%.

CONCLUSION

This study provides a proof of the concept that electrophysiology could be added to MRI and used as another complementary prognostic tool in MS patients.

Visual pathways involvement in clinically isolated syndrome in children

AIM

To investigate extent and nature of visual pathways involvement in children with clinically isolated syndrome (CIS).

METHODS

Forty-seven patients (age 11-17y) with CIS, which later proved to be multiple sclerosis (MS) onset, and 30 controls underwent visual evoked potentials (VEP) investigation within 12d from the appearance of the first signs of disease. Latency and amplitude of P100 peak were compared with normative data and between groups.

RESULTS

In 58% patients, including those without signs of retrobulbar neuritis, significant slowing of conduction along the central visual pathways (P100 latency lengthening) is seen. P100 amplitudes drop (signs of axonal damage) are registered less frequently (29% cases).

CONCLUSION

The results indicate that visual pathways are often affected in the MS onset; mostly demyelination signs are seen. Despite MRI significance for MS diagnostic, VEPs proved to be still effective in early diagnosis of MS in children.

Assessment of visual and auditory evoked potentials in multiple sclerosis patients with and without fatigue

The aim of the study was to evaluate visual and brainstem auditory evoked potentials (VEP, BAEP) in multiple sclerosis (MS) patients with regards to fatigue and disease-related variables. The study comprised 86 MS patients and 40 controls. Fatigue was assessed using the Fatigue Severity Scale (FSS/FSS-5) and the Modified Fatigue Impact Scale (MFIS). Latencies and amplitudes of the P100 component of VEP and the I–V components of BAEP were analyzed. The results of EP were compared between non-fatigued, moderately and severely fatigued MS patients and controls. P100 latency was increased and amplitude decreased in moderately and severely fatigued MS subjects. The latency of the V component of BAEP and interlatencies I-III-V were increased in severely fatigued patients. The amplitude of the V component was lowered in fatigued patients. VEP and BAEP abnormalities were usually one-sided. Interocular P100 latency difference tended to correlate with FSS/FSS-5. The parameters of VEP and BAEP correlated with functional system scores but not with MS duration, overall degree of disability or its progression over time. Significant, usually asymmetrical VEP and BAEP abnormalities were found in fatigued MS patients, with no relationships to disease-related variables. EP may be considered an electrophysiological marker of fatigue in MS patients.

There is still a role for the blink reflex in the diagnosis and follow-up of multiple sclerosis

OBJECTIVE

The evolution of the diagnostic criteria for multiple sclerosis (MS) has essentially evolved to clinical manifestations and magnetic resonance imaging. Inexpensive, quick to apply, non-invasive, quantitative and reliable neurophysiological tests are rare in daily practice and absent in clinical trials.

METHOD

The blink reflex was assessed in 50 patients with remitting-relapsing MS (RRMS) and 100 matched controls.

RESULTS

Patients with RRMS had abnormalities in the blink reflex waves in relation to controls. If only RRMS patients were considered, these abnormalities were more pronounced in patients with longer disease duration, higher disability and for those with clinical or image lesions in the brainstem.

CONCLUSION

Neurophysiological tests, such as the blink reflex, can be used for helping the diagnosis and follow-up of patients with RRMS, since the reflex can identify dissemination in time and in space in a clear and quantitative manner.

SIGNIFICANCE

Potential good methods for diagnosis and follow-up of MS should be considered for clinical trials and daily practice.

Prediction of MS disability by multimodal evoked potentials: investigation during relapse or in the relapse-free interval?

OBJECTIVE

Little is known about optimal timing of multimodal evoked potential (EP)-investigations regarding prediction of MS disability. The aim of this study was to investigate whether timing of EP-investigations during a relapse or in the relapse-free interval influences prediction of MS disability.

METHODS

Two groups of MS patients with similar age and gender distributions received visual, motor and somatosensory EPs either during a relapse (Group 1) or in the relapse-free interval (Group 2). Expanded Disability Status Score (EDSS) was obtained at baseline (T0) and year 3 (T2). Linear regression analysis was performed to examine the association between EDSS(T2) and a baseline EP compound measure (s-EP-Q(T0)) for each group.

RESULTS

Median EDSS(T0) was 3.0 for Group 1 and 1.5 for Group 2. Mean disease durations were 2.0 and 2.8 years, respectively. Median EDSS(T2) was 2.0 for both groups. The s-EP-Q(T0) significantly predicted EDSS(T2) (R(2)=0.47) for patients in Group 2, but not for patients in Group 1 (R(2)=0.07).

CONCLUSION

In early MS the functional remnants of relapses are a better predictor for development of medium-term disability than is the extent of impulse propagation impairment measured during relapse.

SIGNIFICANCE

This suggests a role of multimodal EPs in prediction of MS disability if performed in the relapse-free interval.