Search

Background: Cortical multiple sclerosis lesions are clinically relevant but inconspicuous at conventional clinical MRI. Double inversion recovery (DIR) and phase-sensitive inversion recovery (PSIR) are more sensitive but often unavailable. In the past 2 years, artificial intelligence (AI) was used to generate DIR and PSIR from standard clinical sequences (eg, T1-weighted, T2-weighted, and fluid-attenuated inversion-recovery sequences), but multicenter validation is crucial for further implementation. Purpose: To evaluate cortical and juxtacortical multiple sclerosis lesion detection for diagnostic and disease monitoring purposes on AI-generated DIR and PSIR images compared with MRI-acquired DIR and PSIR images in a multicenter setting. Materials and Methods: Generative adversarial networks were used to generate AI-based DIR (n = 50) and PSIR (n = 43) images. The number of detected lesions between AI-generated images and MRI-acquired (reference) images was compared by randomized blinded scoring by seven readers (all with >10 years of experience in lesion assessment). Reliability was expressed as the intraclass correlation coefficient (ICC). Differences in lesion subtype were determined using Wilcoxon signed-rank tests. Results: MRI scans of 202 patients with multiple sclerosis (mean age, 46 years ± 11 [SD]; 127 women) were retrospectively collected from seven centers (February 2020 to January 2021). In total, 1154 lesions were detected on AI-generated DIR images versus 855 on MRI-acquired DIR images (mean difference per reader, 35.0% ± 22.8; P < .001). On AI-generated PSIR images, 803 lesions were detected versus 814 on MRI-acquired PSIR images (98.9% ± 19.4; P = .87). Reliability was good for both DIR (ICC, 0.81) and PSIR (ICC, 0.75) across centers. Regionally, more juxtacortical lesions were detected on AI-generated DIR images than on MRI-acquired DIR images (495 [42.9%] vs 338 [39.5%]; P < .001). On AI-generated PSIR images, fewer juxtacortical lesions were detected than on MRI-acquired PSIR images (232 [28.9%] vs 282 [34.6%]; P = .02). Conclusion: Artificial intelligence–generated double inversion-recovery and phase-sensitive inversion-recovery images performed well compared with their MRI-acquired counterparts and can be considered reliable in a multicenter setting, with good between-reader and between-center interpretative agreement.

Multiple sclerosis (MS) features extensive connectivity changes, but how structural and functional connectivity relate, and whether this relation could be a useful biomarker for cognitive impairment in MS is unclear. This study included 79 MS patients and 40 healthy controls (HCs). Patients were classified as cognitively impaired (CI) or cognitively preserved (CP). Structural connectivity was determined using diffusion MRI and functional connectivity using resting-state magnetoencephalography (MEG) data (theta, alpha1, and alpha2 bands). Structure-function coupling was assessed by correlating modalities, and further explored in frequency bands that significantly correlated with whole-brain structural connectivity. Functional correlates of short- and long-range structural connections (based on tract length) were then specifically assessed. Receiving operating curve analyses were performed on coupling values to identify biomarker potential. Only the theta band showed significant correlations between whole-brain structural and functional connectivity (rho = −0.26, p = 0.023, only in MS). Long-range structure-function coupling was stronger in CI patients compared to HCs (p = 0.005). Short-range coupling showed no group differences. Structure-function coupling was not a significant classifier of cognitive impairment for any tract length (short-range area under the curve (AUC) = 0.498, p = 0.976, long-range AUC = 0.611, p = 0.095). Long-range structure-function coupling was stronger in CI MS compared to HCs, but more research is needed to further explore this measure as biomarkers in MS.

Cognitive impairment occurs in 40–65% of persons with multiple sclerosis and may be related to alterations in glutamatergic and GABAergic neurotransmission. Therefore, the aim of this study was to determine how glutamatergic and GABAergic changes relate to cognitive functioning in multiple sclerosis in vivo. Sixty persons with multiple sclerosis (mean age 45.5 ± 9.6 years, 48 females, 51 relapsing-remitting multiple sclerosis) and 22 age-matched healthy controls (45.6 ± 22.0 years, 17 females) underwent neuropsychological testing and MRI. Persons with multiple sclerosis were classified as cognitively impaired when scoring at least 1.5 standard deviations below normative scores on ≥30% of tests. Glutamate and GABA concentrations were determined in the right hippocampus and bilateral thalamus using magnetic resonance spectroscopy. GABA-receptor density was assessed using quantitative [11C]flumazenil positron emission tomography in a subset of participants. Positron emission tomography outcome measures were the influx rate constant (a measure predominantly reflecting perfusion) and volume of distribution, which is a measure of GABA-receptor density. Twenty persons with multiple sclerosis (33%) fulfilled the criteria for cognitive impairment. No differences were observed in glutamate or GABA concentrations between persons with multiple sclerosis and healthy controls, or between cognitively preserved, impaired and healthy control groups. Twenty-two persons with multiple sclerosis (12 cognitively preserved and 10 impaired) and 10 healthy controls successfully underwent [11C]flumazenil positron emission tomography. Persons with multiple sclerosis showed a lower influx rate constant in the thalamus, indicating lower perfusion. For the volume of distribution, persons with multiple sclerosis showed higher values than controls in deep grey matter, reflecting increased GABA-receptor density. When comparing cognitively impaired and preserved patients to controls, the preserved group showed a significantly higher volume of distribution in cortical and deep grey matter and hippocampus. Positive correlations were observed between both positron emission tomography measures and information processing speed in the multiple sclerosis group only. Whereas concentrations of glutamate and GABA did not differ between multiple sclerosis and control nor between cognitively impaired, preserved and control groups, increased GABA-receptor density was observed in preserved persons with multiple sclerosis that was not seen in cognitively impaired patients. In addition, GABA-receptor density correlated to cognition, in particular with information processing speed. This could indicate that GABA-receptor density is upregulated in the cognitively preserved phase of multiple sclerosis as a means to regulate neurotransmission and potentially preserve cognitive functioning.

Background Cognitive impairment in people with MS (PwMS) has primarily been investigated using conventional imaging markers or fluid biomarkers of neurodegeneration separately. However, the single use of these markers do only partially explain the large heterogeneity found in PwMS. Objective To investigate the use of multimodal (bio)markers: i.e., serum and cerebrospinal fluid (CSF) levels of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) and conventional imaging markers in predicting cognitive functioning in PwMS. Methods Eighty-two PwMS (56 females, disease duration = 14 ± 9 years) underwent neuropsychological and neurological examination, structural magnetic resonance imaging, blood sampling and lumbar puncture. PwMS were classified as cognitively impaired (CI) if scoring ≥ 1.5SD below normative scores on ≥ 20% of test scores. Otherwise, PwMS were defined as cognitively preserved (CP). Association between fluid and imaging (bio)markers were investigated, as well as binary logistics regression to predict cognitive status. Finally, a multimodal marker was calculated using statistically important predictors of cognitive status. Results Only higher NfL levels (in serum and CSF) correlated with worse processing speed (r = − 0.286, p = 0.012 and r = − 0.364, p = 0.007, respectively). sNfL added unique variance in the prediction of cognitive status on top of grey matter volume (NGMV), p = 0.002). A multimodal marker of NGMV and sNfL yielded most promising results in predicting cognitive status (sensitivity = 85%, specificity = 58%). Conclusion Fluid and imaging (bio)markers reflect different aspects of neurodegeneration and cannot be used interchangeably as markers for cognitive functioning in PwMS. The use of a multimodal marker, i.e., the combination of grey matter volume and sNfL, seems most promising for detecting cognitive deficits in MS.

Background and Objectives:In multiple sclerosis (MS), functional networks undergo continuous reconfiguration and topography changes over the disease course. Here, we aimed to investigate functional networks topography abnormalities in MS and their association with disease phenotype, clinical and cognitive disability, and structural MRI damage.Methods:This is a multi-centre cross-sectional study. Enrolled subjects performed MRI, neurological and neuropsychological assessment. Network topography was assessed on resting state fMRI data using degree centrality, which counted the number of functional connections of each grey matter voxel with the rest of the brain. SPM12 age-, sex-, scanner-, framewise displacement and grey matter volume adjusted ANOVA and multivariable regressions were employed (pResults:We enrolled 971 patients with MS (624 females; mean age=43.1 ±11.8 years; 47 clinically isolated syndrome [CIS], 704 relapsing-remitting [RRMS], 145 secondary progressive [SPMS] and 75 primary progressive [PPMS]) and 330 healthy controls (186 females; mean age=41.2 ± 13.3 years). Patients with MS showed reduced centrality in the salience and sensorimotor networks as well as increased centrality in the default mode network vs controls (pvs controls and in RRMS vs CIS (pvs RRMS (pvs controls (pvs cognitively preserved patients (pDiscussion:Patients with MS presented with reduced centrality in the salience and primary sensorimotor networks and increased centrality in the default mode network. Centrality abnormalities were specific for different disease phenotypes and associated with clinical and cognitive disability, hence suggesting that voxel-wise centrality analysis may reflect pathological substrates underpinning disability accrual.

Translational processes that facilitate effective interdisciplinary communication remain a ‘black box’. Here, we aimed to operationalize translational practices by combining conversation analysis and network science to analyze interdisciplinary research meetings. We applied conversation analysis to transcribed meetings, and identified chair, clarifying, skeptical, expert, connecting, and practical actions. For each meeting, we constructed a network (‘meetome’) with team members as nodes, and the number of consecutive speaking turns between members as links. We found that the relative occurrence of role-specific actions correlated with network measures. We discuss how awareness of interactional roles within meetings may help to implement a translational approach in interdisciplinary research teams.

Various post-translationally modified (PTM) proteoforms of alpha-synuclein (aSyn)—including C-terminally truncated (CTT) and Serine 129 phosphorylated (Ser129-p) aSyn—accumulate in Lewy bodies (LBs) in different regions of the Parkinson’s disease (PD) brain. Insight into the distribution of these proteoforms within LBs and subcellular compartments may aid in understanding the orchestration of Lewy pathology in PD. We applied epitope-specific antibodies against CTT and Ser129-p aSyn proteoforms and different aSyn domains in immunohistochemical multiple labelings on post-mortem brain tissue from PD patients and non-neurological, aged controls, which were scanned using high-resolution 3D multicolor confocal and stimulated emission depletion (STED) microscopy. Our multiple labeling setup highlighted a consistent onion skin-type 3D architecture in mature nigral LBs in which an intricate and structured-appearing framework of Ser129-p aSyn and cytoskeletal elements encapsulates a core enriched in CTT aSyn species. By label-free CARS microscopy we found that enrichments of proteins and lipids were mainly localized to the central portion of nigral aSyn-immunopositive (aSyn+) inclusions. Outside LBs, we observed that 122CTT aSyn+ punctae localized at mitochondrial membranes in the cytoplasm of neurons in PD and control brains, suggesting a physiological role for 122CTT aSyn outside of LBs. In contrast, very limited to no Ser129-p aSyn immunoreactivity was observed in brains of non-neurological controls, while the alignment of Ser129-p aSyn in a neuronal cytoplasmic network was characteristic for brains with (incidental) LB disease. Interestingly, Ser129-p aSyn+ network profiles were not only observed in neurons containing LBs but also in neurons without LBs particularly in donors at early disease stage, pointing towards a possible subcellular pathological phenotype preceding LB formation. Together, our high-resolution and 3D multicolor microscopy observations in the post-mortem human brain provide insights into potential mechanisms underlying a regulated LB morphogenesis. Supplementary Information The online version contains supplementary material available at 10.1007/s00401-021-02329-9.

The neuroinflammatory disease multiple sclerosis is driven by autoimmune pathology in the central nervous system. However, the trigger of the autoimmune pathogenic process is unknown. MS models in immunologically naïve, specific‐pathogen‐free bred rodents support an exogenous trigger, such as an infection. The validity of this outside–in pathogenic concept for MS has been frequently challenged by the difficulty to translate pathogenic concepts developed in these models into effective therapies for the MS patient. Studies in well‐validated non‐human primate multiple sclerosis models where, just like in humans, the autoimmune pathogenic process develops from an experienced immune system trained by prior infections, rather support an endogenous trigger. Data reviewed here corroborate the validity of this inside–out pathogenic concept for multiple sclerosis. They also provide a plausible sequence of events reminiscent of Wilkin’s primary lesion theory: (i) that autoimmunity is a physiological response of the immune system against excess antigen turnover in diseased tissue (the primary lesion) and (ii) that individuals developing autoimmune disease are (genetically predisposed) high responders against critical antigens. Data obtained in multiple sclerosis brains reveal the presence in normally appearing white matter of myelinated axons where myelin sheaths have locally dissociated from their enwrapped axon (i.e., blistering). The ensuing disintegration of axon–myelin units potentially causes the excess systemic release of post‐translationally modified myelin. Data obtained in a unique primate multiple sclerosis model revealed a core pathogenic role of T cells present in the normal repertoire, which hyper‐react to post‐translationally modified (citrullinated) myelin–oligodendrocyte glycoprotein and evoke clinical and pathological aspects of multiple sclerosis.

Quantitative MRI provides biophysical measures of the microstructural integrity of the CNS, which can be compared across CNS regions, patients, and centres. In patients with multiple sclerosis, quantitative MRI techniques such as relaxometry, myelin imaging, magnetization transfer, diffusion MRI, quantitative susceptibility mapping, and perfusion MRI, complement conventional MRI techniques by providing insight into disease mechanisms. These include: (i) presence and extent of diffuse damage in CNS tissue outside lesions (normal-appearing tissue); (ii) heterogeneity of damage and repair in focal lesions; and (iii) specific damage to CNS tissue components. This review summarizes recent technical advances in quantitative MRI, existing pathological validation of quantitative MRI techniques, and emerging applications of quantitative MRI to patients with multiple sclerosis in both research and clinical settings. The current level of clinical maturity of each quantitative MRI technique, especially regarding its integration into clinical routine, is discussed. We aim to provide a better understanding of how quantitative MRI may help clinical practice by improving stratification of patients with multiple sclerosis, and assessment of disease progression, and evaluation of treatment response., Quantitative MRI techniques provide biophysical measures of the microstructural integrity of the CNS. Granziera et al. review the information provided by qMRI in the field of multiple sclerosis research and the potential for translation of qMRI techniques into clinical practice.

Objective Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease of unknown etiology. Although the prevalent view regards a CD4+ -lymphocyte autoimmune reaction against myelin at the root of the disease, recent studies propose autoimmunity as a secondary reaction to idiopathic brain damage. To gain knowledge about this possibility we investigated the presence of axonal and myelinic morphological alterations which could implicate imbalance of axon-myelin units as primary event in MS pathogenesis. Methods Using high resolution imaging histological brain specimens from MS patients and non-neurological/non-MS controls, we explored molecular changes underpinning imbalanced interaction between axon and myelin in normal appearing white matter (NAWM), a region characterized by normal myelination and absent inflammatory activity. Results In MS brains, we detected blister-like swellings formed by myelin detachment from axons, which were substantially less frequently retrieved in non-neurological/non-MS controls. Swellings in MS NAWM presented altered glutamate receptor expression, myelin associated glycoprotein (MAG) distribution and lipid biochemical composition of myelin sheaths. Changes in tethering protein expression, widening of nodes of Ranvier and altered distribution of sodium channels in nodal regions of otherwise normally myelinated axons were also present in MS NAWM. Finally, we demonstrate a significant increase, compared with controls, in citrullinated proteins in myelin of MS cases, pointing toward biochemical modifications that may amplify the immunogenicity of MS myelin. Interpretation Collectively, the impaired interaction of myelin and axons potentially leads to myelin disintegration. Conceptually, the ensuing release of (post-translationally modified) myelin antigens may elicit a subsequent immune attack in MS. This article is protected by copyright. All rights reserved.

Temporal lobe epilepsy (TLE) patients are at risk of memory deficits, which have been linked to functional network disturbances, particularly of integration of the default mode network (DMN). However, the cellular substrates of functional network integration are unknown. We leverage a unique cross-scale dataset of drug-resistant TLE patients (n = 31), who underwent pseudo resting-state functional magnetic resonance imaging (fMRI), resting-state magnetoencephalography (MEG) and/or neuropsychological testing before neurosurgery. fMRI and MEG underwent atlas-based connectivity analyses. Functional network centrality of the lateral middle temporal gyrus, part of the DMN, was used as a measure of local network integration. Subsequently, non-pathological cortical tissue from this region was used for single cell morphological and electrophysiological patch-clamp analysis, assessing integration in terms of total dendritic length and action potential rise speed. As could be hypothesized, greater network centrality related to better memory performance. Moreover, greater network centrality correlated with more integrative properties at the cellular level across patients. We conclude that individual differences in cognitively relevant functional network integration of a DMN region are mirrored by differences in cellular integrative properties of this region in TLE patients. These findings connect previously separate scales of investigation, increasing translational insight into focal pathology and large-scale network disturbances in TLE.

Background: Cognitive decline remains difficult to predict as structural brain damage cannot fully explain the extensive heterogeneity found between MS patients. Objective: To investigate whether functional brain network organization measured with magnetoencephalography (MEG) predicts cognitive decline in MS patients after 5 years and to explore its value beyond structural pathology. Methods: Resting-state MEG recordings, structural MRI, and neuropsychological assessments were analyzed of 146 MS patients, and 100 patients had a 5-year follow-up neuropsychological assessment. Network properties of the minimum spanning tree (i.e. backbone of the functional brain network) indicating network integration and overload were related to baseline and longitudinal cognition, correcting for structural damage. Results: A more integrated beta band network (i.e. smaller diameter) and a less integrated delta band network (i.e. lower leaf fraction) predicted cognitive decline after 5 years ([Formula: see text]), independent of structural damage. Cross-sectional analyses showed that a less integrated network (e.g. lower tree hierarchy) related to worse cognition, independent of frequency band. Conclusions: The level of functional brain network integration was an independent predictive marker of cognitive decline, in addition to the severity of structural damage. This work thereby indicates the promise of MEG-derived network measures in predicting disease progression in MS.

Background: Network abnormalities could help explain physical disability in multiple sclerosis (MS), which remains poorly understood. Objective: This study investigates functional network efficiency changes in the sensorimotor system. Methods: We included 222 MS patients, divided into low disability (LD, Expanded Disability Status Scale (EDSS) ⩽3.5, n = 185) and high disability (HD, EDSS ⩾6, n = 37), and 82 healthy controls (HC). Functional connectivity was assessed between 23 sensorimotor regions. Measures of efficiency were computed and compared between groups using general linear models corrected for age and sex. Binary logistic regression models related disability status to local functional network efficiency (LE), brain volumes and demographics. Functional connectivity patterns of regions important for disability were explored. Results: HD patients demonstrated significantly higher LE of the left primary somatosensory cortex (S1) and right pallidum compared to LD and HC, and left premotor cortex compared to HC only. The logistic regression model for disability ( R2 = 0.38) included age, deep grey matter volume and left S1 LE. S1 functional connectivity was increased with prefrontal and secondary sensory areas in HD patients, compared to LD and HC. Conclusion: Clinical disability in MS associates with functional sensorimotor increases in efficiency and connectivity, centred around S1, independent of structural damage.

Background: Neuroaxonal degeneration is one of the hallmarks of clinical deterioration in progressive multiple sclerosis (PMS). Objective: To elucidate the association between neuroaxonal degeneration and both local cortical and connected white matter (WM) tract pathology in PMS. Methods: Post-mortem in situ 3T magnetic resonance imaging (MRI) and cortical tissue blocks were collected from 16 PMS donors and 10 controls. Cortical neuroaxonal, myelin, and microglia densities were quantified histopathologically. From diffusion tensor MRI, fractional anisotropy, axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) were quantified in normal-appearing white matter (NAWM) and white matter lesions (WML) of WM tracts connected to dissected cortical regions. Between-group differences and within-group associations were investigated through linear mixed models. Results: The PMS donors displayed significant axonal loss in both demyelinated and normal-appearing (NA) cortices ( p Conclusion: Reduced integrity of connected WM tracts and cortical demyelination both contribute to cortical axonal loss in PMS.

van Wageningen et al. present gene expression data of demyelinated and normal-appearing white and grey matter of multiple sclerosis leucocortical lesions. They find that grey matter lesions primarily feature gene expression indicative of a microglial response while white matter lesions feature astrocytic activation and dystrophic neurons.Demyelination of the central nervous system is a prominent pathological hallmark of multiple sclerosis and affects both white and grey matter. However, demyelinated white and grey matter exhibit clear pathological differences, most notably the presence or absence of inflammation and activated glial cells in white and grey matter, respectively. In order to gain more insight into the differential pathology of demyelinated white and grey matter areas, we micro-dissected neighbouring white and grey matter demyelinated areas as well as normal-appearing matter from leucocortical lesions of human post-mortem material and used these samples for RNA sequencing. Our data show that even neighbouring demyelinated white and grey matter of the same leucocortical have a distinct gene expression profile and cellular composition. We propose that, based on their distinct expression profile, pathological processes in neighbouring white and grey matter are likely different which could have implications for the efficacy of treating grey matter lesions with current anti-inflammatory-based multiple sclerosis drugs.

It is unclear why exactly gliomas show preferential occurrence in certain brain areas. Increased spiking activity around gliomas leads to faster tumour growth in animal models, while higher non-invasively measured brain activity is related to shorter survival in patients. However, it is unknown how regional intrinsic brain activity, as measured in healthy controls, relates to glioma occurrence. We first investigated whether gliomas occur more frequently in regions with intrinsically higher brain activity. Second, we explored whether intrinsic cortical activity at individual patients’ tumour locations relates to tumour and patient characteristics. Across three cross-sectional cohorts, 413 patients were included. Individual tumour masks were created. Intrinsic regional brain activity was assessed through resting-state magnetoencephalography acquired in healthy controls and source-localized to 210 cortical brain regions. Brain activity was operationalized as: (i) broadband power; and (ii) offset of the aperiodic component of the power spectrum, which both reflect neuronal spiking of the underlying neuronal population. We additionally assessed (iii) the slope of the aperiodic component of the power spectrum, which is thought to reflect the neuronal excitation/inhibition ratio. First, correlation coefficients were calculated between group-level regional glioma occurrence, as obtained by concatenating tumour masks across patients, and group-averaged regional intrinsic brain activity. Second, intrinsic brain activity at specific tumour locations was calculated by overlaying patients’ individual tumour masks with regional intrinsic brain activity of the controls and was associated with tumour and patient characteristics. As proposed, glioma preferentially occurred in brain regions characterized by higher intrinsic brain activity in controls as reflected by higher offset. Second, intrinsic brain activity at patients’ individual tumour locations differed according to glioma subtype and performance status: the most malignant isocitrate dehydrogenase-wild-type glioblastoma patients had the lowest excitation/inhibition ratio at their individual tumour locations as compared to isocitrate dehydrogenase-mutant, 1p/19q-codeleted glioma patients, while a lower excitation/inhibition ratio related to poorer Karnofsky Performance Status, particularly in codeleted glioma patients. In conclusion, gliomas more frequently occur in cortical brain regions with intrinsically higher activity levels, suggesting that more active regions are more vulnerable to glioma development. Moreover, indices of healthy, intrinsic excitation/inhibition ratio at patients’ individual tumour locations may capture both tumour biology and patients’ performance status. These findings contribute to our understanding of the complex and bidirectional relationship between normal brain functioning and glioma growth, which is at the core of the relatively new field of ‘cancer neuroscience’.

Background: Thalamic atrophy is proposed to be a major predictor of disability progression in multiple sclerosis (MS), while thalamic function remains understudied. Objectives: To study how thalamic functional connectivity (FC) is related to disability and thalamic or cortical network atrophy in two large MS cohorts. Methods: Structural and resting-state functional magnetic resonance imaging (fMRI) was obtained in 673 subjects from Amsterdam (MS: N = 332, healthy controls (HC): N = 96) and Graz (MS: N = 180, HC: N = 65) with comparable protocols, including disability measurements in MS (Expanded Disability Status Scale, EDSS). Atrophy was measured for the thalamus and seven well-recognized resting-state networks. Static and dynamic thalamic FC with these networks was correlated with disability. Significant correlates were included in a backward multivariate regression model. Results: Disability was most strongly related (adjusted R2 = 0.57, p Conclusion: The severity of disability in MS was related to increased static thalamic FC with the SMN. Thalamic FC changes were only related to cortical network atrophy, but not to thalamic atrophy.

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

Background: Suboptimal performance during neuropsychological assessment renders cognitive test results invalid. However, suboptimal performance has rarely been investigated in multiple sclerosis (MS). Objectives: To investigate potential underlying mechanisms of suboptimal performance in MS. Methods: Performance validity testing, neuropsychological assessments, neuroimaging, and questionnaires were analyzed in 99 MS outpatients with cognitive complaints. Based on performance validity testing patients were classified as valid or invalid performers, and based on neuropsychological test results as cognitively impaired or preserved. Group comparisons and correlational analyses were performed on demographics, patient-reported, and disease-related outcomes. Results: Twenty percent displayed invalid performance. Invalid and valid performers did not differ regarding demographic, patient-reported, and disease-related outcomes. Disease severity of invalid and valid performers with cognitive impairment was comparable, but worse than cognitively preserved valid performers. Lower performance validity scores related to lower cognitive functioning, lower education, being male, and higher disability levels ( p Conclusion: Suboptimal performance frequently occurs in patients with MS and cognitive complaints. In both clinical practice and in cognitive research, suboptimal performance should be considered in the interpretation of cognitive outcomes. Identification of factors that differentiate between suboptimal and optimal performers with cognitive impairment needs further exploration.

Introduction: Glioma patients show increased global brain network clustering related to poorer cognition and epilepsy. However, it is unclear whether this increase is spatially widespread, localized in the (peri)tumor region only, or decreases with distance from the tumor. Materials and Methods: Weighted global and local brain network clustering was determined in 71 glioma patients and 53 controls by using magnetoencephalography. Tumor clustering was determined by averaging local clustering of regions overlapping with the tumor, and vice versa for non-tumor regions. Euclidean distance was determined from the tumor centroid to the centroids of other regions. Results: Patients showed higher global clustering compared with controls. Clustering of tumor and non-tumor regions did not differ, and local clustering was not associated with distance from the tumor. Post hoc analyses revealed that in the patient group, tumors were located more often in regions with higher clustering in controls, but it seemed that tumors of patients with high global clustering were located more often in regions with lower clustering in controls. Conclusions: Glioma patients show non-local network disturbances. Tumors of patients with high global clustering may have a preferred localization, namely regions with lower clustering in controls, suggesting that tumor localization relates to the extent of network disruption. Impact statement This work uses the innovative framework of network neuroscience to investigate functional connectivity patterns associated with brain tumors. Glioma (primary brain tumor) patients experience cognitive deficits and epileptic seizures, which have been related to brain network alterations. This study shows that glioma patients have a spatially widespread increase in global network clustering, which cannot be attributed to local effects of the tumor. Moreover, tumors occur more often in brain regions with higher network clustering in controls. This study emphasizes the global character of network alterations in glioma patients and suggests that preferred tumor locations are characterized by particular network profiles.

Multiple sclerosis (MS) is a demyelinating and neurodegenerative disease of the central nervous system (CNS). Repair through remyelination can be extensive, but quantification of remyelination remains challenging. To date, no method for standardized digital quantification of remyelination of MS lesions exists. This methodological study aims to present and validate a novel standardized method for myelin quantification in progressive MS brains to study myelin content more precisely. Fifty-five MS lesions in 32 tissue blocks from 14 progressive MS cases and five tissue blocks from 5 non-neurological controls were sampled. MS lesions were selected by macroscopic investigation of WM by standard histopathological methods. Tissue sections were stained for myelin with luxol fast blue (LFB) and histological assessment of de- or remyelination was performed by light microscopy. The myelin quantity was estimated with a novel myelin quantification method (MQM) in ImageJ. Three independent raters applied the MQM and the inter-rater reliability was calculated. We extended the method to diffusely appearing white matter (DAWM) and encephalitis to test potential wider applicability of the method. Inter-rater agreement was excellent (ICC = 0.96) and there was a high reliability with a lower- and upper limit of agreement up to −5.93% to 18.43% variation in myelin quantity. This study builds on the established concepts of histopathological semi-quantitative assessment of myelin and adds a novel, reliable and accurate quantitative measurement tool for the assessment of myelination in human post-mortem samples.

Background: The impact of cerebellar damage and (dys)function on cognition remains understudied in multiple sclerosis. Objective: To assess the cognitive relevance of cerebellar structural damage and functional connectivity (FC) in relapsing-remitting multiple sclerosis (RRMS) and secondary progressive multiple sclerosis (SPMS). Methods: This study included 149 patients with early RRMS, 81 late RRMS, 48 SPMS and 82 controls. Cerebellar cortical imaging included fractional anisotropy, grey matter volume and resting-state functional magnetic resonance imaging (MRI). Cerebellar FC was assessed with literature-based resting-state networks, using static connectivity (that is, conventional correlations), and dynamic connectivity (that is, fluctuations in FC strength). Measures were compared between groups and related to disability and cognition. Results: Cognitive impairment (CI) and cerebellar damage were worst in SPMS. Only SPMS showed cerebellar connectivity changes, compared to early RRMS and controls. Lower static FC was seen in fronto-parietal and default-mode networks. Higher dynamic FC was seen in dorsal and ventral attention, default-mode and deep grey matter networks. Cerebellar atrophy and higher dynamic FC together explained 32% of disability and 24% of cognitive variance. Higher dynamic FC was related to working and verbal memory and to information processing speed. Conclusion: Cerebellar damage and cerebellar connectivity changes were most prominent in SPMS and related to worse CI.

Greely (2021) argues that surrogates for living human brains in vivo might be of tremendous benefit to understanding human brain function—and eventually to curing devastating brain diseases—without...

ObjectiveTo characterize functional network changes related to conversion to cognitive impairment in a large sample of patients with multiple sclerosis (MS) over a period of 5 years.MethodsTwo hundred twenty-seven patients with MS and 59 healthy controls of the Amsterdam MS cohort underwent neuropsychological testing and resting-state fMRI at 2 time points (time interval 4.9 ± 0.9 years). At both baseline and follow-up, patients were categorized as cognitively preserved (CP; n = 123), mildly impaired (MCI;z< −1.5 on ≥2 cognitive tests, n = 32), or impaired (CI;z< −2 on ≥2 tests, n = 72), and longitudinal conversion between groups was determined. Network function was quantified with eigenvector centrality, a measure of regional network importance, which was computed for individual resting-state networks at both time points.ResultsOver time, 18.9% of patients converted to a worse phenotype; 22 of 123 patients who were CP (17.9%) converted from CP to MCI, 10 of 123 from CP to CI (8.1%), and 12 of 32 patients with MCI converted to CI (37.5%). At baseline, default-mode network (DMN) centrality was higher in CI individuals compared to controls (p= 0.05). Longitudinally, ventral attention network (VAN) importance increased in CP, driven by stable CP and CP-to-MCI converters (p< 0.05).ConclusionsOf all patients, 19% worsened in their cognitive status over 5 years. Conversion from intact cognition to impairment is related to an initial disturbed functioning of the VAN, then shifting toward DMN dysfunction in CI. Because the VAN normally relays information to the DMN, these results could indicate that in MS normal processes crucial for maintaining overall network stability are progressively disrupted as patients clinically progress.

Neuropsychological test scores in people with MS (PwMS) do not fully reflect cognitive functioning in daily life. Therefore, we developed a questionnaire based on instrumental activities of daily living (IADL), using the Amsterdam IADL-Q© for Alzheimer’s disease as starting point. Forty-eight items were evaluated on relevance and clarity by (inter)national experts (n = 30), PwMS (n = 61) and proxies (n = 30). Consequently, four items were omitted, two items were merged and seven items were added. Fifty items were included in the IADL questionnaire specific to cognitive functioning in MS (the MS-IADL-Q). Future studies are warranted to assess the psychometric properties of the MS-IADL-Q.

The severity and effects of damage to short- and long-range structural connections in multiple sclerosis are unknown. Meijer et al. report that long-range connections are more severely damaged than short-range connections. Damage to long-range connections is more strongly associated with reduced structural network efficiency, abnormal functional connectivity, and impaired cognition., An efficient network such as the human brain features a combination of global integration of information, driven by long-range connections, and local processing involving short-range connections. Whether these connections are equally damaged in multiple sclerosis is unknown, as is their relevance for cognitive impairment and brain function. Therefore, we cross-sectionally investigated the association between damage to short- and long-range connections with structural network efficiency, the functional connectome and cognition. From the Amsterdam multiple sclerosis cohort, 133 patients (age = 54.2 ± 9.6) with long-standing multiple sclerosis and 48 healthy controls (age = 50.8 ± 7.0) with neuropsychological testing and MRI were included. Structural connectivity was estimated from diffusion tensor images using probabilistic tractography (MRtrix 3.0) between pairs of brain regions. Structural connections were divided into short- (length < quartile 1) and long-range (length > quartile 3) connections, based on the mean distribution of tract lengths in healthy controls. To determine the severity of damage within these connections, (i) fractional anisotropy as a measure for integrity; (ii) total number of fibres; and (iii) percentage of tract affected by lesions were computed for each connecting tract and averaged for short- and long-range connections separately. To investigate the impact of damage in these connections for structural network efficiency, global efficiency was computed. Additionally, resting-state functional connectivity was computed between each pair of brain regions, after artefact removal with FMRIB’s ICA-based X-noiseifier. The functional connectivity similarity index was computed by correlating individual functional connectivity matrices with an average healthy control connectivity matrix. Our results showed that the structural network had a reduced efficiency and integrity in multiple sclerosis relative to healthy controls (both P < 0.05). The long-range connections showed the largest reduction in fractional anisotropy (z = −1.03, P < 0.001) and total number of fibres (z = −0.44, P < 0.01), whereas in the short-range connections only fractional anisotropy was affected (z = −0.34, P = 0.03). Long-range connections also demonstrated a higher percentage of tract affected by lesions than short-range connections, independent of tract length (P < 0.001). Damage to long-range connections was more strongly related to structural network efficiency and cognition (fractional anisotropy: r = 0.329 and r = 0.447. number of fibres r = 0.321 and r = 0.278. and percentage of lesions: r = −0.219; r = −0.426, respectively) than damage to short-range connections. Only damage to long-distance connections correlated with a more abnormal functional network (fractional anisotropy: r = 0.226). Our findings indicate that long-range connections are more severely affected by multiple sclerosis-specific damage than short-range connections. Moreover compared to short-range connections, damage to long-range connections better explains network efficiency and cognition.

In this review, combined post-mortem brain magnetic resonance imaging (MRI) and histology studies are highlighted, illustrating the relevance of translational approaches to define novel MRI signatures of neuropathological lesions in neuroinflammatory and neurodegenerative disorders. Initial studies combining post-mortem MRI and histology have validated various MRI sequences, assessing their sensitivity and specificity as diagnostic biomarkers in neurologic disease. More recent studies have focused on defining new radiological (bio)markers and implementing them in the clinical (research) setting. By combining neurological and neuroanatomical expertise with radiological development and pathological validation, a cycle emerges that allows for the discovery of novel MRI biomarkers to be implemented in vivo. Examples of this cycle are presented for multiple sclerosis, Alzheimer’s disease, Parkinson’s disease, and traumatic brain injury. Some applications have been shown to be successful, while others require further validation. In conclusion, there is much to explore with post-mortem MRI and histology studies, which can eventually be of high relevance for clinical practice.

Background and purpose: To predict disability and cognition in multiple sclerosis (MS) after 6 and 12 years, using early clinical and imaging measures. Methods: A total of 115 patients with MS were selected and followed up after 2 and 6 years, with 79 patients also being followed up after 12 years. Disability was measured using the Expanded Disability Status Scale (EDSS); cognition was measured only at follow-up using neuropsychological testing. Predictors of interest included EDSS score, baseline brain and lesion volumes and their changes over 2 years, baseline age, clinical phenotype, sex and educational level. Results: Higher 6-year EDSS score was predicted by early EDSS score and whole-brain volume changes and baseline diagnosis of primary progressive MS (adjusted R 2 = 0.56). Predictors for 12-year EDSS score included larger EDSS score changes and higher T1-hypointense lesion volumes (adjusted R 2 = 0.38). Year 6 cognition was predicted by primary progressive MS phenotype, lower educational level, male sex and early whole-brain atrophy (adjusted R 2 = 0.26); year 12 predictors included male sex, lower educational level and higher baseline T1-hypointense lesion volumes (adjusted R 2 = 0.14). Conclusions: Patients with early signs of neurodegeneration and a progressive disease onset were more prone to develop both disability progression and cognitive dysfunction. Male sex and lower educational level only affected cognitive dysfunction, which remains difficult to predict and probably needs more advanced imaging measures.

Background Previous studies have demonstrated extensive functional network disturbances in patients with multiple sclerosis (MS), showing a less efficient brain network. Recent studies indicate that the dynamic properties of the brain network show a strong correlation with cognitive function. Purpose To investigate network dynamics on functional MRI in cognitively impaired patients with MS. Materials and Methods In secondary analysis of prospectively acquired data, with imaging performed between 2008 and 2012, differences in regional functional network dynamics (ie, eigenvector centrality dynamics) between cognitively impaired and cognitively preserved participants with MS were investigated. Functional network dynamics were computed on images from functional MRI (3 T) by using a sliding-window approach. Cognitively impaired and preserved groups were compared by using a clusterwise permutation-based method. Results The study included 96 healthy control subjects and 332 participants with MS (including 226 women and 106 men; median age, 48.1 years ± 11.0). Among the 332 participants with MS, 87 were cognitively impaired and 180 had preserved cognitive function; mildly impaired patients (n = 65) were excluded. The cognitively impaired group included a higher proportion of men compared with the cognitively preserved group (35 of 87 [40%] vs 48 of 180 [27%], respectively; P = .02) and had a higher mean age (51.1 years vs 46.3 years, respectively; P < .01). The clusterwise permutation-based comparison at P less than .05 showed reduced centrality dynamics in default-mode, frontoparietal, and visual network regions on functional MRI in cognitively impaired participants versus cognitively preserved participants. A subsequent correlation and hierarchical clustering analysis revealed that the default-mode and visual networks normally demonstrate negatively correlated fluctuations in functional importance (r = -0.23 in healthy control subjects), with an almost complete loss of this negative correlation in cognitively impaired participants compared with cognitively preserved participants (r = -0.04 vs r = -0.14; corrected P = .02). Conclusion As shown on functional MRI, cognitively impaired patients with multiple sclerosis not only demonstrate reduced dynamics in default-mode, frontoparietal, and visual networks, but also show a loss of interplay between default-mode and visual networks. © RSNA, 2019 Online supplemental material is available for this article. See also the article by Eijlers et al and the editorial by Zivadinov and Dwyer in this issue.

Upper and lower limb impairments are common in people with multiple sclerosis (pwMS), yet difficult to clinically identify in early stages of disease progression. Tasks involving complex motor control can potentially reveal more subtle deficits in early stages, and can be performed during functional MRI (fMRI) acquisition, to investigate underlying neural mechanisms, providing markers for early motor progression. We investigated brain activation during visually guided force matching of hand or foot in 28 minimally disabled pwMS (Expanded Disability Status Scale (EDSS), The results from this study demonstrate that ultra‐high field fMRI during complex hand and foot tracking can identify subtle impairments in lower limb movements and upper and lower limb brain activity in minimally disabled people with multiple sclerosis (pwMS). Compared to healthy control, pwMS displayed delayed and more erroneous lower limb tracking, together with lower cerebellar, occipital and superior parietal cortical activation. Despite no differences in upper limb task performance, pwMS displayed lower inferior occipital cortical activation.

Meningeal inflammation strongly associates with demyelination and neuronal loss in the underlying cortex of progressive MS patients, thereby contributing significantly to clinical disability. However, the pathological mechanisms of meningeal inflammation-induced cortical pathology are still largely elusive. By extensive analysis of cortical microglia in post-mortem progressive MS tissue, we identified cortical areas with two MS-specific microglial populations, termed MS1 and MS2 cortex. The microglial population in MS1 cortex was characterized by a higher density and increased expression of the activation markers HLA class II and CD68, whereas microglia in MS2 cortex showed increased morphological complexity and loss of P2Y12 and TMEM119 expression. Interestingly, both populations associated with inflammation of the overlying meninges and were time-dependently replicated in an in vivo rat model for progressive MS-like chronic meningeal inflammation. In this recently developed animal model, cortical microglia at 1-month post-induction of experimental meningeal inflammation resembled microglia in MS1 cortex, and microglia at 2 months post-induction acquired a MS2-like phenotype. Furthermore, we observed that MS1 microglia in both MS cortex and the animal model were found closely apposing neuronal cell bodies and to mediate pre-synaptic displacement and phagocytosis, which coincided with a relative sparing of neurons. In contrast, microglia in MS2 cortex were not involved in these synaptic alterations, but instead associated with substantial neuronal loss. Taken together, our results show that in response to meningeal inflammation, microglia acquire two distinct phenotypes that differentially associate with neurodegeneration in the progressive MS cortex. Furthermore, our in vivo data suggests that microglia initially protect neurons from meningeal inflammation-induced cell death by removing pre-synapses from the neuronal soma, but eventually lose these protective properties contributing to neuronal loss. Supplementary Information The online version contains supplementary material available at 10.1007/s00401-021-02293-4.

Multiple sclerosis (MS) is after trauma the most important neurological disease in young adults, affecting 1 per 1000 individuals. With currently available medications, most of these targeting the immune system, satisfactory results have been obtained in patients with relapsing MS, but these can have serious adverse effects. Moreover, despite some promising developments, such as with B cell targeting therapies or sphingosine-1-phosphate modulating drugs, there still is a high unmet need of safe drugs with broad efficacy in patients with progressive MS. Despite substantial investments and intensive preclinical research, the proportion of promising lead compounds that reaches the approved drug status remains disappointingly low. One cause lies in the poor predictive validity of MS animal models used in the translation of pathogenic mechanisms into safe and effective treatments for the patient. This disturbing situation has raised criticism against the relevance of animal models used in preclinical research and calls for improvement of these models. This publication presents a potentially useful strategy to enhance the predictive validity of MS animal models, namely, to analyze the causes of failure in forward translation (lab to clinic) via reverse translation (clinic to lab). Through this strategy new insights can be gained that can help generate more valid MS models.