Regional grey matter microstructural changes and volume loss according to disease duration in multiple sclerosis patients

Multimodal magnetic resonance longitudinal study on the deep gray matter in multiple sclerosis patients with teriflunomide

Disease-modifying therapies (DMTs) are used in an increasing number of patients with multiple sclerosis (MS). However, whether DMTs have intrinsic effects on deep gray matter (DGM) microstructure and atrophy is still poorly understood. In this study, we described the quantitative susceptibility values (QSV) and diffusion kurtosis imaging (DKI) metrics of DGM in relapsing-remitting MS (RRMS) patients and their association with cognitive deficits. We recruited 62 patients with RRMS receiving DMTs and 30 patients with RRMS not receiving DMTs underwent MRI on a 3T scanner. Fractional anisotropy (FA), kurtosis fractional anisotropy (KFA), mean diffusivity (MD), mean kurtosis (MK), QSV and volumes of bilateral caudate nucleus (CAU), amygdala (AMYG), putamen (PUT), hippocampus (Hipp), globus pallidus (GP) and thalamus (THA) were measured. Correlation analysis was performed between those image indexes with longitudinal significant changes and clinical neurological scores, including Expanded Disability Status Scale (EDSS), Digit Span Testand (DST), Symbol Digit Modalities Test (SDMT), Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Significant longitudinal increases in FA, KFA and MK values were found in both groups in bilateral CAU, AMYG, PUT, Hipp, GP and THA (all p < 0.005). MD values of the right of CAU in the two groups were significant longitudinal increase (p = 0.009, p = 0.047); MD values of the right of GP (p = 0.042), the left of THA (p = 0.003), the right of THA (p = 0.001) in treated MS were significant longitudinal decrease; There were no significant longitudinal changes between treated and untreated groups in normalized deep gray matter volume. For QSV, longitudinal increase in the right of PUT (p = 0.022) in the treated MS group and in the left of Hipp (p = 0.045) in the untreated MS group. The QSV and DKI measures were highly correlated with cognitive and disability tests. The treated RRMS patients showed different longitudinal changes of MD value and QSV with untreated in several DGM regions, and these differences were correlated with cognitive and microstructural integrity.

Clemastine enhances exercise-induced motor improvement in hypoxic ischemic rats

Neonatal hypoxic ischemia (HI) occurs owing to reduced cerebral oxygen levels and perfusion during the perinatal period. Brain injury after HI triggers neurological manifestations such as motor impairment, and the improvement of impaired brain function remains challenging. Recent studies suggest that cortical myelination plays a role in motor learning, but its involvement in motor improvement after HI injury is not well understood. This study aimed to investigate the impact of myelination on motor improvement following neonatal HI injury. We employed a modified Rice-Vannucci model; the right common carotid artery of postnatal day 7 (P7) Wistar rats was isolated and divided, and the rats were then exposed to hypoxic condition (90 min, 8 % O2). A total of 101 rats (66 males) were divided into four groups: trained-HI (n = 38), trained-Sham (n = 16), untrained-HI (n = 31), and untrained-Sham (n = 16). The trained groups underwent rotarod-based exercise training from P22 to P41 (3 days per week). Structural analysis using magnetic resonance imaging and immunohistochemistry (n = 6 per group) revealed increased fractional anisotropy and myelin density in the primary somatosensory cortex of the trained-HI group. We further evaluated the effect of myelination promotion on rotarod performance by administering clemastine, a myelination-promoting drug, via daily intraperitoneal injections. Clemastine did not enhance motor improvement in untrained-HI rats. However, clemastine-administered trained-HI rats (n = 7) exhibited significantly improved motor performance compared to both saline-administered trained-HI rats (n = 11) and clemastine-administered untrained-HI rats (n = 7). These findings suggest that myelination may be a key mechanism in motor improvement after HI injury and that combining exercise training with clemastine administration could be an effective therapeutic strategy for motor improvement following HI injury.

Polygenic susceptibility for multiple sclerosis is associated with working memory in low-performing young adults

BACKGROUND

Multiple sclerosis (MS) is a complex disease with substantial heritability estimates. Besides typical clinical manifestations such as motor and sensory deficits, MS is characterized by structural and functional brain abnormalities, and by cognitive impairment such as decreased working memory (WM) performance.

OBJECTIVES

We investigated the possible link between the polygenic risk for MS and WM performance in healthy adults (18-35 years). Additionally, we addressed the relationship between polygenic risk for MS and white matter fractional anisotropy (FA).

METHODS

We generated a polygenic risk score (PRS) of MS susceptibility and investigated its association with WM performance in 3282 healthy adults (two subsamples, N1 = 1803, N2 = 1479). The association between MS-PRS and FA was studied in the second subsample. MS severity PRS associations were also investigated for the WM and FA measurements.

RESULTS

MS-PRS was significantly associated with WM performance within the 10% lowest WM-performing individuals (p = 0.001; pFDR = 0.018). It was not significantly associated with any of the investigated FA measurements. MS severity PRS was significantly associated with brain-wide mean FA (p = 0.041) and showed suggestive associations with additional FA measurements.

CONCLUSIONS

By identifying a genetic link between MS and WM performance this study contributes to the understanding of the genetic complexity of MS, and hopefully to the possible identification of molecular pathways linked to cognitive deficits in MS. It also contributes to the understanding of genetic associations with MS severity, as these associations seem to involve distinct biological pathways compared to genetic variants linked to the overall risk of developing MS.

Longitudinal network-based brain grey matter MRI measures are clinically relevant and sensitive to treatment effects in multiple sclerosis

In multiple sclerosis clinical trials, MRI outcome measures are typically extracted at a whole-brain level, but pathology is not homogeneous across the brain and so whole-brain measures may overlook regional treatment effects. Data-driven methods, such as independent component analysis, have shown promise in identifying regional disease effects but can only be computed at a group level and cannot be applied prospectively. The aim of this work was to develop a technique to extract longitudinal independent component analysis network-based measures of co-varying grey matter volumes, derived from T1-weighted volumetric MRI, in individual study participants, and assess their association with disability progression and treatment effects in clinical trials. We used longitudinal MRI and clinical data from 5089 participants (22 045 visits) with multiple sclerosis from eight clinical trials. We included people with relapsing-remitting, primary and secondary progressive multiple sclerosis. We used data from five negative clinical trials (2764 participants, 13 222 visits) to extract the independent component analysis-based measures. We then trained and cross-validated a least absolute shrinkage and selection operator regression model (which can be applied prospectively to previously unseen data) to predict the independent component analysis measures from the same regional MRI volume measures and applied it to data from three positive clinical trials (2325 participants, 8823 visits). We used nested mixed-effect models to determine how networks differ across multiple sclerosis phenotypes are associated with disability progression and to test sensitivity to treatment effects. We found 17 consistent patterns of co-varying regional volumes. In the training cohort, volume loss was faster in four networks in people with secondary progressive compared with relapsing-remitting multiple sclerosis and three networks with primary progressive multiple sclerosis. Volume changes were faster in secondary compared with primary progressive multiple sclerosis in four networks. In the combined positive trials cohort, eight independent component analysis networks and whole-brain grey matter volume measures showed treatment effects, and the magnitude of treatment-placebo differences in the network-based measures was consistently greater than with whole-brain grey matter volume measures. Longitudinal network-based analysis of grey matter volume changes is feasible using clinical trial data, showing differences cross-sectionally and longitudinally between multiple sclerosis phenotypes, associated with disability progression, and treatment effects. Future work is required to understand the pathological mechanisms underlying these regional changes.

Topological abnormalities of the morphometric similarity network of the cerebral cortex in schizophrenia

A morphometric similarity (MS) network can be constructed using multiple magnetic resonance imaging parameters of each cortical region. An MS network can be used to assess the similarity between cortical regions. Although MS networks can detect microstructural alterations and capture connections between histologically similar cortical areas, the influence of schizophrenia on the topological characteristics of MS networks remains unclear. We obtained T1- and diffusion-weighted images of 239 healthy controls and 190 individuals with schizophrenia to construct the MS network. Group comparisons of the mean MS of the cortical regions and subnetworks were performed. The strengths of the connections between the cortical regions and the global and nodal network indices were compared between the groups. Clinical associations with the network indices were tested using Spearman's rho. Compared with healthy controls, individuals with schizophrenia had significant group differences in the mean MS of several cortical regions and subnetworks. Individuals with schizophrenia had both superior and inferior strengths of connections between cortical regions compared with those of healthy controls. We observed regional abnormalities of the MS network in individuals with schizophrenia regarding lower centrality values of the pars opercularis, superior frontal, and superior temporal areas. Specific nodal network measures of the right pars opercularis and left superior temporal areas were associated with illness duration in individuals with schizophrenia. We identified regional abnormalities of the MS network in schizophrenia with the left superior temporal area possibly being a key region in topological organization and cortical connections.

The cognitive relevance of non-lesional damage to cortical networks in people with multiple sclerosis

BACKGROUND

Cognitive impairment, a common and debilitating symptom in people with multiple sclerosis (MS), is especially related to cortical damage. However, the impact of regional cortical damage remains poorly understood. Our aim was to evaluate structural (network) integrity in lesional and non-lesional cortex in people with MS, and its relationship with cognitive dysfunction.

METHODS

In this cross-sectional study, 176 people with MS and 48 healthy controls underwent MRI, including double inversion recovery and diffusion-weighted scans, and neuropsychological assessment. Cortical integrity was assessed based on fractional anisotropy (FA) and mean diffusivity (MD) within 212 regions split into lesional or non-lesional cortex, and grouped into seven cortical networks. Integrity was compared between people with MS and controls, and across cognitive groups: cognitively-impaired (CI; ≥ two domains at Z ≤ - 2 below controls), mildly CI (≥ two at - 2 < Z ≤ - 1.5), or cognitively-preserved (CP).

RESULTS

Cortical lesions were observed in 87.5% of people with MS, mainly in ventral attention network, followed by limbic and default mode networks. Compared to controls, in non-lesional cortex, MD was increased in people with MS, but mean FA did not differ. Within the same individual, MD and FA were increased in lesional compared to non-lesional cortex. CI-MS exhibited higher MD than CP-MS in non-lesional cortex of default mode, frontoparietal and sensorimotor networks, of which the default mode network could best explain cognitive performance.

CONCLUSION

Diffusion differences in lesional cortex were more severe than in non-lesional cortex. However, while most people with MS had cortical lesions, diffusion differences in CI-MS were more prominent in non-lesional cortex than lesional cortex, especially within default mode, frontoparietal and sensorimotor networks.

Cortical Macro- and Microstructural Changes in Parkinson's Disease with Probable Rapid Eye Movement Sleep Behavior Disorder

BACKGROUND

Evidence regarding cortical atrophy patterns in Parkinson's disease (PD) with probable rapid eye movement sleep behavior disorder (RBD) (PD-pRBD) remains scarce. Cortical mean diffusivity (cMD), as a novel imaging biomarker highly sensitive to detecting cortical microstructural changes in different neurodegenerative diseases, has not been investigated in PD-pRBD yet.

OBJECTIVES

The aim was to investigate cMD as a sensitive measure to identify subtle cortical microstructural changes in PD-pRBD and its relationship with cortical thickness (CTh).

METHODS

Twenty-two PD-pRBD, 31 PD without probable RBD (PD-nonpRBD), and 28 healthy controls (HC) were assessed using 3D T1-weighted and diffusion-weighted magnetic resonance imaging on a 3-T scanner and neuropsychological testing. Measures of cortical brain changes were obtained through cMD and CTh. Two-class group comparisons of a general linear model were performed (P < 0.05). Cohen's d effect size for both approaches was computed.

RESULTS

PD-pRBD patients showed higher cMD than PD-nonpRBD patients in the left superior temporal, superior frontal, and precentral gyri, precuneus cortex, as well as in the right middle frontal and postcentral gyri and paracentral lobule (d > 0.8), whereas CTh did not detect significant differences. PD-pRBD patients also showed increased bilateral posterior cMD in comparison with HCs (d > 0.8). These results partially overlapped with CTh results (0.5 < d < 0.8). PD-nonpRBD patients showed no differences in cMD when compared with HCs but showed cortical thinning in the left fusiform gyrus and lateral occipital cortex bilaterally (d > 0.5).

CONCLUSIONS

cMD may be more sensitive than CTh displaying significant cortico-structural differences between PD subgroups, indicating this imaging biomarker's utility in studying early cortical changes in PD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Predicting disease severity in multiple sclerosis using multimodal data and machine learning

BACKGROUND

Multiple sclerosis patients would benefit from machine learning algorithms that integrates clinical, imaging and multimodal biomarkers to define the risk of disease activity.

METHODS

We have analysed a prospective multi-centric cohort of 322 MS patients and 98 healthy controls from four MS centres, collecting disability scales at baseline and 2 years later. Imaging data included brain MRI and optical coherence tomography, and omics included genotyping, cytomics and phosphoproteomic data from peripheral blood mononuclear cells. Predictors of clinical outcomes were searched using Random Forest algorithms. Assessment of the algorithm performance was conducted in an independent prospective cohort of 271 MS patients from a single centre.

RESULTS

We found algorithms for predicting confirmed disability accumulation for the different scales, no evidence of disease activity (NEDA), onset of immunotherapy and the escalation from low- to high-efficacy therapy with intermediate to high-accuracy. This accuracy was achieved for most of the predictors using clinical data alone or in combination with imaging data. Still, in some cases, the addition of omics data slightly increased algorithm performance. Accuracies were comparable in both cohorts.

CONCLUSION

Combining clinical, imaging and omics data with machine learning helps identify MS patients at risk of disability worsening.

Causal relationship between multiple sclerosis and cortical structure: a Mendelian randomization study

BACKGROUND

Observational studies have suggested an association between multiple sclerosis (MS) and cortical structure, but the results have been inconsistent.

OBJECTIVE

We used two-sample Mendelian randomization (MR) to assess the causal relationship between MS and cortical structure.

METHODS

MS data as the exposure trait, including 14,498 cases and 24,091 controls, were obtained from the International Multiple Sclerosis Genetics Consortium. Genome-wide association study (GWAS) data for cortical surface area (SAw/nw) and thickness (THw/nw) in 51,665 individuals of European ancestry were obtained from the ENIGMA Consortium. The inverse-variance weighted (IVW) method was used as the primary analysis for MR. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Enrichment analysis was performed on MR analyses filtered by sensitivity analysis.

RESULTS

After IVW and sensitivity analysis filtering, only six surviving MR results provided suggestive evidence supporting a causal relationship between MS and cortical structure, including lingual SAw (p = .0342, beta (se) = 5.7127 (2.6969)), parahippocampal SAw (p = .0224, beta (se) = 1.5577 (0.6822)), rostral middle frontal SAw (p = .0154, beta (se) = - 9.0301 (3.7281)), cuneus THw (p = .0418, beta (se) =  - 0.0020 (0.0010)), lateral orbitofrontal THw (p = .0281, beta (se) = 0.0025 (0.0010)), and lateral orbitofrontal THnw (p = .0417, beta (se) = 0.0029 (0.0014)). Enrichment analysis suggested that leukocyte cell-related pathways, JAK-STAT signaling pathway, NF-kappa B signaling pathway, cytokine-cytokine receptor interaction, and prolactin signaling pathway may be involved in the effect of MS on cortical morphology.

CONCLUSION

Our results provide evidence supporting a causal relationship between MS and cortical structure. Enrichment analysis suggests that the pathways mediating brain morphology abnormalities in MS patients are mainly related to immune and inflammation-driven pathways.

Neuroimaging to monitor worsening of multiple sclerosis: advances supported by the grant for multiple sclerosis innovation

Key unmet needs in multiple sclerosis (MS) include detection of early pathology, disability worsening independent of relapses, and accurate monitoring of treatment response. Collaborative approaches to address these unmet needs have been driven in part by industry-academic networks and initiatives such as the Grant for Multiple Sclerosis Innovation (GMSI) and Multiple Sclerosis Leadership and Innovation Network (MS-LINK™) programs. We review the application of recent advances, supported by the GMSI and MS-LINK™ programs, in neuroimaging technology to quantify pathology related to central pathology and disease worsening, and potential for their translation into clinical practice/trials. GMSI-supported advances in neuroimaging methods and biomarkers include developments in magnetic resonance imaging, positron emission tomography, ocular imaging, and machine learning. However, longitudinal studies are required to facilitate translation of these measures to the clinic and to justify their inclusion as endpoints in clinical trials of new therapeutics for MS. Novel neuroimaging measures and other biomarkers, combined with artificial intelligence, may enable accurate prediction and monitoring of MS worsening in the clinic, and may also be used as endpoints in clinical trials of new therapies for MS targeting relapse-independent disease pathology.

Symmetry differences of structural connectivity in multiple sclerosis and healthy state

Focal and diffuse cerebral damages occur in Multiple Sclerosis (MS) that promotes profound shifts in local and global structural connectivity parameters, mainly derived from diffusion tensor imaging. Most of the reconstruction analyses have applied conventional tracking algorithms largely based on the controversial streamline count. For a more credible explanation of the diffusion MRI signal, we used convex optimization modeling for the microstructure-informed tractography2 (COMMIT2) framework. All multi-shell diffusion data from 40 healthy controls (HCs) and 40 relapsing-remitting MS (RRMS) patients were transformed into COMMIT2-weighted matrices based on the Schefer-200 parcels atlas (7 networks) and 14 bilateral subcortical regions. The success of the classification process between MS and healthy state was efficiently predicted by the left DMN-related structures and visual network-associated pathways. Additionally, the lesion volume and age of onset were remarkably correlated with the components of the left DMN. Using complementary approaches such as global metrics revealed differences in WM microstructural integrity between MS and HCs (efficiency, strength). Our findings demonstrated that the cutting-edge diffusion MRI biomarkers could hold the potential for interpreting brain abnormalities in a more distinctive way.

Voluntary muscle activation in people with multiple sclerosis is reduced across a wide range of forces following maximal effort-fatiguing contractions

Although multiple sclerosis (MS) is frequently associated with motor impairment, little is known about how muscle activation is affected with MS. The aim of this study was to use transcranial magnetic stimulation (TMS) and motor nerve stimulation to investigate voluntary muscle activation in people with MS across a range of contraction forces. Ten people with MS (39 ± 7 yr) and 10 healthy controls (40 ± 5 yr) performed elbow flexions at target contraction forces of 25%, 50%, 75%, 90%, and 100% maximal voluntary contraction (MVC) while electromyography (EMG) of the biceps brachii was recorded. Sustained elbow flexion MVCs were then performed until force declined to 60% of baseline MVC, where the target contraction forces were again examined but after the sustained MVC. Following the sustained MVC, there was a reduction in biceps EMG amplitude (P < 0.01) and motor cortical voluntary activation (P < 0.01) for the MS group across all contraction intensities. There was also an increase in the rate of torque development for motor nerve-resting twitches in the MS group following the sustained MVC (P = 0.03). Despite the MS group reporting higher fatigue severity scale scores (P < 0.01), disease duration was a better predictor of muscle activation for the MS group (r = -0.757, P = 0.01). These findings indicate that voluntary muscle activation is compromised in people with MS following maximal effort contractions, which may be associated with disease duration rather than self-reports of fatigue.NEW & NOTEWORTHY We use transcranial magnetic stimulation to demonstrate that people with relapsing-remitting multiple sclerosis (MS) have a reduced ability to activate muscles following maximal effort-fatiguing contractions. A reduced ability to activate the elbow flexor muscles after a fatiguing contraction was associated with disease duration and not self-reported levels of fatigue.

Multimodal Investigation of Deep Gray Matter Nucleus in Patients with Multiple Sclerosis and Their Clinical Correlations: A Multivariate Pattern Analysis Study

Deep gray matter (DGM) nucleus are involved in patients with multiple sclerosis (MS) and are strongly associated with clinical symptoms. We used machine learning approach to further explore microstructural alterations in DGM of MS patients. One hundred and fifteen MS patients and seventy-one healthy controls (HC) underwent brain MRI. The fractional anisotropy (FA), mean diffusivity (MD), quantitative susceptibility value (QSV) and volumes of the caudate nucleus (CN), putamen (PT), globus pallidus (GP), and thalamus (TH) were measured. Multivariate pattern analysis, based on a machine-learning algorithm, was applied to investigate the most damaged regions. Partial correlation analysis was used to investigate the correlation between MRI quantitative metrics and clinical neurological scores. The area under the curve of FA-based classification model was 0.83, while they were 0.93 for MD and 0.81 for QSV. The Montreal cognitive assessment scores were correlated with the volume of the DGM and the expanded disability status scale scores were correlated with the MD of the GP and PT. The study results indicated that MS patients had involvement of DGM with the CN being the most affected. The atrophy of DGM in MS patients mainly affected cognitive function and the microstructural damage of DGM was mainly correlated with clinical disability.

Detection of grey matter microstructural substrates of neurodegeneration in multiple sclerosis

Multiple sclerosis features complex pathological changes in grey matter that begin early and eventually lead to diffuse atrophy. Novel approaches to image grey-matter microstructural alterations in vivo are highly sought after and would enable more sensitive monitoring of disease activity and progression. This cross-sectional study aimed to assess the sensitivity of high-gradient diffusion MRI for microstructural tissue damage in cortical and deep grey matter in people with multiple sclerosis and test the hypothesis that reduced cortical cell body density is associated with cortical and deep grey-matter volume loss. Forty-one people with multiple sclerosis (age 24-72, 14 females) and 37 age- and sex-matched healthy controls were scanned on a 3 T Connectom MRI scanner equipped with 300 mT/m gradients using a multi-shell diffusion MRI protocol. The soma and neurite density imaging model was fitted to high-gradient diffusion MRI data to obtain estimates of intra-neurite, intra-cellular and extra-cellular signal fractions and apparent soma radius. Cortical and deep grey-matter microstructural imaging metrics were compared between multiple sclerosis and healthy controls and correlated with grey-matter volume, clinical disability and cognitive outcomes. People with multiple sclerosis showed significant cortical and deep grey-matter volume loss compared with healthy controls. People with multiple sclerosis showed trends towards lower cortical intra-cellular signal fraction and significantly lower intra-cellular and higher extra-cellular signal fractions in deep grey matter, especially the thalamus and caudate, compared with healthy controls. Changes were most pronounced in progressive disease and correlated with the Expanded Disability Status Scale, but not the Symbol Digit Modalities Test. In multiple sclerosis, normalized thalamic volume was associated with thalamic microstructural imaging metrics. Whereas thalamic volume loss did not correlate with cortical volume loss, cortical microstructural imaging metrics were significantly associated with thalamic volume, and not with cortical volume. Compared with the short diffusion time (Δ = 19 ms) achievable on the Connectom scanner, at the longer diffusion time of Δ = 49 ms attainable on clinical scanners, multiple sclerosis-related changes in imaging metrics were generally less apparent with lower effect sizes in cortical and deep grey matter. Soma and neurite density imaging metrics obtained from high-gradient diffusion MRI data provide detailed grey-matter characterization beyond cortical and thalamic volumes and distinguish multiple sclerosis-related microstructural pathology from healthy controls. Cortical cell body density correlates with thalamic volume, appears sensitive to the microstructural substrate of neurodegeneration and reflects disability status in people with multiple sclerosis, becoming more pronounced as disability worsens.

Neuroimmune, clinical and treatment challenges in multiple sclerosis-related psychoses

In recent years, epidemiological and genetic studies have shown an association between autoimmune diseases and psychosis. The question arises whether patients with schizophrenia are more likely to develop multiple sclerosis (MS) later in life. It is well known that the immune system plays an important role in the etiopathogenesis of both disorders. Immune disturbances may be similar or very different in terms of different types of immune responses, disturbed myelination, and/or immunogenetic predispositions. A psychotic symptom may be a consequence of the MS diagnosis itself or a separate entity. In this review article, we discussed the timing of onset of psychotic symptoms and MS and whether the use of corticosteroids as therapy for acute relapses in MS is unfairly neglected in patients with psychiatric comorbidities. In addition, we discussed that the anti-inflammatory potential of antipsychotics could be useful and should be considered, especially in the treatment of psychosis that coexists with MS. Autoimmune disorders could precipitate psychotic symptoms, and in this context, autoimmune psychosis must be considered as a persistent symptomatology that requires continuous and specific treatment.

Diffusion tensor imaging metrics associated with future disability in multiple sclerosis

The relationship between brain diffusion microstructural changes and disability in multiple sclerosis (MS) remains poorly understood. We aimed to explore the predictive value of microstructural properties in white (WM) and grey matter (GM), and identify areas associated with mid-term disability in MS patients. We studied 185 patients (71% female; 86% RRMS) with the Expanded Disability Status Scale (EDSS), timed 25-foot walk (T25FW), nine-hole peg test (9HPT), and Symbol Digit Modalities Test (SDMT) at two time-points. We used Lasso regression to analyse the predictive value of baseline WM fractional anisotropy and GM mean diffusivity, and to identify areas related to each outcome at 4.1 years follow-up. Motor performance was associated with WM (T25FW: RMSE = 0.524, R² = 0.304; 9HPT dominant hand: RMSE = 0.662, R² = 0.062; 9HPT non-dominant hand: RMSE = 0.649, R² = 0.139), and SDMT with GM diffusion metrics (RMSE = 0.772, R² = 0.186). Cingulum, longitudinal fasciculus, optic radiation, forceps minor and frontal aslant were the WM tracts most closely linked to motor dysfunction, and temporal and frontal cortex were relevant for cognition. Regional specificity related to clinical outcomes provide valuable information that can be used to develop more accurate predictive models that could improve therapeutic strategies.

Synapse Dysfunctions in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic neuroinflammatory disease of the central nervous system (CNS) affecting nearly three million humans worldwide. In MS, cells of an auto-reactive immune system invade the brain and cause neuroinflammation. Neuroinflammation triggers a complex, multi-faceted harmful process not only in the white matter but also in the grey matter of the brain. In the grey matter, neuroinflammation causes synapse dysfunctions. Synapse dysfunctions in MS occur early and independent from white matter demyelination and are likely correlates of cognitive and mental symptoms in MS. Disturbed synapse/glia interactions and elevated neuroinflammatory signals play a central role. Glutamatergic excitotoxic synapse damage emerges as a major mechanism. We review synapse/glia communication under normal conditions and summarize how this communication becomes malfunctional during neuroinflammation in MS. We discuss mechanisms of how disturbed glia/synapse communication can lead to synapse dysfunctions, signaling dysbalance, and neurodegeneration in MS.

Changes in diffusion tensor imaging indices in basal ganglia and thalamus of patients with Relapsing-Remitting Multiple Sclerosis and relation with clinical conditions: A case-control study

Background

Multiple sclerosis (MS) is recognized as the most prevalent autoimmune abnormality of the CNS. T1WI, T2WI, and FLAIR are limited in the quantification of tissue damage and detection of tissue alterations in white and grey matter in MS. This study aimed to the evaluation of changes in DTI indices in these patients at the thalamus and basal ganglia.

Methods

30 relapsing-remitting MS (RRMS) cases and 30 normal individuals were included. Conventional MRI (T2, FLAIR) was acquired to confirm NAGM in MS patients. A T1 MPRAGE protocol was used to normalize DTI images. FSL, SPM, and Explore DTI software were employed to reach Mean Diffusivities (MD), Axial Diffusivities (AD), Fractional anisotropy (FA), and Radial Diffusivity (RD) at the thalamus and the basal ganglia.

Results

The FA and RD of the thalamus were decreased in healthy controls compared to MS cases (0.319 vs. 0.296 and 0.0009 vs. 0.0006, respectively) (P < 0.05). The AD value in the thalamus and the FA value in the caudate nucleus were significantly lower in MS cases than in controls (0.0009 vs. 0.0011 and 0.16 vs. 0.18, respectively) (P < 0.05). MD values in the thalamus or basal ganglia were not significantly different between groups.

Conclusions

DTI measures including FA, RD, and AD have a good diagnostic performance in detecting microstructural changes in the normal-appearing thalamus in cases with RRMS while they had no significant relationship with clinical signs in terms of EDSS.

Availability of data and material

Not applicable.

Applying multilayer analysis to morphological, structural, and functional brain networks to identify relevant dysfunction patterns

In recent years, research on network analysis applied to MRI data has advanced significantly. However, the majority of the studies are limited to single networks obtained from resting-state fMRI, diffusion MRI, or gray matter probability maps derived from T1 images. Although a limited number of previous studies have combined two of these networks, none have introduced a framework to combine morphological, structural, and functional brain connectivity networks. The aim of this study was to combine the morphological, structural, and functional information, thus defining a new multilayer network perspective. This has proved advantageous when jointly analyzing multiple types of relational data from the same objects simultaneously using graph- mining techniques. The main contribution of this research is the design, development, and validation of a framework that merges these three layers of information into one multilayer network that links and relates the integrity of white matter connections with gray matter probability maps and resting-state fMRI. To validate our framework, several metrics from graph theory are expanded and adapted to our specific domain characteristics. This proof of concept was applied to a cohort of people with multiple sclerosis, and results show that several brain regions with a synchronized connectivity deterioration could be identified.

Association of Lesion Location and Fatigue Symptoms After Ischemic Stroke: A VLSM Study

Background:

Poststroke fatigue (PSF) is a common symptom in stroke survivors, yet its anatomical mechanism is unclear. Our study was aimed to identify which brain lesions are related to the PSF in patients with acute stroke.

Method

Patients with first-ever acute ischemic stroke consecutively admitted from the first affiliated hospital of the University of Science and Technology of China (USTC) between January 2017 and June 2020. Fatigue was scored using the Fatigue Severity Scale. All the participants were assessed by 3.0 T brain MRI including diffusion-weighted imaging. The infarct lesions were delineated manually and transformed into a standard template. Voxel-based lesion-symptom mapping (VLSM) was applied to investigate the association between lesion location and the occurrence and severity of fatigue. The same analyses were carried out by flipping the left-sided lesions. Multivariate logistic regressions were applied to verify the associations.

Results

Of the 361 patients with acute stroke, 142 (39.3%) patients were diagnosed with fatigue in the acute phase and 116 (35.8%) at 6 months after the index stroke. VLSM analysis indicated clusters in the right thalamus which was significantly associated with the occurrence and severity of PSF at 6-month follow-up. In contrast, no significant cluster was found in the acute phase of stroke. The flipped analysis did not alter the results. Multivariate logistic regression verified that lesion load in the right thalamus (OR 2.67, 95% CI 1.46–4.88) was an independent predictor of 6-month PSF.

Conclusion

Our findings indicated that lesions in the right thalamus increased the risk of fatigue symptoms 6 months poststroke.

Intracortical surface-based MR diffusivity to investigate neurologic and psychiatric disorders: a review

Diffusion tensor imaging (DTI) allows the quantification of water diffusivity within the cerebral cortex. Alterations in cortical mean diffusivity (MD) have been suggested to reflect microstructural damage. Interestingly, microstructural changes can be detected in the absence of macrostructural alterations such as cortical thinning or gray matter volume loss. However, volume-based neuroimaging techniques for the study of cortical MD have shown some limitations in terms of intersubject registration, partial volume correction, and smoothing artifacts. In this review, we summarize how a surface-based approach for the assessment of intracortical MD has not only overcome these technical limitations, but also provided important contributions to the fields of neurology and psychiatry. Since its proposal in 2018, the use of this neuroimaging technique has revealed cortical microstructural alterations in a wide range of clinical contexts, including Alzheimer's disease, Parkinson's disease, schizophrenia, Huntington's disease, multiple sclerosis, amyotrophic lateral sclerosis, and primary progressive aphasia. In most cases, the detection of early intracortical MD alterations preceded the identification of macrostructural changes. Importantly, microstructural damage significantly correlated with cognitive performance and biomarker measures, suggesting a potential role for its use in clinical trials as a sensitive imaging marker of neurodegeneration. Given that DTI is a widely available imaging modality, these encouraging results motivate further research using this novel neuroimaging metric in other clinical contexts. Overall, this technique has shed light into the key role of early cortical degeneration in many diseases where cortical involvement was previously thought to have limited clinical and biological significance.