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Background: Blood–barrier (BBB) breakdown and active inflammation are hallmarks of relapsing multiple sclerosis (RMS), but the molecular events contributing to the development of new lesions are not well explored. Leaky endothelial junctions are associated with increased production of endothelial-derived extracellular microvesicles (EVs) and result in the entry of circulating immune cells into the brain. MRI with intravenous gadolinium (Gd) can visualize acute blood–barrier disruption as the initial event of the evolution of new lesions. Methods: Here, weekly MRI with Gd was combined with proteomics, multiplex immunoassay, and endothelial stress-optimized EV array to identify early markers related to BBB disruption. Five patients with RMS with no disease-modifying treatment were monitored weekly using high-resolution 3T MRI scanning with intravenous gadolinium (Gd) for 8 weeks. Patients were then divided into three groups (low, medium, or high MRI activity) defined by the number of new, total, and maximally enhancing Gd-enhancing lesions and the number of new FLAIR lesions. Plasma samples taken at each MRI were analyzed for protein biomarkers of inflammation by quantitative proteomics, and cytokines using multiplex immunoassays. EVs were characterized with an optimized endothelial stress EV array based on exosome surface protein markers for the detection of soluble secreted EVs. Results: Proteomics analysis of plasma yielded quantitative information on 208 proteins at each patient time point (n = 40). We observed the highest number of unique dysregulated proteins (DEPs) and the highest functional enrichment in the low vs. high MRI activity comparison. Complement activation and complement/coagulation cascade were also strongly overrepresented in the low vs. high MRI activity comparison. Activation of the alternative complement pathway, pathways of blood coagulation, extracellular matrix organization, and the regulation of TLR and IGF transport were unique for the low vs. high MRI activity comparison as well, with these pathways being overrepresented in the patient with high MRI activity. Principal component analysis indicated the individuality of plasma profiles in patients. IL-17 was upregulated at all time points during 8 weeks in patients with high vs. low MRI activity. Hierarchical clustering of soluble markers in the plasma indicated that all four MRI outcomes clustered together with IL-17, IL-12p70, and IL-1β. MRI outcomes also showed clustering with EV markers CD62E/P, MIC A/B, ICAM-1, and CD42A. The combined cluster of these cytokines, EV markers, and MRI outcomes clustered also with IL-12p40 and IL-7. All four MRI outcomes correlated positively with levels of IL-17 (p < 0.001, respectively), and EV-ICAM-1 (p < 0.0003, respectively). IL-1β levels positively correlated with the number of new Gd-enhancing lesions (p < 0.01), new FLAIR lesions (p < 0.001), and total number of Gd-enhancing lesions (p < 0.05). IL-6 levels positively correlated with the number of new FLAIR lesions (p < 0.05). Random Forests and linear mixed models identified IL-17, CCL17/TARC, CCL3/MIP-1α, and TNF-α as composite biomarkers predicting new lesion evolution. Conclusions: Combination of serial frequent MRI with proteome, neuroinflammation markers, and protein array data of EVs enabled assessment of temporal changes in inflammation and endothelial dysfunction in RMS related to the evolution of new and enhancing lesions. Particularly, the Th17 pathway and IL-1β clustered and correlated with new lesions and Gd enhancement, indicating their importance in BBB disruption and initiating acute brain inflammation in MS. In addition to the Th17 pathway, abundant protein changes between MRI activity groups suggested the role of EVs and the coagulation system along with innate immune responses including acute phase proteins, complement components, and neutrophil degranulation.

Multiple sclerosis is a heterogeneous progressive disease. Here, the authors use an unsupervised machine learning algorithm to determine multiple sclerosis subtypes, progression, and response to potential therapeutic treatments based on neuroimaging data.

Experimental autoimmune encephalomyelitis (EAE) is a model of multiple sclerosis (MS). EAE reflects important histopathological hallmarks, dissemination, and diversity of the disease, but has only moderate reproducibility of clinical and histopathological features. Focal lesions are less frequently observed in EAE than in MS, and can neither be constrained to specific locations nor timed to occur at a pre-specified moment. This renders difficult any experimental assessment of the pathogenesis of lesion evolution, including its inflammatory, degenerative (demyelination and axonal degeneration), and reparatory (remyelination, axonal sprouting, gliosis) component processes. We sought to develop a controlled model of inflammatory, focal brain lesions in EAE using focused ultrasound (FUS). We hypothesized that FUS induced focal blood brain barrier disruption (BBBD) will increase the likelihood of transmigration of effector cells and subsequent lesion occurrence at the sonicated location. Lesion development was monitored with conventional magnetic resonance imaging (MRI) as well as with magnetic resonance elastography (MRE) and further analyzed by histopathological means. EAE was induced in 12 6–8 weeks old female C57BL/6 mice using myelin oligodendrocyte glycoprotein (MOG) peptide. FUS-induced BBBD was performed 6, 7, and 9 days after immunization in subgroups of four animals and in an additional control group. MRI and MRE were performed on a 7T horizontal bore small animal MRI scanner. Imaging was conducted longitudinally 2 and 3 weeks after disease induction and 1 week after sonication in control animals, respectively. The scan protocol comprised contrast-enhanced T1-weighted and T2-weighted sequences as well as MRE with a vibration frequency of 1 kHz. Animals were sacrificed for histopathology after the last imaging time point. The overall clinical course of EAE was mild. A total of seven EAE animals presented with focal T2w hyperintense signal alterations in the sonicated hemisphere. These were most frequent in the group of animals sonicated 9 days after immunization. Histopathology revealed foci of activated microglia/macrophages in the sonicated right hemisphere of seven EAE animals. Larger cellular infiltrates or apparent demyelination were not seen. Control animals showed no abnormalities on MRI and did not have clusters of activated microglia/macrophages at the sites targeted with FUS. None of the animals had hemorrhages or gross tissue damage as potential side effects of FUS. EAE-animals tended to have lower values of viscoelasticity and elasticity in the sonicated compared to the contralateral parenchyma. This trend was significant when comparing the right sonicated to the left normal hemisphere and specifically the right sonicated compared to the left normal cortex in animals that underwent FUS-BBBD 9 days after immunization (right vs. left hemisphere: mean viscoelasticity 6.1 vs. 7.2 kPa; p = 0.003 and mean elasticity 4.9 vs. 5.7 kPa, p = 0.024; right vs. left cortex: mean viscoelasticity 5.8 vs. 7.5 kPa; p = 0.004 and mean elasticity 5 vs. 6.5 kPa; p = 0.008). A direct comparison of the biomechanical properties of focal T2w hyperintensities with normal appearing brain tissue did not yield significant results. Control animals showed no differences in viscoelasticity between sonicated and contralateral brain parenchyma. We here provide first evidence for a controlled lesion induction model in EAE using FUS-induced BBBD. The observed lesions in EAE are consistent with foci of activated microglia that may be interpreted as targeted initial inflammatory activity and which have been described as pre-active lesions in MS. Such foci can be identified and monitored with MRI. Moreover, the increased inflammatory activity in the sonicated brain parenchyma seems to have an effect on overall tissue matrix structure as reflected by changes of biomechanical parameters.

Most neurological disorders seemingly have heterogenous pathogenesis, with overlapping contribution of neuronal, immune and vascular mechanisms of brain injury. The perivascular space in the brain represents a crossroad where those mechanisms interact, as well as a key anatomical component of the recently discovered glymphatic pathway, which is considered to play a crucial role in the clearance of brain waste linked to neurodegenerative diseases. The pathological interplay between neuronal, immune and vascular factors can create an environment that promotes self-perpetration of mechanisms of brain injury across different neurological diseases, including those that are primarily thought of as neurodegenerative, neuroinflammatory or cerebrovascular. Changes of the perivascular space can be monitored in humans in vivo using magnetic resonance imaging (MRI). In the context of glymphatic clearance, MRI-visible enlarged perivascular spaces (EPVS) are considered to reflect glymphatic stasis secondary to the perivascular accumulation of brain debris, although they may also represent an adaptive mechanism of the glymphatic system to clear them. EPVS are also established correlates of dementia and cerebral small vessel disease (SVD) and are considered to reflect brain inflammatory activity. In this review, we describe the “perivascular unit” as a key anatomical and functional substrate for the interaction between neuronal, immune and vascular mechanisms of brain injury, which are shared across different neurological diseases. We will describe the main anatomical, physiological and pathological features of the perivascular unit, highlight potential substrates for the interplay between different noxae and summarize MRI studies of EPVS in cerebrovascular, neuroinflammatory and neurodegenerative disorders.

This article focuses on the various magnetic resonance imaging metrics currently used in multiple sclerosis and discusses how they relate to central nervous system atrophy. The authors discuss the significance of T2 lesion burden, gray matter damage, T1 hypointense lesions (black holes), contrast-enhanced lesions, magnetization transfer imaging, diffusion imaging, and magnetic resonance spectroscopy. These magnetic resonance imaging surrogates exhibit different sensitivities for each of the underlying pathogenic processes of multiple sclerosis. By exploiting the complementary nature and varying sensitivities of these magnetic resonance imaging surrogates, it is possible to create a more comprehensive picture of the degenerative process of multiple sclerosis. [ABSTRACT FROM AUTHOR]

Mobility impairment in older persons is associated with brain white matter hyperintensities (WMH), a common finding in magnetic resonance images and one established imaging biomarker of small vessel disease. The contribution of possible microstructural abnormalities within normal-appearing white matter (NAWM) to mobility, however, remains unclear. We used diffusion tensor imaging (DTI) measures, i.e. fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), to assess microstructural changes within supratentorial NAWM and WMH sub-compartments, and to investigate their association with changes in mobility performance, i.e. Tinetti assessment and the 2.5-meters walk time test. We analyzed baseline (N = 86, age ≥75 years) and 4-year (N = 41) follow-up data. Results from cross-sectional analysis on baseline data showed significant correlation between WMH volume and NAWM-FA (r = -0.33, p = 0.002), NAWM-AD (r = 0.32, p = 0.003) and NAWM-RD (r = 0.39, p = 0.0002). Our longitudinal analysis showed that after 4-years, FA and AD decreased and RD increased within NAWM. In regional tract-based analysis decrease in NAWM-FA and increase in NAWM-RD within the genu of the corpus callosum correlated with slower walk time independent of age, gender and WMH burden. In conclusion, global DTI indices of microstructural integrity indicate that significant changes occur in the supratentorial NAWM over four years. The observed changes likely reflect white matter deterioration resulting from aging as well as accrual of cerebrovascular injury associated with small vessel disease. The observed association between mobility scores and regional measures of NAWM microstructural integrity within the corpus callosum suggests that subtle changes within this structure may contribute to mobility impairment.

OBJECTIVE:To explore the value of machine learning methods for predicting multiple sclerosis disease course. METHODS:1693 CLIMB study patients were classified as increased EDSS≥1.5 (worsening) or not (non-worsening) at up to five years after baseline visit. Support vector machines (SVM) were used to build the classifier, and compared to logistic regression (LR) using demographic, clinical and MRI data obtained at years one and two to predict EDSS at five years follow-up. RESULTS:Baseline data alone provided little predictive value. Clinical observation for one year improved overall SVM sensitivity to 62% and specificity to 65% in predicting worsening cases. The addition of one year MRI data improved sensitivity to 71% and specificity to 68%. Use of non-uniform misclassification costs in the SVM model, weighting towards increased sensitivity, improved predictions (up to 86%). Sensitivity, specificity, and overall accuracy improved minimally with additional follow-up data. Predictions improved within specific groups defined by baseline EDSS. LR performed more poorly than SVM in most cases. Race, family history of MS, and brain parenchymal fraction, ranked highly as predictors of the non-worsening group. Brain T2 lesion volume ranked highly as predictive of the worsening group. INTERPRETATION:SVM incorporating short-term clinical and brain MRI data, class imbalance corrective measures, and classification costs may be a promising means to predict MS disease course, and for selection of patients suitable for more aggressive treatment regimens.

Diffusion tensor imaging (DTI) is a sensitive tool for the assessment of microstructural alterations in brain white matter (WM). We propose a new processing technique to detect, local and global longitudinal changes of diffusivity metrics, in homologous regions along WM fiber-bundles. To this end, a reliable and automatic processing pipeline was developed in three steps: 1) co-registration and diffusion metrics computation, 2) tractography, bundle extraction and processing, and 3) longitudinal fiber-bundle analysis. The last step was based on an original Gaussian mixture model providing a fine analysis of fiber-bundle cross-sections, and allowing a sensitive detection of longitudinal changes along fibers. This method was tested on simulated and clinical data. High levels of F-Measure were obtained on simulated data. Experiments on cortico-spinal tract and inferior fronto-occipital fasciculi of five patients with Multiple Sclerosis (MS) included in a weekly follow-up protocol highlighted the greater sensitivity of this fiber scale approach to detect small longitudinal alterations.

Grey matter (GM) damage is a clinically relevant feature of multiple sclerosis (MS) that has been previously assessed with diffusion tensor imaging (DTI). Fractional anisotropy (FA) of the basal ganglia and thalamus might be increased in MS patients, and correlates with disability scores. Despite the established role of the striatum and thalamus in motor control, mood and cognition, the impact of DTI changes within these structures on motor and neuropsychological performance has not yet been specifically addressed in MS. We investigated DTI metrics of deep GM nuclei and their potential association with mobility and neuropsychological function. DTI metrics from 3T MRI were assessed in the caudate, putamen, and thalamus of 30 MS patients and 10 controls. Sixteen of the patients underwent neuropsychological testing. FA of the caudate and putamen was higher in MS patients compared to controls. Caudate FA correlated with Expanded Disability Status Scale score, Ambulation Index, and severity of depressive symptomatology. Putamen and thalamus FA correlated with deficits in memory tests. In contrast, cerebral white matter (WM) lesion burden showed no significant correlation with any of the disability, mobility and psychometric parameters. Our findings support evidence of FA changes in the basal ganglia in MS patients, as well as deep GM involvement in disabling features of MS, including mobility and cognitive impairment. Deep GM FA appears to be a more sensitive correlate of disability than WM lesion burden.

Successful socialization requires the ability of understanding of others' mental states. This ability called as mentalization (Theory of Mind) may become deficient and contribute to everyday life difficulties in multiple sclerosis. We aimed to explore the impact of brain pathology on mentalization performance in multiple sclerosis. Mentalization performance of 49 patients with multiple sclerosis was compared to 24 age- and gender matched healthy controls. T1- and T2-weighted three-dimensional brain MRI images were acquired at 3Tesla from patients with multiple sclerosis and 18 gender- and age matched healthy controls. We assessed overall brain cortical thickness in patients with multiple sclerosis and the scanned healthy controls, and measured the total and regional T1 and T2 white matter lesion volumes in patients with multiple sclerosis. Performances in tests of recognition of mental states and emotions from facial expressions and eye gazes correlated with both total T1-lesion load and regional T1-lesion load of association fiber tracts interconnecting cortical regions related to visual and emotion processing (genu and splenium of corpus callosum, right inferior longitudinal fasciculus, right inferior fronto-occipital fasciculus, uncinate fasciculus). Both of these tests showed correlations with specific cortical areas involved in emotion recognition from facial expressions (right and left fusiform face area, frontal eye filed), processing of emotions (right entorhinal cortex) and socially relevant information (left temporal pole). Thus, both disconnection mechanism due to white matter lesions and cortical thinning of specific brain areas may result in cognitive deficit in multiple sclerosis affecting emotion and mental state processing from facial expressions and contributing to everyday and social life difficulties of these patients.

Brain atrophy and cognitive dysfunction are neurodegenerative features of Multiple Sclerosis (MS). We used a candidate gene approach to address whether genetic variants implicated in susceptibility to late onset Alzheimer's Disease (AD) influence brain volume and cognition in MS patients.MS subjects were genotyped for five single nucleotide polymorphisms (snps) associated with susceptibility to AD: PICALM, CR1, CLU, PCK1, and ZNF224. We assessed brain volume using Brain Parenchymal Fraction (BPF) measurements obtained from Magnetic Resonance Imaging (MRI) data and cognitive function using the Symbol Digit Modalities Test (SDMT). Genotypes were correlated with cross-sectional BPF and SDMT scores using linear regression after adjusting for sex, age at symptom onset, and disease duration. 722 MS patients with a mean (±SD) age at enrollment of 41 (±10) years were followed for 44 (±28) months. The AD risk-associated allele of a non-synonymous SNP in the PCK1 locus (rs8192708G) is associated with a smaller average brain volume (P=0.0047) at the baseline MRI, but it does not impact our baseline estimate of cognition. PCK1 is additionally associated with higher baseline T2-hyperintense lesion volume (P=0.0088). Finally, we provide technical validation of our observation in a subset of 641 subjects that have more than one MRI study, demonstrating the same association between PCK1 and smaller average brain volume (P=0.0089) at the last MRI visit.Our study provides suggestive evidence for greater brain atrophy in MS patients bearing the PCK1 allele associated with AD-susceptibility, yielding new insights into potentially shared neurodegenerative process between MS and late onset AD.