Prognostic value of single-subject grey matter networks in early multiple sclerosis.

The identification of prognostic markers in early multiple sclerosis (MS) is challenging and requires reliable measures that robustly predict future disease trajectories. Ideally, such measures should make inferences at the individual level to inform clinical decisions. This study investigated the prognostic value of longitudinal structural networks to predict 5-year Expanded Disability Status Scale (EDSS) progression in patients with relapsing-remitting MS (RRMS). We hypothesized that network measures, derived from MRI, outperform conventional MRI measurements at identifying patients at risk of developing disability progression. This longitudinal, multicentre study within the Magnetic Resonance Imaging in MS (MAGNIMS) network included 406 patients with RRMS (mean age = 35.7 ± 9.1 years) followed up for 5 years (mean follow-up = 5.0 ± 0.6 years). EDSS was determined to track disability accumulation. A group of 153 healthy subjects (mean age = 35.0 ± 10.1 years) with longitudinal MRI served as controls. All subjects underwent MRI at baseline and again 1 year after baseline. Grey matter atrophy over 1 year and white matter lesion load were determined. A single-subject brain network was reconstructed from T1-weighted scans based on grey matter atrophy measures derived from a statistical parameter mapping-based segmentation pipeline. Key topological measures, including network degree, global efficiency and transitivity, were calculated at single-subject level to quantify network properties related to EDSS progression. Areas under receiver operator characteristic (ROC) curves were constructed for grey matter atrophy and white matter lesion load, and the network measures and comparisons between ROC curves were conducted. The applied network analyses differentiated patients with RRMS who experience EDSS progression over 5 years through lower values for network degree [H(2) = 30.0, P < 0.001] and global efficiency [H(2) = 31.3, P < 0.001] from healthy controls but also from patients without progression. For transitivity, the comparisons showed no difference between the groups [H(2) = 1.5, P = 0.474]. Most notably, changes in network degree and global efficiency were detected independent of disease activity in the first year. The described network reorganization in patients experiencing EDSS progression was evident in the absence of grey matter atrophy. Network degree and global efficiency measurements demonstrated superiority of network measures in the ROC analyses over grey matter atrophy and white matter lesion load in predicting EDSS worsening (all P-values < 0.05). Our findings provide evidence that grey matter network reorganization over 1 year discloses relevant information about subsequent clinical worsening in RRMS. Early grey matter restructuring towards lower network efficiency predicts disability accumulation and outperforms conventional MRI predictors.

Assessing treatment response to oral drugs for multiple sclerosis in real-world setting: a MAGNIMS Study.

BACKGROUND: The assessment of treatment response is a crucial step for patients with relapsing-remitting multiple sclerosis on disease-modifying therapies (DMTs). We explored whether a scoring system developed within the MAGNIMS (MRI in Multiple Sclerosis) network to evaluate treatment response to injectable drugs can be adopted also to oral DMTs. METHODS: A multicentre dataset of 1200 patients who started three oral DMTs (fingolimod, teriflunomide and dimethyl fumarate) was collected within the MAGNIMS network. Disease activity after the first year was classified by the 'MAGNIMS' score based on the combination of relapses (0-≥2) and/or new T2 lesions (<3 or ≥3) on brain MRI. We explored the association of this score with the following 3-year outcomes: (1) confirmed disability worsening (CDW); (2) treatment failure (TFL); (3) relapse count between years 1 and 3. The additional value of contrast-enhancing lesions (CELs) and lesion location was explored. RESULTS: At 3 years, 160 patients experienced CDW: 12% of them scored '0' (reference), 18% scored '1' (HR=1.82, 95% CI 1.20 to 2.76, p=0.005) and 37% scored '2' (HR=2.74, 95% CI 1.41 to 5.36, p=0.003) at 1 year. The analysis of other outcomes provided similar findings. Considering the location of new T2 lesions (supratentorial vs infratentorial/spinal cord) and the presence of CELs improved the prediction of CDW and TFL, respectively, in patients with minimal MRI activity alone (one or two new T2 lesions). CONCLUSIONS: Early relapses and substantial MRI activity in the first year of treatment are associated with worse short-term outcomes in patients treated with some of the oral DMTs.

Concurrent inflammation-related brain reorganization in multiple sclerosis and depression.

BACKGROUND: Neuroinflammation affects brain tissue integrity in multiple sclerosis (MS) and may have a role in major depressive disorder (MDD). Whether advanced magnetic resonance imaging characteristics of the gray-to-white matter border serve as proxy of neuroinflammatory activity in MDD and MS remain unknown. METHODS: We included 684 participants (132 MDD patients with recurrent depressive episodes (RDE), 70 MDD patients with a single depressive episode (SDE), 222 MS patients without depressive symptoms (nMS), 58 MS patients with depressive symptoms (dMS), and 202 healthy controls (HC)). 3 T-T1w MRI-derived gray-to-white matter contrast (GWc) was used to reconstruct and characterize connectivity alterations of GWc-covariance networks by means of modularity, clustering coefficient, and degree. A cross-validated support vector machine was used to test the ability of GWc to stratify groups according to their depression symptoms, measured with BDI, at the single-subject level in MS and MDD independently. FINDINGS: MS and MDD patients showed increased modularity (ANOVA partial-η2 = 0.3) and clustering (partial-η2 = 0.1) compared to HC. In the subgroups, a linear trend analysis attested a gradient of modularity increases in the form: HC, dMS, nMS, SDE, and RDE (ANOVA partial-η2 = 0.28, p < 0.001) while this trend was less evident for clustering coefficient. Reduced morphological integrity (GWc) was seen in patients with increased depressive symptoms (partial-η2 = 0.42, P < 0.001) and was associated with depression scores across patient groups (r = -0.2, P < 0.001). Depressive symptoms in MS were robustly classified (88 %). CONCLUSIONS: Similar structural network alterations in MDD and MS exist, suggesting possible common inflammatory events like demyelination, neuroinflammation that are caught by GWc analyses. These alterations may vary depending on the severity of symptoms and in the case of MS may elucidate the occurrence of comorbid depression.

Translational value of choroid plexus imaging for tracking neuroinflammation in mice and humans.

Neuroinflammation is a pathophysiological hallmark of multiple sclerosis and has a close mechanistic link to neurodegeneration. Although this link is potentially targetable, robust translatable models to reliably quantify and track neuroinflammation in both mice and humans are lacking. The choroid plexus (ChP) plays a pivotal role in regulating the trafficking of immune cells from the brain parenchyma into the cerebrospinal fluid (CSF) and has recently attracted attention as a key structure in the initiation of inflammatory brain responses. In a translational framework, we here address the integrity and multidimensional characteristics of the ChP under inflammatory conditions and question whether ChP volumes could act as an interspecies marker of neuroinflammation that closely interrelates with functional impairment. Therefore, we explore ChP characteristics in neuroinflammation in patients with multiple sclerosis and in two experimental mouse models, cuprizone diet-related demyelination and experimental autoimmune encephalomyelitis. We demonstrate that ChP enlargement-reconstructed from MRI-is highly associated with acute disease activity, both in the studied mouse models and in humans. A close dependency of ChP integrity and molecular signatures of neuroinflammation is shown in the performed transcriptomic analyses. Moreover, pharmacological modulation of the blood-CSF barrier with natalizumab prevents an increase of the ChP volume. ChP enlargement is strongly linked to emerging functional impairment as depicted in the mouse models and in multiple sclerosis patients. Our findings identify ChP characteristics as robust and translatable hallmarks of acute and ongoing neuroinflammatory activity in mice and humans that could serve as a promising interspecies marker for translational and reverse-translational approaches.

Subcortical Volumes as Early Predictors of Fatigue in Multiple Sclerosis.

OBJECTIVE: Fatigue is a frequent and severe symptom in multiple sclerosis (MS), but its pathophysiological origin remains incompletely understood. We aimed to examine the predictive value of subcortical gray matter volumes for fatigue severity at disease onset and after 4 years by applying structural equation modeling (SEM). METHODS: This multicenter cohort study included 601 treatment-naive patients with MS after the first demyelinating event. All patients underwent a standardized 3T magnetic resonance imaging (MRI) protocol. A subgroup of 230 patients with available clinical follow-up data after 4 years was also analyzed. Associations of subcortical volumes (included into SEM) with MS-related fatigue were studied regarding their predictive value. In addition, subcortical regions that have a central role in the brain network (hubs) were determined through structural covariance network (SCN) analysis. RESULTS: Predictive causal modeling identified volumes of the caudate (s [standardized path coefficient] = 0.763, p = 0.003 [left]; s = 0.755, p = 0.006 [right]), putamen (s = 0.614, p = 0.002 [left]; s = 0.606, p = 0.003 [right]) and pallidum (s = 0.606, p = 0.012 [left]; s = 0.606, p = 0.012 [right]) as prognostic factors for fatigue severity in the cross-sectional cohort. Moreover, the volume of the pons was additionally predictive for fatigue severity in the longitudinal cohort (s = 0.605, p = 0.013). In the SCN analysis, network hubs in patients with fatigue worsening were detected in the putamen (p = 0.008 [left]; p = 0.007 [right]) and pons (p = 0.0001). INTERPRETATION: We unveiled predictive associations of specific subcortical gray matter volumes with fatigue in an early and initially untreated MS cohort. The colocalization of these subcortical structures with network hubs suggests an early role of these brain regions in terms of fatigue evolution. ANN NEUROL 2022;91:192-202.

Diffusion-based structural connectivity patterns of multiple sclerosis phenotypes.

BACKGROUND: We aimed to describe the severity of the changes in brain diffusion-based connectivity as multiple sclerosis (MS) progresses and the microstructural characteristics of these networks that are associated with distinct MS phenotypes. METHODS: Clinical information and brain MRIs were collected from 221 healthy individuals and 823 people with MS at 8 MAGNIMS centres. The patients were divided into four clinical phenotypes: clinically isolated syndrome, relapsing-remitting, secondary progressive and primary progressive. Advanced tractography methods were used to obtain connectivity matrices. Then, differences in whole-brain and nodal graph-derived measures, and in the fractional anisotropy of connections between groups were analysed. Support vector machine algorithms were used to classify groups. RESULTS: Clinically isolated syndrome and relapsing-remitting patients shared similar network changes relative to controls. However, most global and local network properties differed in secondary progressive patients compared with the other groups, with lower fractional anisotropy in most connections. Primary progressive participants had fewer differences in global and local graph measures compared with clinically isolated syndrome and relapsing-remitting patients, and reductions in fractional anisotropy were only evident for a few connections. The accuracy of support vector machine to discriminate patients from healthy controls based on connection was 81%, and ranged between 64% and 74% in distinguishing among the clinical phenotypes. CONCLUSIONS: In conclusion, brain connectivity is disrupted in MS and has differential patterns according to the phenotype. Secondary progressive is associated with more widespread changes in connectivity. Additionally, classification tasks can distinguish between MS types, with subcortical connections being the most important factor.

Network alterations underlying anxiety symptoms in early multiple sclerosis.

BACKGROUND: Anxiety, often seen as comorbidity in multiple sclerosis (MS), is a frequent neuropsychiatric symptom and essentially affects the overall disease burden. Here, we aimed to decipher anxiety-related networks functionally connected to atrophied areas in patients suffering from MS. METHODS: Using 3-T MRI, anxiety-related atrophy maps were generated by correlating longitudinal cortical thinning with the severity of anxiety symptoms in MS patients. To determine brain regions functionally connected to these maps, we applied a technique termed "atrophy network mapping". Thereby, the anxiety-related atrophy maps were projected onto a large normative connectome (n = 1000) performing seed-based functional connectivity. Finally, an instructed threat paradigm was conducted with regard to neural excitability and effective connectivity, using transcranial magnetic stimulation combined with high-density electroencephalography. RESULTS: Thinning of the left dorsal prefrontal cortex was the only region that was associated with higher anxiety levels. Atrophy network mapping identified functional involvement of bilateral prefrontal cortex as well as amygdala and hippocampus. Structural equation modeling confirmed that the volumes of these brain regions were significant determinants that influence anxiety symptoms in MS. We additionally identified reduced information flow between the prefrontal cortex and the amygdala at rest, and pathologically increased excitability in the prefrontal cortex in MS patients as compared to controls. CONCLUSION: Anxiety-related prefrontal cortical atrophy in MS leads to a specific network alteration involving structures that resemble known neurobiological anxiety circuits. These findings elucidate the emergence of anxiety as part of the disease pathology and might ultimately enable targeted treatment approaches modulating brain networks in MS.

Altered grey matter integrity and network vulnerability relate to epilepsy occurrence in patients with multiple sclerosis.

BACKGROUND AND PURPOSE: The aim of this study was to investigate the relevance of compartmentalized grey matter (GM) pathology and network reorganization in multiple sclerosis (MS) patients with concomitant epilepsy. METHODS: From 3-T magnetic resonance imaging scans of 30 MS patients with epilepsy (MSE group; age 41 ± 15 years, 21 females, disease duration 8 ± 6 years, median Expanded Disability Status Scale [EDSS] score 3), 60 MS patients without epilepsy (MS group; age 41 ± 12 years, 35 females, disease duration 6 ± 4 years, EDSS score 2), and 60 healthy subjects (HS group; age 40 ± 13 years, 27 females) the regional volumes of GM lesions and of cortical, subcortical and hippocampal structures were quantified. Network topology and vulnerability were modelled within the graph theoretical framework. Receiver-operating characteristic (ROC) curve analysis was applied to assess the accuracy of GM pathology measures to discriminate between MSE and MS patients. RESULTS: Higher lesion volumes within the hippocampus, mesiotemporal cortex and amygdala were detected in the MSE compared to the MS group (all p < 0.05). The MSE group had lower cortical volumes mainly in temporal and parietal areas compared to the MS and HS groups (all p < 0.05). Lower hippocampal tail and presubiculum volumes were identified in both the MSE and MS groups compared to the HS group (all p < 0.05). Network topology in the MSE group was characterized by higher transitivity and assortativity, and higher vulnerability compared to the MS and HS groups (all p < 0.05). Hippocampal lesion volume yielded the highest accuracy (area under the ROC curve 0.80 [0.67-0.91]) in discriminating between MSE and MS patients. CONCLUSIONS: High lesion load, altered integrity of mesiotemporal GM structures, and network reorganization are associated with a greater propensity for epilepsy occurrence in people with MS.

Gray matter integrity predicts white matter network reorganization in multiple sclerosis.

Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease leading to gray matter atrophy and brain network reconfiguration as a response to increasing tissue damage. We evaluated whether white matter network reconfiguration appears subsequently to gray matter damage, or whether the gray matter degenerates following alterations in white matter networks. MRI data from 83 patients with clinically isolated syndrome and early relapsing-remitting MS were acquired at two time points with a follow-up after 1 year. White matter network integrity was assessed based on probabilistic tractography performed on diffusion-weighted data using graph theoretical analyses. We evaluated gray matter integrity by computing cortical thickness and deep gray matter volume in 94 regions at both time points. The thickness of middle temporal cortex and the volume of deep gray matter regions including thalamus, caudate, putamen, and brain stem showed significant atrophy between baseline and follow-up. White matter network dynamics, as defined by modularity and distance measure changes over time, were predicted by deep gray matter volume of the atrophying anatomical structures. Initial white matter network properties, on the other hand, did not predict atrophy. Furthermore, gray matter integrity at baseline significantly predicted physical disability at 1-year follow-up. In a sub-analysis, deep gray matter volume was significantly related to cognitive performance at baseline. Hence, we postulate that atrophy of deep gray matter structures drives the adaptation of white matter networks. Moreover, deep gray matter volumes are highly predictive for disability progression and cognitive performance.

Myelination- and immune-mediated MR-based brain network correlates.

BACKGROUND: Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS), characterized by inflammatory and neurodegenerative processes. Despite demyelination being a hallmark of the disease, how it relates to neurodegeneration has still not been completely unraveled, and research is still ongoing into how these processes can be tracked non-invasively. Magnetic resonance imaging (MRI) derived brain network characteristics, which closely mirror disease processes and relate to functional impairment, recently became important variables for characterizing immune-mediated neurodegeneration; however, their histopathological basis remains unclear. METHODS: In order to determine the MRI-derived correlates of myelin dynamics and to test if brain network characteristics derived from diffusion tensor imaging reflect microstructural tissue reorganization, we took advantage of the cuprizone model of general demyelination in mice and performed longitudinal histological and imaging analyses with behavioral tests. By introducing cuprizone into the diet, we induced targeted and consistent demyelination of oligodendrocytes, over a period of 5 weeks. Subsequent myelin synthesis was enabled by reintroduction of normal food. RESULTS: Using specific immune-histological markers, we demonstrated that 2 weeks of cuprizone diet induced a 52% reduction of myelin content in the corpus callosum (CC) and a 35% reduction in the neocortex. An extended cuprizone diet increased myelin loss in the CC, while remyelination commenced in the neocortex. These histologically determined dynamics were reflected by MRI measurements from diffusion tensor imaging. Demyelination was associated with decreased fractional anisotropy (FA) values and increased modularity and clustering at the network level. MRI-derived modularization of the brain network and FA reduction in key anatomical regions, including the hippocampus, thalamus, and analyzed cortical areas, were closely related to impaired memory function and anxiety-like behavior. CONCLUSION: Network-specific remyelination, shown by histology and MRI metrics, determined amelioration of functional performance and neuropsychiatric symptoms. Taken together, we illustrate the histological basis for the MRI-driven network responses to demyelination, where increased modularity leads to evolving damage and abnormal behavior in MS. Quantitative information about in vivo myelination processes is mirrored by diffusion-based imaging of microstructural integrity and network characteristics.

Increased cerebrospinal fluid albumin and immunoglobulin A fractions forecast cortical atrophy and longitudinal functional deterioration in relapsing-remitting multiple sclerosis.

BACKGROUND: Currently, no unequivocal predictors of disease evolution exist in patients with multiple sclerosis (MS). Cortical atrophy measurements are, however, closely associated with cumulative disability. OBJECTIVE: Here, we aim to forecast longitudinal magnetic resonance imaging (MRI)-driven cortical atrophy and clinical disability from cerebrospinal fluid (CSF) markers. METHODS: We analyzed CSF fractions of albumin and immunoglobulins (Ig) A, G, and M and their CSF to serum quotients. RESULTS: Widespread atrophy was highly associated with increased baseline CSF concentrations and quotients of albumin and IgA. Patients with increased CSFIgA and CSFIgM showed higher functional disability at follow-up. CONCLUSION: CSF markers of blood-brain barrier integrity and specific immune response forecast emerging gray matter pathology and disease progression in MS.

Association of smoking but not HLA-DRB1*15:01, APOE or body mass index with brain atrophy in early multiple sclerosis.

BACKGROUND: The course of multiple sclerosis (MS) shows substantial inter-individual variability. The underlying determinants of disease severity likely involve genetic and environmental factors. OBJECTIVE: The aim of this study was to assess the impact of APOE and HLA polymorphisms as well as smoking and body mass index (BMI) in the very early MS course. METHODS: Untreated patients ( n = 263) with a recent diagnosis of relapsing-remitting (RR) MS or clinically isolated syndrome underwent standardized magnetic resonance imaging (MRI). Genotyping was performed for single-nucleotide polymorphisms (SNPs) rs3135388 tagging the HLA-DRB1*15:01 haplotype and rs7412 (Ɛ2) and rs429358 (Ɛ4) in APOE. Linear regression analyses were applied based on the three SNPs, smoking and BMI as exposures and MRI surrogate markers for disease severity as outcomes. RESULTS: Current smoking was associated with reduced gray matter fraction, lower brain parenchymal fraction and increased cerebrospinal fluid fraction in comparison to non-smoking, whereas no effect was observed on white matter fraction. BMI and the SNPs in HLA and APOE were not associated with structural MRI parameters. CONCLUSIONS: Smoking may have an unfavorable effect on the gray matter fraction as a potential measure of MS severity already in early MS. These findings may impact patients' counseling upon initial diagnosis of MS.

Treatment response to dimethyl fumarate is characterized by disproportionate CD8+ T cell reduction in MS.

BACKGROUND: The effect of dimethyl fumarate (DMF) on circulating lymphocyte subsets and their contribution as predictors of clinical efficacy have not yet been investigated in multiple sclerosis (MS). OBJECTIVE: To evaluate lymphocytes and lymphocyte subsets (analyzed 6 months after DMF start) in MS patients with and without disease activity after 1 year of treatment in a retrospective study. METHODS: Peripheral blood lymphocyte subsets were analyzed by flow cytometry. Untreated MS patients ( n = 40) were compared to those 6 months after onset of DMF treatment ( n = 51). Clinical and magnetic resonance imaging (MRI) disease activity of DMF-treated patients were assessed in the first year under treatment. RESULTS: Stable patients showed significantly lower lymphocytes, CD4+ and CD8+ T cells as well as CD19+ B cells compared to active patients under DMF treatment. Furthermore, an increased CD4/CD8 ratio ( p < 0.025) in stable patients indicated a disproportionate reduction of CD8+ T cells relative to CD4+ T cells. Reduced lymphocytes, CD8+ T cells, and CD19+ B cells 6 months after DMF start allowed prediction of the treatment response in the first year. CONCLUSION: DMF treatment response is reflected by lower circulating lymphocytes and specific lymphocyte subsets. Changes in the cellular immune profiles under DMF treatment are clinically relevant and might serve as a surrogate marker of treatment response.

Frontal Lobe Connectivity and Network Community Characteristics are Associated with the Outcome of Subthalamic Nucleus Deep Brain Stimulation in Patients with Parkinson's Disease.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is nowadays an evidence-based state of the art therapy option for motor and non-motor symptoms in patients with Parkinson's disease (PD). However, the exact anatomical regions of the cerebral network that are targeted by STN-DBS have not been precisely described and no definitive pre-intervention predictors of the clinical response exist. In this study, we test the hypothesis that the clinical effectiveness of STN-DBS depends on the connectivity profile of the targeted brain networks. Therefore, we used diffusion-weighted imaging (DWI) and probabilistic tractography to reconstruct the anatomical networks and the graph theoretical framework to quantify the connectivity profile. DWI was obtained pre-operatively from 15 PD patients who underwent DBS (mean age = 67.87 ± 7.88, 11 males, H&Y score = 3.5 ± 0.8) using a 3T MRI scanner (Philips Achieva). The pre-operative connectivity properties of a network encompassing frontal, prefrontal cortex and cingulate gyrus were directly linked to the postoperative clinical outcome. Eccentricity as a topological-characteristic of the network defining how cerebral regions are embedded in relation to distant sites correlated inversely with the applied voltage at the active electrode for optimal clinical response. We found that network topology and pre-operative connectivity patterns have direct influence on the clinical response to DBS and may serve as important and independent predictors of the postoperative clinical outcome.

Longitudinal quantitative MRI assessment of cortical damage in multiple sclerosis: A pilot study.

PURPOSE: Quantitative MRI (qMRI) allows assessing cortical pathology in multiple sclerosis (MS) on a microstructural level, where cortical damage has been shown to prolong T1 -relaxation time and increase proton density (PD) compared to controls. However, the evolution of these changes in MS over time has not been investigated so far. In this pilot study we used an advanced method for the longitudinal assessment of cortical tissue change in MS patients with qMRI in comparison to cortical atrophy, as derived from conventional MRI. MATERIALS AND METHODS: Twelve patients with relapsing-remitting MS underwent 3T T1 /PD-mapping at two timepoints with a mean interval of 12 months. The respective cortical T1 /PD-values were extracted from the middle of the cortical layer and the cortical thickness was measured for surface-based identification of clusters with increasing/decreasing values. RESULTS: Statistical analysis showed clusters with increasing PD- and T1 -values over time (annualized rate for T1 /PD increase in these clusters: 3.4 ± 2.56% for T1 , P = 0.0007; 2.3 ± 2.59% for PD, P = 0.01). Changes are heterogeneous across the cortex and different patterns of longitudinal PD and T1 increase emerged. Analysis of the cortical thickness yielded only one small cluster indicating a decrease of cortical thickness. CONCLUSION: Changes of cortical tissue composition in MS seem to be reflected by a spatially inhomogeneous, multifocal increase of the PD values, indicating replacement of neural tissue by water, and of the T1 -relaxation time, a surrogate of demyelination, axonal loss, and gliosis. qMRI changes were more prominent than cortical atrophy, showing the potential of qMRI techniques to quantify microstructural alterations that remain undetected by conventional MRI. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1485-1490.

A "kissing lesion": In-vivo 7T evidence of meningeal inflammation in early multiple sclerosis.

BACKGROUND: The role of cortical lesions (CLs) in disease progression and clinical deficits is increasingly recognized in multiple sclerosis (MS); however the origin of CLs in MS still remains unclear. OBJECTIVE: Here, we report a para-sulcal CL detected two years after diagnosis in a relapsing-remitting MS (RRMS) patient without manifestation of clinical deficit. METHODS: Ultra-high field (7T) MR imaging using magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE) sequence was performed. RESULTS: A para-sulcal CL was detected which showed hypointense rim and iso- to hyperintense core. This was detected in the proximity of the leptomeninges in the left precentral gyrus extending to the adjacent postcentral gyrus. CONCLUSION: This finding indicates that inflammatory infiltration into the cortex through the meninges underlies cortical pathology already in the early stage of disease and in mild disease course.

Role of IL-17-producing lymphocytes in severity of multiple sclerosis upon natalizumab treatment.

OBJECTIVE: Natalizumab is known to prevent T-helper cells entering the central nervous system (CNS). We hypothesize that more pathogenic T-helper cells are present outside the CNS and a possible relationship to disease severity. METHODS: Characterization and enrichment of human CD4+IL-17+ cells were performed ex vivo using peripheral blood mononuclear cells from natalizumab-treated relapsing-remitting multiple sclerosis (RRMS) patients ( n = 33), untreated RRMS patients ( n = 13), and healthy controls ( n = 33). Magnetic resonance imaging (MRI) scans were performed routinely for patients. RESULTS: Lymphocytes were elevated in peripheral blood of natalizumab-treated patients compared to untreated patients and healthy controls. Whereas group comparison for CD4+IL-17+ numbers also differed, CD4+IFN-γ+ and CD4+IL-22+ counts were not increased. CD4+IL-17+ cells not only expressed but also secreted IL-17. In natalizumab-treated patients, IL-17+ cell frequency was found to correlate with T1-hypointense lesions, but was not an indicator for rebound activity after treatment discontinuation, except in one patient who experienced a fulminant rebound, and interestingly, in whom the highest IL-17+ cell levels were observed. CONCLUSION: Increased lymphocytes and CD4+IL-17+ cells in the blood of RRMS patients receiving natalizumab corroborate the drug's mechanism of action, that is, blocking transmigration to CNS. Correlation between IL-17-expressing lymphocytes and T1-hypointense lesions underlines the important role of these cells in the disease pathology.

Increased structural white and grey matter network connectivity compensates for functional decline in early multiple sclerosis.

BACKGROUND: The pathology of multiple sclerosis (MS) consists of demyelination and neuronal injury, which occur early in the disease; yet, remission phases indicate repair. Whether and how the central nervous system (CNS) maintains homeostasis to counteract clinical impairment is not known. OBJECTIVE: We analyse the structural connectivity of white matter (WM) and grey matter (GM) networks to understand the absence of clinical decline as the disease progresses. METHODS: A total of 138 relapsing-remitting MS patients (classified into six groups by disease duration) and 32 healthy controls were investigated using 3-Tesla magnetic resonance imaging (MRI). Networks were analysed using graph theoretical approaches based on connectivity patterns derived from diffusion-tensor imaging with probabilistic tractography for WM and voxel-based morphometry and regional-volume-correlation matrix for GM. RESULTS: In the first year after disease onset, WM networks evolved to a structure of increased modularity, strengthened local connectivity and increased local clustering while no clinical decline occurred. GM networks showed a similar dynamic of increasing modularity. This modified connectivity pattern mainly involved the cerebellum, cingulum and temporo-parietal regions. Clinical impairment was associated at later disease stages with a divergence of the network patterns. CONCLUSION: Our findings suggest that network functionality in MS is maintained through structural adaptation towards increased local and modular connectivity, patterns linked to adaptability and homeostasis.

Comparison of two quantitative proton density mapping methods in multiple sclerosis.

OBJECTIVE: Proton density (PD) mapping requires correction for the receive profile (RP), which is frequently performed via bias-field correction. An alternative RP-mapping method utilizes a comparison of uncorrected PD-maps and a value ρ(T1) directly derived from T1-maps via the Fatouros equation. This may be problematic in multiple sclerosis (MS), if respective parameters are only valid for healthy brain tissue. We aimed to investigate whether the alternative method yields correct PD values in MS patients. MATERIALS/METHODS: PD mapping was performed on 27 patients with relapsing-remitting MS and 27 healthy controls, utilizing both methods, yielding reference PD values (PDref, bias-field method) and PDalt (alternative method). RESULTS: PDalt-values closely matched PDref, both for patients and controls. In contrast, ρ(T1) differed by up to 3 % from PDref, and the voxel-wise correlation between PDref and ρ(T1) was reduced in a patient subgroup with a higher degree of disability. Still, discrepancies between ρ(T1) and PDref were almost identical across different tissue types, thus translating into a scaling factor, which cancelled out during normalization to 100 % in CSF, yielding a good agreement between PDalt and PDref. CONCLUSION: RP correction utilizing the auxiliary parameter ρ(T1) derived via the Fatouros equation provides accurate PD results in MS patients, in spite of discrepancies between ρ(T1) and actual PD values.

Power estimation for non-standardized multisite studies.

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions.