Assessment of Motor Evoked Potentials in Multiple Sclerosis

Machine Learning Algorithms Introduce Evoked Potentials As Alternative Biomarkers for the Expanded Disability Status Scale Prognosis of Multiple Sclerosis Patients

Machine learning (ML) has witnessed a notable increase in significance within the medical field, primarily due to the increasing availability of health-related data and the progressive enhancements in ML algorithms. Thus, ML can be utilized to formulate predictive models that aid in disease diagnosis, anticipate disease progression, tailor treatment to fulfill individual patient needs, and improve the operational efficiency of healthcare systems. Timely detection of a disease contributes to effective symptom management and guarantees that appropriate treatment is provided. In multiple sclerosis (MS), evoked potentials (EPs) show a strong correlation with the Expanded Disability Status Scale (EDSS), suggesting their potential as reliable predictors of disability progression. The aim of the present study is to apply artificial intelligence (AI) techniques to identify predictors linked to the progression of MS as assessed by the disability index (EDSS). It is essential to clarify the role of EPs in the prognostication of MS. We conducted an analysis of empirical data obtained from a medical database consisting of 125 records. Our primary objective is to construct an expert AI system capable of predicting the EDSS index through the application of advanced knowledge-mining algorithms. We have developed intelligent systems that predict the progression of MS utilizing ML algorithms, specifically decision trees and neural networks. In our experimental evaluation, decision trees, neural networks, and Bayes for EPs achieved accuracies of 88.9%, 92.9%, and 88.2% respectively, which are comparable to MRI that obtained accuracies of 88.2%, 96.0%, and 85.0%. The EPs can be established as predictors of MS with efficacy analogous to that of MRI findings. Further investigation is necessary to validate EPs, which are significantly less expensive, portable, and simpler to administer than MRI, as equally effective as imaging or biochemical methods in functioning as biomarkers for MS.

Accurate determination of motor evoked potential amplitude in TMS: The impact of personal and experimental factors

OBJECTIVE

Corticospinal excitability can be quantified using motor-evoked potentials (MEP) following transcranial magnetic stimulation (TMS). However, the inherent variability of MEPs poses significant challenges. We establish a framework using personal and experimental factors to select the optimal number of trials (nopt) required for reliable MEP estimates.

METHODS

47 healthy younger underwent single-pulse TMS over the left primary motor cortex (M1). Per participant, 550 MEPs were collected at intensities ranging from 110 % to 150 % of the resting motor threshold (rMT), in 10 % increments. Per intensity, we calculated nopt. We analyzed which personal and experimental factors affected nopt.

RESULTS

nopt decreased with increasing TMS intensity, lower rMT baseline values, and exclusion of single-trial outliers. Sex had no significant effect.

CONCLUSIONS

Our study indicates that even when TMS is used as an outcome measure, custom-tailoring its protocol to study-related circumstances is key, as TMS intensity, outliers, baseline rMT, and the desired precision level affect the number of TMS trials needed to obtain a reliable MEP. Thus, we underscore the absence of a universal rule-of-thumb rule, although our predictive equations and online tool provide future TMS experimenters with the means to estimate the required number of TMS trials based on individual characteristics and specific experimental conditions.

SIGNIFICANCE

Our predictive equations offer a tailored approach for selecting nopt, enhancing the reliability of TMS-derived corticospinal excitability measurements.

MEPFeatX-automated feature extraction of motor-evoked potentials in transcranial magnetic stimulation

Motor evoked potentials (MEPs) are an important measure in transcranial magnetic stimulation (TMS) when assessing neuronal excitability in clinical diagnostics related to motor function, as well as in neuroscience research. However, manual feature extraction from large datasets can be time-consuming and prone to human error, and valuable features, such as MEP polyphasia and duration, are often neglected. Several packages have been developed to simplify the process; however, they are often tailored to specific studies or are not accessible. Here, we introduce MEPFeatX, a verified MATLAB package designed for automated and comprehensive MEP feature extraction across a wide range of stimulation paradigms. MEPFeatX is designed and documented for easy integration into any MEP analysis pipeline. Primed templates for specific paradigms, as well as additional analysis coded in R language, are also provided. Thus, MEPFeatX provides its users with a comprehensive and accurate set of MEP features, along with their visuals, facilitating quick and reliable MEP analysis in TMS studies.

Cross-sectional and longitudinal evaluation of white matter microstructure damage and cognitive correlations by automated fibre quantification in relapsing-remitting multiple sclerosis patients

The purpose of this study was to characterize whole-brain white matter (WM) fibre tracts by automated fibre quantification (AFQ), capture subtle changes cross-sectionally and longitudinally in relapsing-remitting multiple sclerosis (RRMS) patients and explore correlations between these changes and cognitive performance A total of 114 RRMS patients and 71 healthy controls (HCs) were enrolled and follow-up investigations were conducted on 46 RRMS patients. Fractional anisotropy (FA), mean diffusion (MD), axial diffusivity (AD), and radial diffusivity (RD) at each node along the 20 WM fibre tracts identified by AFQ were investigated cross-sectionally and longitudinally in entire and pointwise manners. Partial correlation analyses were performed between the abnormal metrics and cognitive performance. At baseline, compared with HCs, patients with RRMS showed a widespread decrease in FA and increases in MD, AD, and RD among tracts. In the pointwise comparisons, more detailed abnormalities were localized to specific positions. At follow-up, although there was no significant difference in the entire WM fibre tract, there was a reduction in FA in the posterior portion of the right superior longitudinal fasciculus (R_SLF) and elevations in MD and AD in the anterior and posterior portions of the right arcuate fasciculus (R_AF) in the pointwise analysis. Furthermore, the altered metrics were widely correlated with cognitive performance in RRMS patients. RRMS patients exhibited widespread WM microstructure alterations at baseline and alterations in certain regions at follow-up, and the altered metrics were widely correlated with cognitive performance in RRMS patients, which will enhance our understanding of WM microstructure damage and its cognitive correlation in RRMS patients.

Differentiating Neurodegenerative Disease From Compressive Cervical Myelopathy Using Motor-Evoked Potentials

STUDY DESIGN

A retrospective case-control study.

OBJECTIVE

To differentiate neurodegenerative diseases from compressive cervical myelopathy (CCM) using motor-evoked potentials (MEPs).

SUMMARY OF BACKGROUND DATA

When considering surgery for CCM, it may be necessary to differentiate the condition from a neurodegenerative disease.

MATERIALS AND METHODS

A total of 30 healthy volunteers, 52 typical CCM patients with single-level compression of the spinal cord at C4-5 or C5-6, 7 patients with amyotrophic lateral sclerosis (ALS), and 12 patients with demyelinating disease of the central nervous system, including 11 patients with multiple sclerosis and 1 patient with neuromyelitis optica spectrum disorder, formed our study population. MEPs were recorded from the bilateral abductor digiti minimi (ADM) and abductor hallucis (AH) muscles using transcranial magnetic stimulation and electrical stimulation of the ulnar and tibial nerves. Central motor conduction time, peripheral conduction time, amplitude of MEPs, and frequency of F waves were evaluated. Receiver operating characteristic curve analysis was used to determine the cutoff value for distinguishing between CCM and ALS.

RESULTS

Significant differences were observed in the amplitude of MEPs and frequency of F waves evoked by peripheral nerve stimulation between patients with CCM and ALS. The MEP amplitude of AH was more accurate in differentiating between the two diseases compared with ADM (cutoff value, 11.2 mV, sensitivity, 87.5%; specificity, 85.7%). All 7 patients with ALS showed reduced frequency of F waves from ADM or AH, but none of the healthy volunteers or patients with other diseases demonstrated this finding. Moreover, there were no significant differences between CCM and demyelinating disease of the central nervous system in any of the assessments.

CONCLUSION

The amplitude of MEPs and frequency of F waves evoked by peripheral nerve stimulation could be helpful in differentiating ALS from CCM.

Characteristics of motor evoked potentials in patients with peripheral vascular disease

With an aging population, it is common to encounter people diagnosed with peripheral vascular disease (PVD). Some will undergo surgeries during which the spinal cord may be compromised and intraoperative neuromonitoring with motor evoked potentials (MEPs) is employed to help mitigate paralysis. No data exist on characteristics of MEPs in older, PVD patients, which would be valuable for patients undergoing spinal cord at-risk surgery or participating in neurophysiological research. Transcranial magnetic stimulation, which can be delivered to the awake patient, was used to stimulate the motor cortex of 20 patients (mean (±SD)) age 63.2yrs (±11.5) with confirmed PVD, every 10 minutes for one hour with MEPs recorded from selected upper and lower limb muscles. Data were compared to that from 20 healthy volunteers recruited for a protocol development study (28yrs (±7.6)). MEPs did not differ between patient's symptomatic and asymptomatic legs. MEP amplitudes were not different for a given muscle between patients and healthy participants. Except for vastus lateralis, disease severity did not correlate with MEP amplitude. There were no differences over time in the coefficient of variation of MEP amplitude at each time point for any muscle in patients or in healthy participants. Although latencies of MEPs were not different between patients and healthy participants for a given muscle, they were longer in older participants. The results obtained suggest PVD alone does not impact MEPs; there were no differences between more symptomatic and less symptomatic legs. Further, in general, disease severity did not corelate with MEP characteristics. With an aging population, more patients with PVD and cardiovascular risk factors will be participating in neurophysiological studies or undergoing surgery where spinal cord integrity is monitored. Our data show that MEPs from these patients can be easily evoked and interpreted.

A new era of current and future treatment applications of transcranial magnetic stimulation

Background

Transcranial magnetic stimulation (TMS) equipment has advanced dramatically over the years thanks to considerable advancements in signal motors, coils, placement devices, and modeling, optimization, and treatment scheduling programs. In this review, a primary assessment of the impact of transcranial magnetic stimulation (TMS) on seizure course in people with and without epilepsy has been done through search in the Embase, PubMed, Scopus, and Web of Science databases. Other proposed roles of TMS in various studies has been reported. The features of TMS protocols for several potential disorders was assessed and the key TMS findings has been documented starting from 1985 until 2023.

Results

More than 500 papers were found that describe various research populations, TMS techniques, and TMS functions in 16 various medical conditions.

Conclusion

After reviewing recent updates in TMS, further researches are needed to improve the technical part of the used TMS protocols and to have definitive results not experimental one with regard to TMS usage in various psychiatric and neurological disorders.

Transcranial Magnetic Stimulation Measures, Pyramidal Score on Expanded Disability Status Scale and Magnetic Resonance Imaging of Corticospinal Tract in Multiple Sclerosis

Probing the cortic ospinal tract integrity by transcranial magnetic stimulation (TMS) could help to understand the neurophysiological correlations of multiple sclerosis (MS) symptoms. Therefore, the study objective was, first, to investigate TMS measures (resting motor threshold-RMT, motor evoked potential (MEP) latency, and amplitude) of corticospinal tract integrity in people with relapsing-remitting MS (pwMS). Then, the study examined the conformity of TMS measures with clinical disease-related (Expanded Disability Status Scale-EDSS) and magnetic resonance imaging (MRI) results (lesion count) in pwMS. The e-field navigated TMS, MRI, and EDSS data were collected in 23 pwMS and compared to non-clinical samples. The results show that pwMS differed from non-clinical samples in MEP latency for upper and lower extremity muscles. Also, pwMS with altered MEP latency (prolonged or absent MEP response) had higher EDSS, general and pyramidal, functional scores than pwMS with normal MEP latency finding. Furthermore, the RMT intensity for lower extremity muscles was predictive of EDSS functional pyramidal scores. TMS/MEP latency findings classified pwMS as the same as EDSS functional pyramidal scores in 70-83% of cases and were similar to the MRI results, corresponding to EDSS functional pyramidal scores in 57-65% of cases. PwMS with altered MEP latency differed from pwMS with normal MEP latency in the total number of lesions in the brain corticospinal and cervical corticospinal tract. The study provides preliminary results on the correspondence of MRI and TMS corticospinal tract evaluation results with EDSS functional pyramidal score results in MS.

The Cortical Silent Period in the Cricothyroid Muscle as a Neurophysiologic Feature for Dystonia Observation: E-Field-Navigated Transcranial Magnetic (TMS) Study

The cortical silent period (cSP) is a period of electrical silence following a motor-evoked potential (MEP) in the electromyographic signal recorded from a muscle. The MEP can be elicited by transcranial magnetic stimulation (TMS) over the primary motor cortex site corresponding with the muscle. The cSP reflects the intracortical inhibitory process mediated by GABA_A and GABA_B receptors. The study aimed to investigate the cSP in the cricothyroid (CT) muscle after applying e-field-navigated TMS over the laryngeal motor cortex (LMC) in healthy subjects. Then, a cSP as a neurophysiologic feature for laryngeal dystonia was observed. We applied a single-pulse e-field-navigated TMS to the LMC over both hemispheres with hook-wire electrodes positioned in the CT muscle in nineteen healthy participants, which triggered the elicitation of contralateral and ipsilateral corticobulbar MEPs. The subjects were engaged in a vocalization task, and then we assessed the following metrics: LMC intensity, peak-to-peak MEP amplitude in the CT muscle, and cSP duration. The results showed that the cSP duration from the contralateral CT muscle was distributed from 40 ms to 60.83 ms, and from the ipsilateral CT muscle, from 40 ms to 65.58 ms. Also, no significant difference was found between the contralateral and ipsilateral cSP duration (t(30) = 0.85, p = 0.40), MEP amplitude in the CT muscle (t(30) = 0.91, p = 0.36), and LMC intensity (t(30) = 1.20, p = 0.23). To conclude, the applied research protocol showed the feasibility of recording LMC corticobulbar MEPs and observing the cSP during vocalization in healthy participants. Furthermore, an understanding of neurophysiologic cSP features can be used to study the pathophysiology of neurological disorders that affect laryngeal muscles, such as laryngeal dystonia.