Leptomeningeal enhancement in multiple sclerosis and other neurological diseases: A systematic review and Meta-Analysis

BACKGROUND The lack of systematic evidence on leptomeningeal enhancement (LME) on MRI in neurological diseases, including multiple sclerosis (MS), hampers its interpretation in clinical routine and research settings. PURPOSE To perform a systematic review and meta-analysis of MRI LME in MS and other neurological diseases. MATERIALS AND METHODS In a comprehensive literature search in Medline, Scopus, and Embase, out of 2292 publications, 459 records assessing LME in neurological diseases were eligible for qualitative synthesis. Of these, 135 were included in a random-effects model meta-analysis with subgroup analyses for MS. RESULTS Of eligible publications, 161 investigated LME in neoplastic neurological (n = 2392), 91 in neuroinfectious (n = 1890), and 75 in primary neuroinflammatory diseases (n = 4038). The LME-proportions for these disease classes were 0.47 [95%-CI: 0.37-0.57], 0.59 [95%-CI: 0.47-0.69], and 0.26 [95%-CI: 0.20-0.35], respectively. In a subgroup analysis comprising 1605 MS cases, LME proportion was 0.30 [95%-CI 0.21-0.42] with lower proportions in relapsing-remitting (0.19 [95%-CI 0.13-0.27]) compared to progressive MS (0.39 [95%-CI 0.30-0.49], p = 0.002) and higher proportions in studies imaging at 7 T (0.79 [95%-CI 0.64-0.89]) compared to lower field strengths (0.21 [95%-CI 0.15-0.29], p < 0.001). LME in MS was associated with longer disease duration (mean difference 2.2 years [95%-CI 0.2-4.2], p = 0.03), higher Expanded Disability Status Scale (mean difference 0.6 points [95%-CI 0.2-1.0], p = 0.006), higher T1 (mean difference 1.6 ml [95%-CI 0.1-3.0], p = 0.04) and T2 lesion load (mean difference 5.9 ml [95%-CI 3.2-8.6], p < 0.001), and lower cortical volume (mean difference -21.3 ml [95%-CI -34.7--7.9], p = 0.002). CONCLUSIONS Our study provides high-grade evidence for the substantial presence of LME in MS and a comprehensive panel of other neurological diseases. Our data could facilitate differential diagnosis of LME in clinical settings. Additionally, our meta-analysis corroborates that LME is associated with key clinical and imaging features of MS. PROSPERO No: CRD42021235026

A lymphocyte-microglia-astrocyte axis in chronic active multiple sclerosis

Multiple sclerosis (MS) lesions that do not resolve in the months after they form harbour ongoing demyelination and axon degeneration, and are identifiable in vivo by their paramagnetic rims on MRI scans(1-3). Here, to define mechanisms underlying this disabling, progressive neurodegenerative state(4-6) and foster development of new therapeutic agents, we used MRI-informed single-nucleus RNA sequencing to profile the edge of demyelinated white matter lesions at various stages of inflammation. We uncovered notable glial and immune cell diversity, especially at the chronically inflamed lesion edge. We define \u27microglia inflamed in MS\u27 (MIMS) and \u27astrocytes inflamed in MS\u27, glial phenotypes that demonstrate neurodegenerative programming. The MIMS transcriptional profile overlaps with that of microglia in other neurodegenerative diseases, suggesting that primary and secondary neurodegeneration share common mechanisms and could benefit from similar therapeutic approaches. We identify complement component 1q (C1q) as a critical mediator of MIMS activation, validated immunohistochemically in MS tissue, genetically by microglia-specific C1q ablation in mice with experimental autoimmune encephalomyelitis, and therapeutically by treating chronic experimental autoimmune encephalomyelitis with C1q blockade. C1q inhibition is a potential therapeutic avenue to address chronic white matter inflammation, which could be monitored by longitudinal assessment of its dynamic biomarker, paramagnetic rim lesions, using advanced MRI methods

Magnetic resonance imaging in multiple sclerosis animal models: A systematic review, meta-analysis, and white paper

Magnetic resonance imaging (MRI) is the most important paraclinical tool for assessing drug response in multiple sclerosis (MS) clinical trials. As such, MRI has also been widely used in preclinical research to investigate drug efficacy and pathogenic aspects in MS animal models. Keeping track of all published preclinical imaging studies, and possible new therapeutic approaches, has become difficult considering the abundance of studies. Moreover, comparisons between studies are hampered by methodological differences, especially since small differences in an MRI protocol can lead to large differences in tissue contrast. We therefore provide a comprehensive qualitative overview of preclinical MRI studies in the field of neuroinflammatory and demyelinating diseases, aiming to summarize experimental setup, MRI methodology, and risk of bias. We also provide estimates of the effects of tested therapeutic interventions by a meta-analysis. Finally, to improve the standardization of preclinical experiments, we propose guidelines on technical aspects of MRI and reporting that can serve as a framework for future preclinical studies using MRI in MS animal models. By implementing these guidelines, clinical translation of findings will be facilitated, and could possibly reduce experimental animal numbers

Microstructural assessment of multiple sclerosis lesions and peri-plaques using advanced multishell diffusion MRI

Chronic active multiple sclerosis (MS) lesions, seen on susceptibility-based MRI as Paramagnetic Rim Lesions (PRL), are associated with increased clinical disability and axonal damage. Diffusion MRI (dMRI) can characterize in vivo tissue damage, however, the tissue microstructure specificity of established dMRI models is limited. Here, we characterized PRL vs non-PRL microstructure and their surrounding peri-plaque white matter (PPWM) using Track Density Imaging (TDI) and 4 different dMRI models, including two novel ones; Microstructure Fingerprinting (MF) and DIstribution of Anisotropic MicrOstructural eNvironments in DWI (DIAMOND). To our knowledge, MF, DIAMOND, and TDI have never been used to depict the microstructure of MS lesions. Consistent with previous data, we show that PRL and their surrounding PPWM are characterized by higher axonal damage when compared to non-PRL. Results derived from the TDI, MF and DIAMOND models are in line with those obtained with DTI and NODDI, suggesting that these advanced diffusion imaging methods can be used to study MS lesion pathology

Magnetic resonance imaging in multiple sclerosis animal models: A systematic review, meta-analysis, and white paper.

Magnetic resonance imaging (MRI) is the most important paraclinical tool for assessing drug response in multiple sclerosis (MS) clinical trials. As such, MRI has also been widely used in preclinical research to investigate drug efficacy and pathogenic aspects in MS animal models. Keeping track of all published preclinical imaging studies, and possible new therapeutic approaches, has become difficult considering the abundance of studies. Moreover, comparisons between studies are hampered by methodological differences, especially since small differences in an MRI protocol can lead to large differences in tissue contrast. We therefore provide a comprehensive qualitative overview of preclinical MRI studies in the field of neuroinflammatory and demyelinating diseases, aiming to summarize experimental setup, MRI methodology, and risk of bias. We also provide estimates of the effects of tested therapeutic interventions by a meta-analysis. Finally, to improve the standardization of preclinical experiments, we propose guidelines on technical aspects of MRI and reporting that can serve as a framework for future preclinical studies using MRI in MS animal models. By implementing these guidelines, clinical translation of findings will be facilitated, and could possibly reduce experimental animal numbers

BMAT: An open-source BIDS managing and analysis tool

Magnetic Resonance Imaging (MRI) is an established technique to study in vivo neurological disorders such as Multiple Sclerosis (MS). To avoid errors on MRI data organization and automated processing, a standard called Brain Imaging Data Structure (BIDS) has been recently proposed. The BIDS standard eases data sharing and processing within or between centers by providing guidelines for their description and organization. However, the transformation from the complex unstructured non-open file data formats coming directly from the MRI scanner to a correct BIDS structure can be cumbersome and time consuming. This hinders a wider adoption of the BIDS format across different study centers. To solve this problem and ease the day-to-day use of BIDS for the neuroimaging scientific community, we present the BIDS Managing and Analysis Tool (BMAT). The BMAT software is a complete and easy-to-use local open-source neuroimaging analysis tool with a graphical user interface (GUI) that uses the BIDS format to organize and process brain MRI data for MS imaging research studies. BMAT provides the possibility to translate data from MRI scanners to the BIDS structure, create and manage BIDS datasets as well as develop and run automated processing pipelines, and is faster than its competitor. BMAT software propose the possibility to download useful analysis apps, especially applied to MS research with lesion segmentation and processing of imaging contrasts for novel disease biomarkers such as the central vein sign and the paramagnetic rim lesions

Enlarged perivascular spaces are associated with brain microangiopathy and aging in multiple sclerosis

Background: Growing evidence links brain-MRI enlarged perivascular spaces (EPVS) and multiple sclerosis (MS), but their role remains unclear. Objective: This study aimed to investigate the cross-sectional associations of EPVS with several neuroinflammatory and neurodegenerative features in a large multicentric-MS cohort. Methods: In total, 207 patients underwent 3T axial-T2-weighted brain-MRI for EPVS assessment (EPVS dichotomized into high/low according to ⩾ 2/< 2 rating categories). MRI biomarkers included brain-predicted age and brain-predicted age difference (brain-PAD), central vein sign (CVS)-positive lesion percentage (CVS%), paramagnetic rim and cortical lesions, T2-lesion load, and brain volumetry. The variable relative importance for EPVS-category prediction was explored using a classification random forest approach. Results: High EPVS patients were older (49 vs 44 years, p = 0.003), had ⩾ 1 vascular risk factors (VRFs; p = 0.005), lower CVS% (67% vs 78%, p < 0.001), reduced brain volumes (whole brain: 0.63 vs 0.73, p = 0.01; gray matter: 0.36 vs 0.40; p = 0.002), and older brain-predicted age (58 vs 50 years, p < 0.001). No differences were found for neuroinflammatory markers. After adjusting for age and VFRs (multivariate analyses), the high EPVS category correlated with lower CVS% (odds ratio (OR) = 0.98, 95% confidence interval (CI) = 0.96–0.99; p = 0.02), lower whole brain (OR = 0.01, 95% CI = 0.0003–0.5; p = 0.02), gray matter (OR = 0.0004, 95% CI = 0.0000004–0.4; p = 0.03) volumes, and higher brain-PAD (OR = 1.05, 95% CI = 1.01–1.09; p = 0.02). Random forest identified brain-PAD as the most important predictor of high EPVS. Conclusion: EPVS in MS likely reflect microangiopathic disease rather than neuroinflammation, potentially contributing to accelerated neurodegeneration

The “central vein sign” in patients with diagnostic “red flags” for multiple sclerosis: A prospective multicenter 3T study

Background: The central vein sign (CVS) has been shown to help in the differential diagnosis of multiple sclerosis (MS), but most prior studies are retrospective. Objectives: To prospectively assess the diagnostic predictive value of the CVS in diagnostically difficult cases. Methods: In this prospective multicenter study, 51 patients with suspected MS who had clinical, imaging, or laboratory “red flags” (i.e. features atypical for MS) underwent 3T fluid-attenuated inversion recovery (FLAIR*) magnetic resonance imaging (MRI) for CVS assessment. After the diagnostic work-up, expert clinicians blinded to the results of the CVS assessment came to a clinical diagnosis. The value of the CVS to prospectively predict an MS diagnosis was assessed. Results: Of the 39 patients who received a clinical diagnosis by the end of the study, 27 had MS and 12 received a non-MS diagnosis that included systemic lupus erythematosus, sarcoidosis, migraine, Sjögren disease, SPG4-spastic-paraparesis, neuromyelitis optica, and Susac syndrome. The percentage of perivenular lesions was higher in MS (median = 86%) compared to non-MS (median = 21%; p < 0.0001) patients. A 40% perivenular lesion cutoff was associated with 97% accuracy and a 96% positive/100% negative predictive value. Conclusion: The CVS detected on 3T FLAIR* images can accurately predict an MS diagnosis in patients suspected to have MS, but with atypical clinical, laboratory, and imaging features.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

The "central vein sign" in patients with diagnostic "red flags" for multiple sclerosis: A prospective multicenter 3T study

info:eu-repo/semantics/publishe