Structural brain connectivity in patients with restless legs syndrome: a diffusion tensor imaging study

Difference in functional connectivity between end-stage renal disease patients with and without restless legs syndrome: A prospective study

PURPOSE

The purpose of this study was to examine differences in functional connectivity between patients with end-stage renal disease (ESRD) with and without restless legs syndrome (RLS). In addition, the study aimed to identify any potential associations between RLS severity and functional connectivity.

METHODS

We enrolled patients with ESRD who had been undergoing hemodialysis. Patients with and without RLS were separated into two groups. Using functional near-infrared spectroscopy (fNIRS) and a graph theory approach, we determined the functional connectivity of patients with ESRD. The data were collected during a 300-s resting state evaluation performed in the dialysis room prior to dialysis.

RESULTS

Eighteen of 48 patients with ESRD were diagnosed with RLS, whereas 30 patients did not exhibit RLS symptoms. Notably, functional connectivity metrics differed significantly between patients with and without RLS. Specifically, patients with ESRD and RLS displayed higher values for mean clustering coefficient (0.474 vs. 0.352, p = 0.001), global efficiency (0.520 vs. 0.414, p = 0.001), strength (6.538 vs. 4.783, p = 0.001), and transitivity (0.714 vs. 0.521, p = 0.001), while values for diameter (5.451 vs. 7.338, p = 0.002), eccentricity (4.598 vs. 5.985, p = 0.004), and characteristic path length (2.520 vs. 3.271, p = 0.002) were lower in patients with ESRD and RLS compared to those without RLS. In addition, there were correlations between the RLS severity score and the assortative coefficient (r = 0.479, p = 0.044), the small-worldness index (r = -0.475, p = 0.046), and transitivity (r = 0.500, p = 0.034).

CONCLUSIONS

We demonstrated differences in functional connectivity between patients with ESRD with and without RLS, which may shed light on the pathophysiology of RLS. Notably, a number of functional connectivity metrics demonstrated strong associations with RLS severity. Our study also confirmed the applicability of fNIRS as a tool for investigating functional connectivity in patients with RLS.

Structural and functional multilayer network analysis in restless legs syndrome patients

The combination of brain structural and functional connectivity offers complementary insights into its organisation. Multilayer network analysis explores various relationships across different layers within a single system. We aimed to investigate changes in the structural and functional multilayer network in 69 patients with primary restless legs syndrome (RLS) compared with 50 healthy controls. Participants underwent diffusion tensor imaging (DTI) and resting state-functional magnetic resonance imaging (rs-fMRI) using a three-tesla MRI scanner. We constructed a structural connectivity matrix derived from DTI using a DSI program and made a functional connectivity matrix based on rs-fMRI using an SPM program and CONN toolbox. A multilayer network analysis, using BRAPH program, was then conducted to assess the connectivity patterns in both groups. At the global level, significant differences there were between the patients with RLS and healthy controls. The average multiplex participation was lower in patients with RLS than in healthy controls (0.804 vs. 0.821, p = 0.042). Additionally, several regions showed significant differences in the nodal level in multiplex participation between patients with RLS and healthy controls, particularly the frontal and temporal lobes. The regions affected included the inferior frontal gyrus, medial orbital gyrus, precentral gyrus, rectus gyrus, insula, superior and inferior temporal gyrus, medial and lateral occipitotemporal gyrus, and temporal pole. These results represent evidence of diversity in interactions between structural and functional connectivity in patients with RLS, providing a more comprehensive understanding of the brain network in RLS. This may contribute to a precise diagnosis of RLS, and aid the development of a biomarker to track treatment effectiveness.

A survey-based approach on restless legs syndrome: practices and perspectives among Italian neurologists

INTRODUCTION

Restless Legs Syndrome (RLS) is a widely prevalent and complex neurological disorder. Despite notable advancements in managing RLS, the disorder continues to face challenges related to its recognition and management.

OBJECTIVE

This study seeks to gain comprehensive insights into the knowledge and clinical practices among Italian neurologists regarding RLS diagnosis, management, and treatment, comparing approaches among general neurologists, movement disorder specialists, and sleep experts.

METHODS

Members of the Italian Society of Neurology, the Italian Society of Parkinson and Movement Disorders, and the Italian Association of Sleep Medicine were invited to participate in a 19-question online survey.

RESULTS

Among the 343 surveyed neurologists, 60% categorized RLS as a "sleep-related movement disorder." Forty% indicated managing 5-15 RLS patients annually, with sleep specialists handling the highest patient volume. Of note, only 34% adhered strictly to all five essential diagnostic criteria. The majority (69%) favored low-dosage dopamine agonists as their first-line treatment, with movement disorder specialists predominantly endorsing this approach, while sleep experts preferred iron supplementation. Regular screening for iron levels was widespread (91%), with supplementation typically guided by serum iron alterations. In cases of ineffective initial treatments, escalating dopamine agonist dosage was the preferred strategy (40%).

CONCLUSIONS

These findings underscore a lack of a clear conceptualization of RLS, with a widespread misconception of the disorder as solely a movement disorder significantly influencing treatment approaches. Disparities in RLS understanding across neurology subspecialties underscore the necessity for improved diagnostic accuracy, targeted educational initiatives, and management guidelines to ensure consistent and effective RLS management.

Alterations in the multilayer network in patients with rapid eye movement sleep behaviour disorder

This study aimed to reveal the pathophysiology of isolated rapid eye movement sleep behaviour disorder (RBD) in patients using multilayer network analysis. Participants eligible for isolated RBD were included and verified via polysomnography. Both iRBD patients and healthy controls underwent brain MRI, including T1-weighted imaging and diffusion tensor imaging. Grey matter matrix was derived from T1-weighted images using a morphometric similarity network. White matter matrix was formed from diffusion tensor imaging-based structural connectivity. Multilayer network analysis of grey and white matter was performed using graph theory. We studied 29 isolated RBD patients and 30 healthy controls. Patients exhibited a higher average overlap degree (27.921 vs. 23.734, p = 0.002) and average multilayer clustering coefficient (0.474 vs. 0.413, p = 0.002) compared with controls. Additionally, several regions showed significant differences in the degree of overlap and multilayer clustering coefficient between patients with isolated RBD and healthy controls at the nodal level. The degree of overlap in the left medial orbitofrontal, left posterior cingulate, and right paracentral nodes and the multilayer clustering coefficients in the left lateral occipital, left rostral middle frontal, right fusiform, right inferior posterior parietal, and right parahippocampal nodes were higher in patients with isolated RBD than in healthy controls. We found alterations in the multilayer network at the global and nodal levels in patients with isolated RBD, and these changes may be associated with the pathophysiology of isolated RBD. Multilayer network analysis can be used widely to explore the mechanisms underlying various neurological disorders.

From brain to spinal cord: neuromodulation by direct current stimulation and its promising effects as a treatment option for restless legs syndrome

Neuromodulation is a fast-growing field of mostly non-invasive therapies, which includes spinal cord stimulation (SCS), transcranial direct current stimulation (tDCS), vagal nerve stimulation (VNS), peripheral nerve stimulation, transcranial magnetic stimulation (TMS) and transcutaneous spinal direct current stimulation (tsDCS). This narrative review offers an overview of the therapy options, especially of tDCS and tsDCS for chronic pain and spinal cord injury. Finally, we discuss the potential of tsDCS in Restless Legs Syndrome as a promising non-invasive, alternative therapy to medication therapy.

Structural connectivity as a predictive factor for responsiveness to levetiracetam treatment in epilepsy

PURPOSE

To investigate whether structural connectivity or glymphatic system function is a potential predictive factor for levetiracetam (LEV) response in patients with newly diagnosed epilepsy.

METHODS

We enrolled patients with newly diagnosed epilepsy who were administered LEV as initial monotherapy and underwent diffusion tensor imaging (DTI) at diagnosis. We categorized the patients into drug response. We used graph theory to calculate the network measures for structural connectivity based on the DTI scans in patients with epilepsy. Additionally, we evaluated glymphatic system function by calculating the DTI analysis along the perivascular space (DTI-ALPS) index based on DTI scans.

RESULTS

We enrolled 84 patients with epilepsy. The clinical factors and DTI-ALPS index did not differ between the groups. However, some of the structural connectivity measures significantly differ between the groups. The poor responders exhibited a higher mean clustering coefficient, global efficiency, and small-worldness index than the good responders (p = 0.003, p = 0.048, and p = 0.038, respectively). In the receiver operating characteristic curve analysis, the mean clustering coefficient exhibited the highest performance in predicting the responsiveness to LEV (area under the curve of 0.677). In the multiple logistic regression analysis, the mean clustering coefficient of the structural connectivity measures was the only significant predictor of LEV response (p = 0.014). Furthermore, in the survival analysis, the mean clustering coefficient was the only significant predictor of LEV response (p = 0.026).

CONCLUSION

We demonstrated that structural connectivity is a potential predictive factor for responsiveness to LEV treatment in patients with newly diagnosed epilepsy.

Glymphatic system dysfunction in restless legs syndrome: evidenced by diffusion tensor imaging along the perivascular space

STUDY OBJECTIVES

There is growing evidence pointing at glymphatic system dysfunction in diseases with circadian disruption, such as sleep disorders. Lower diffusivity in the direction of perivascular space has been shown in several neurological and sleep-related disorders; however, its role in restless legs syndrome (RLS) is unclear. We hypothesized that similarly, in RLS the diffusivity in glymphatic system is decreased. Here, we aimed to evaluate glymphatic system functionality in patients with RLS, compare it to healthy controls, and analyze the correlation between its function and clinical characteristics.

METHODS

Sixty-nine patients with primary RLS and 51 healthy controls were recruited at a tertiary hospital. All participants underwent diffusion tensor imaging (DTI) and magnetic resonance imaging (MRI) using a 3T MRI scanner, and the DTI along the perivascular space (DTI-ALPS) index was calculated using DTI data. We compared the DTI-ALPS index between the patients with RLS and healthy controls. We also conducted the correlation analysis between the DTI-ALPS index and clinical characteristics, including age, age of onset, symptom duration, and RLS severity.

RESULTS

DTI-ALPS index differed significantly between the patients with RLS and healthy controls; the DTI-ALPS index in the patients with RLS was lower than that in the healthy controls (1.48 vs. 0.60, p = 0.008). There was no significant correlation between the DTI-ALPS index and clinical characteristics.

CONCLUSION

A significantly lower DTI-ALPS index in patients with RLS suggests that the glymphatic system function is impaired in patients with RLS.

Correlation of Diffusion Tensor Tractography with Restless Legs Syndrome Severity

This prospective study investigated white matter tracts associated with restless legs syndrome (RLS) severity in 69 patients with primary RLS using correlational tractography based on diffusion tensor imaging. Fractional anisotropy (FA) and quantitative anisotropy (QA) were analyzed separately to understand white matter abnormalities in RLS patients. Connectometry analysis revealed positive correlations between RLS severity and FA values in various white matter tracts, including the left and right cerebellum, corpus callosum forceps minor and major, corpus callosum body, right cingulum, and frontoparietal tract. In addition, connectometry analysis revealed that the FA of the middle cerebellar peduncle, left inferior longitudinal fasciculus, left corticospinal tract, corpus callosum forceps minor, right cerebellum, left frontal aslant tract, left dentatorubrothalamic tract, right inferior longitudinal fasciculus, left corticostriatal tract superior, and left cingulum parahippocampoparietal tract was negatively correlated with RLS severity in patients with RLS. However, there were no significant correlations between QA values and RLS severity. It is implied that RLS symptoms may be potentially reversible with appropriate treatment. This study highlights the importance of considering white matter alterations in understanding the pathophysiology of RLS and in developing effective treatment strategies.

Cerebellum drives functional dysfunctions in restless leg syndrome

OBJECTIVE

Restless legs syndrome (RLS) has serious effects on patients' sleep quality, physical and mental health. However, the pathophysiological mechanisms of RLS remain unclear. This study utilized both static and dynamic functional activity and connectivity analyses approaches as well as effective connectivity analysis to reveal the neurophysiological basis of RLS.

METHODS

The resting-state functional MRI (rs-fMRI) data from 32 patients with RLS and 33 age-, and gender-matched healthy control (HC) were collected. Dynamic and static amplitude of low frequency fluctuation (ALFF), functional connectivity (FC), and Granger causality analysis (GCA) were employed to reveal the abnormal functional activities and couplings in patients with RLS.

RESULTS

RLS patients showed over-activities in left parahippocampus and right cerebellum, hyper-connectivities of right cerebellum with left basal ganglia, left postcentral gyrus and right precentral gyrus, and enhanced effective connectivity from right cerebellum to left postcentral gyrus compared to HC.

CONCLUSIONS

Abnormal cerebellum-basal ganglia-sensorimotor cortex circuit may be the underlying neuropathological basis of RLS. Our findings highlight the important role of right cerebellum in the onset of RLS and suggest right cerebellum may be a potential target for precision therapy.

White matter microstructure alterations in idiopathic restless legs syndrome: a study combining crossing fiber-based and tensor-based approaches

Introduction

Restless legs syndrome (RLS) is a common sensorimotor disorder characterized by an irrepressible urge to move the legs and frequently accompanied by unpleasant sensations in the legs. The pathophysiological mechanisms underlying RLS remain unclear, and RLS is hypothesized to be associated with alterations in white matter tracts.

Methods

Diffusion MRI is a unique noninvasive method widely used to study white matter tracts in the human brain. Thus, diffusion-weighted images were acquired from 18 idiopathic RLS patients and 31 age- and sex-matched healthy controls (HCs). Whole brain tract-based spatial statistics (TBSS) and atlas-based analyzes combining crossing fiber-based metrics and tensor-based metrics were performed to investigate the white matter patterns in individuals with RLS.

Results

TBSS analysis revealed significantly higher fractional anisotropy (FA) and partial volume fraction of primary (F1) fiber populations in multiple tracts associated with the sensorimotor network in patients with RLS than in HCs. In the atlas based analysis, the bilateral anterior thalamus radiation, bilateral corticospinal tract, bilateral inferior fronto-occipital fasciculus, left hippocampal cingulum, left inferior longitudinal fasciculus, and left uncinate fasciculus showed significantl increased F1, but only the left hippocampal cingulum showed significantly higher FA.

Discussion

The results demonstrated that F1 identified extensive alterations in white matter tracts compared with FA and confirmed the hypothesis that crossing fiber-based metrics are more sensitive than tensor-based metrics in detecting white matter abnormalities in RLS. The present findings provide evidence that the increased F1 metric observed in sensorimotor tracts may be a critical neural substrate of RLS, enhancing our understanding of the underlying pathological changes.