Comparative overview of multi-shell diffusion MRI models to characterize the microstructure of multiple sclerosis lesions and periplaques.

In multiple sclerosis (MS), accurate in vivo characterization of the heterogeneous lesional and extra-lesional tissue pathology remains challenging. Marshalling several advanced imaging techniques - quantitative relaxation time (T1) mapping, a model-free average diffusion signal approach and four multi-shell diffusion models - this study investigates the performance of multi-shell diffusion models and characterizes the microstructural damage within (i) different MS lesion types - active, chronic active, and chronic inactive - (ii) their respective periplaque white matter (WM), and (iii) the surrounding normal-appearing white matter (NAWM). In 83 MS participants (56 relapsing-remitting, 27 progressive) and 23 age and sex-matched healthy controls (HC), we analysed a total of 317 paramagnetic rim lesions (PRL+), 232 non-paramagnetic rim lesions (PRL-), 38 contrast-enhancing lesions (CEL). Consistent with previous findings and histology, our analysis revealed the ability of advanced multi-shell diffusion models to characterize the unique microstructural patterns of CEL, and to elucidate their possible evolution into a resolving (chronic inactive) vs smoldering (chronic active) inflammatory stage. In addition, we showed that the microstructural damage extends well beyond the MRI-visible lesion edge, gradually fading out while moving outward from the lesion edge into the immediate WM periplaque and the NAWM, the latter still characterized by diffuse microstructural damage in MS vs HC. This study also emphasizes the critical role of selecting appropriate diffusion models to elucidate the complex pathological architecture of MS lesions and their periplaque. More specifically, multi-compartment diffusion models based on biophysically interpretable metrics such as neurite orientation dispersion and density (NODDI; mean auc=0.8002) emerge as the preferred choice for MS applications, while simpler models based on a representation of the diffusion signal, like diffusion tensor imaging (DTI; mean auc=0.6942), consistently underperformed, also when compared to T1 mapping (mean auc=0.73375).

Diagnostic Performance of Cortical Lesions and the Central Vein Sign in Multiple Sclerosis.

Importance: Multiple sclerosis (MS) misdiagnosis remains an important issue in clinical practice. Objective: To quantify the performance of cortical lesions (CLs) and central vein sign (CVS) in distinguishing MS from other conditions showing brain lesions on magnetic resonance imaging (MRI). Design, Setting, and Participants: This was a retrospective, cross-sectional multicenter study, with clinical and MRI data acquired between January 2010 and May 2020. Centralized MRI analysis was conducted between July 2020 and December 2022 by 2 raters blinded to participants' diagnosis. Participants were recruited from 14 European centers and from a multicenter pan-European cohort. Eligible participants had a diagnosis of MS, clinically isolated syndrome (CIS), or non-MS conditions; availability of a brain 3-T MRI scan with at least 1 sequence suitable for CL and CVS assessment; presence of T2-hyperintense white matter lesions (WMLs). A total of 1051 individuals were included with either MS/CIS (n = 599; 386 [64.4%] female; mean [SD] age, 41.5 [12.3] years) or non-MS conditions (including other neuroinflammatory disorders, cerebrovascular disease, migraine, and incidental WMLs in healthy control individuals; n = 452; 302 [66.8%] female; mean [SD] age, 49.2 [14.5] years). Five individuals were excluded due to missing clinical or demographic information (n = 3) or unclear diagnosis (n = 2). Exposures: MS/CIS vs non-MS conditions. Main Outcomes and Measures: Area under the receiver operating characteristic curves (AUCs) were used to explore the diagnostic performance of CLs and the CVS in isolation and in combination; sensitivity, specificity, and accuracy were calculated for various cutoffs. The diagnostic importance of CLs and CVS compared to conventional MRI features (ie, presence of infratentorial, periventricular, and juxtacortical WMLs) was ranked with a random forest model. Results: The presence of CLs and the previously proposed 40% CVS rule had a sensitivity, specificity, and accuracy for MS of 59.0% (95% CI, 55.1-62.8), 93.6% (95% CI, 91.4-95.6), and 73.9% (95% CI, 71.6-76.3) and 78.7% (95% CI, 75.5-82.0), 86.0% (95% CI, 82.1-89.5), and 81.5% (95% CI, 78.9-83.7), respectively. The diagnostic performance of the CVS (AUC, 0.89 [95% CI, 0.86-0.91]) was superior to that of CLs (AUC, 0.77 [95% CI, 0.75-0.80]; P < .001), and was increased when combining the 2 imaging markers (AUC, 0.92 [95% CI, 0.90-0.94]; P = .04); in the random forest model, both CVS and CLs outperformed the presence of infratentorial, periventricular, and juxtacortical WMLs in supporting MS differential diagnosis. Conclusions and Relevance: The findings in this study suggest that CVS and CLs may be valuable tools to increase the accuracy of MS diagnosis.

B cell depletion therapy does not resolve chronic active multiple sclerosis lesions.

BACKGROUND: Chronic active lesions (CAL) in multiple sclerosis (MS) have been observed even in patients taking high-efficacy disease-modifying therapy, including B-cell depletion. Given that CAL are a major determinant of clinical progression, including progression independent of relapse activity (PIRA), understanding the predicted activity and real-world effects of targeting specific lymphocyte populations is critical for designing next-generation treatments to mitigate chronic inflammation in MS. METHODS: We analyzed published lymphocyte single-cell transcriptomes from MS lesions and bioinformatically predicted the effects of depleting lymphocyte subpopulations (including CD20 B-cells) from CAL via gene-regulatory-network machine-learning analysis. Motivated by the results, we performed in vivo MRI assessment of PRL changes in 72 adults with MS, 46 treated with anti-CD20 antibodies and 26 untreated, over ∼2 years. FINDINGS: Although only 4.3% of lymphocytes in CAL were CD20 B-cells, their depletion is predicted to affect microglial genes involved in iron/heme metabolism, hypoxia, and antigen presentation. In vivo, tracking 202 PRL (150 treated) and 175 non-PRL (124 treated), none of the treated paramagnetic rims disappeared at follow-up, nor was there a treatment effect on PRL for lesion volume, magnetic susceptibility, or T1 time. PIRA occurred in 20% of treated patients, more frequently in those with ≥4 PRL (p = 0.027). INTERPRETATION: Despite predicted effects on microglia-mediated inflammatory networks in CAL and iron metabolism, anti-CD20 therapies do not fully resolve PRL after 2-year MRI follow up. Limited tissue turnover of B-cells, inefficient passage of anti-CD20 antibodies across the blood-brain-barrier, and a paucity of B-cells in CAL could explain our findings. FUNDING: Intramural Research Program of NINDS, NIH; NINDS grants R01NS082347 and R01NS082347; Dr. Miriam and Sheldon G. Adelson Medical Research Foundation; Cariplo Foundation (grant #1677), FRRB Early Career Award (grant #1750327); Fund for Scientific Research (FNRS).

Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective.

In recent years, the use of magnetic resonance imaging (MRI) for the diagnostic work-up of multiple sclerosis (MS) has evolved considerably. The 2017 McDonald criteria show high sensitivity and accuracy in predicting a second clinical attack in patients with a typical clinically isolated syndrome and allow an earlier diagnosis of MS. They have been validated, are evidence-based, simplify the clinical use of MRI criteria and improve MS patients' management. However, to limit the risk of misdiagnosis, they should be applied by expert clinicians only after the careful exclusion of alternative diagnoses. Recently, new MRI markers have been proposed to improve diagnostic specificity for MS and reduce the risk of misdiagnosis. The central vein sign and chronic active lesions (i.e., paramagnetic rim lesions) may increase the specificity of MS diagnostic criteria, but further effort is necessary to validate and standardize their assessment before implementing them in the clinical setting. The feasibility of subpial demyelination assessment and the clinical relevance of leptomeningeal enhancement evaluation in the diagnostic work-up of MS appear more limited. Artificial intelligence tools may capture MRI attributes that are beyond the human perception, and, in the future, artificial intelligence may complement human assessment to further ameliorate the diagnostic work-up and patients' classification. However, guidelines that ensure reliability, interpretability, and validity of findings obtained from artificial intelligence approaches are still needed to implement them in the clinical scenario. This review provides a summary of the most recent updates regarding the application of MRI for the diagnosis of MS.

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.

Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: Emerging machine learning techniques and future avenues.

The current diagnostic criteria for multiple sclerosis (MS) lack specificity, and this may lead to misdiagnosis, which remains an issue in present-day clinical practice. In addition, conventional biomarkers only moderately correlate with MS disease progression. Recently, some MS lesional imaging biomarkers such as cortical lesions (CL), the central vein sign (CVS), and paramagnetic rim lesions (PRL), visible in specialized magnetic resonance imaging (MRI) sequences, have shown higher specificity in differential diagnosis. Moreover, studies have shown that CL and PRL are potential prognostic biomarkers, the former correlating with cognitive impairments and the latter with early disability progression. As machine learning-based methods have achieved extraordinary performance in the assessment of conventional imaging biomarkers, such as white matter lesion segmentation, several automated or semi-automated methods have been proposed as well for CL, PRL, and CVS. In the present review, we first introduce these MS biomarkers and their imaging methods. Subsequently, we describe the corresponding machine learning-based methods that were proposed to tackle these clinical questions, putting them into context with respect to the challenges they are facing, including non-standardized MRI protocols, limited datasets, and moderate inter-rater variability. We conclude by presenting the current limitations that prevent their broader deployment and suggesting future research directions.

Prognostic indicators and outcomes of hospitalised COVID-19 patients with neurological disease: An individual patient data meta-analysis.

BACKGROUND: Neurological COVID-19 disease has been reported widely, but published studies often lack information on neurological outcomes and prognostic risk factors. We aimed to describe the spectrum of neurological disease in hospitalised COVID-19 patients; characterise clinical outcomes; and investigate factors associated with a poor outcome. METHODS: We conducted an individual patient data (IPD) meta-analysis of hospitalised patients with neurological COVID-19 disease, using standard case definitions. We invited authors of studies from the first pandemic wave, plus clinicians in the Global COVID-Neuro Network with unpublished data, to contribute. We analysed features associated with poor outcome (moderate to severe disability or death, 3 to 6 on the modified Rankin Scale) using multivariable models. RESULTS: We included 83 studies (31 unpublished) providing IPD for 1979 patients with COVID-19 and acute new-onset neurological disease. Encephalopathy (978 [49%] patients) and cerebrovascular events (506 [26%]) were the most common diagnoses. Respiratory and systemic symptoms preceded neurological features in 93% of patients; one third developed neurological disease after hospital admission. A poor outcome was more common in patients with cerebrovascular events (76% [95% CI 67-82]), than encephalopathy (54% [42-65]). Intensive care use was high (38% [35-41]) overall, and also greater in the cerebrovascular patients. In the cerebrovascular, but not encephalopathic patients, risk factors for poor outcome included breathlessness on admission and elevated D-dimer. Overall, 30-day mortality was 30% [27-32]. The hazard of death was comparatively lower for patients in the WHO European region. INTERPRETATION: Neurological COVID-19 disease poses a considerable burden in terms of disease outcomes and use of hospital resources from prolonged intensive care and inpatient admission; preliminary data suggest these may differ according to WHO regions and country income levels. The different risk factors for encephalopathy and stroke suggest different disease mechanisms which may be amenable to intervention, especially in those who develop neurological symptoms after hospital admission.

Chronic White Matter Inflammation and Serum Neurofilament Levels in Multiple Sclerosis.

OBJECTIVE: To assess whether chronic white matter inflammation in patients with multiple sclerosis (MS) as detected in vivo by paramagnetic rim MRI lesions (PRLs) is associated with higher serum neurofilament light chain (sNfL) levels, a marker of neuroaxonal damage. METHODS: In 118 patients with MS with no gadolinium-enhancing lesions or recent relapses, we analyzed 3D-submillimeter phase MRI and sNfL levels. Histopathologic evaluation was performed in 25 MS lesions from 20 additional autopsy MS cases. RESULTS: In univariable analyses, participants with ≥2 PRLs (n = 43) compared to those with ≤1 PRL (n = 75) had higher age-adjusted sNfL percentiles (median, 91 and 68; p < 0.001) and higher Multiple Sclerosis Severity Scale scores (MSSS median, 4.3 and 2.4; p = 0.003). In multivariable analyses, sNfL percentile levels were higher in PRLs ≥2 cases (ßadd, 16.3; 95% confidence interval [CI], 4.6-28.0; p < 0.01), whereas disease-modifying treatment (DMT), Expanded Disability Status Scale (EDSS) score, and T2 lesion load did not affect sNfL. In a similar model, sNfL percentile levels were highest in cases with ≥4 PRLs (n = 30; ßadd, 30.4; 95% CI, 15.6-45.2; p < 0.01). Subsequent multivariable analysis revealed that PRLs ≥2 cases also had higher MSSS (ßadd, 1.1; 95% CI, 0.3-1.9; p < 0.01), whereas MSSS was not affected by DMT or T2 lesion load. On histopathology, both chronic active and smoldering lesions exhibited more severe acute axonal damage at the lesion edge than in the lesion center (edge vs center: p = 0.004 and p = 0.0002, respectively). CONCLUSION: Chronic white matter inflammation was associated with increased levels of sNfL and disease severity in nonacute MS, suggesting that PRL contribute to clinically relevant, inflammation-driven neurodegeneration.

Myelin and axon pathology in multiple sclerosis assessed by myelin water and multi-shell diffusion imaging.

Damage to the myelin sheath and the neuroaxonal unit is a cardinal feature of multiple sclerosis; however, a detailed characterization of the interaction between myelin and axon damage in vivo remains challenging. We applied myelin water and multi-shell diffusion imaging to quantify the relative damage to myelin and axons (i) among different lesion types; (ii) in normal-appearing tissue; and (iii) across multiple sclerosis clinical subtypes and healthy controls. We also assessed the relation of focal myelin/axon damage with disability and serum neurofilament light chain as a global biological measure of neuroaxonal damage. Ninety-one multiple sclerosis patients (62 relapsing-remitting, 29 progressive) and 72 healthy controls were enrolled in the study. Differences in myelin water fraction and neurite density index were substantial when lesions were compared to healthy control subjects and normal-appearing multiple sclerosis tissue: both white matter and cortical lesions exhibited a decreased myelin water fraction and neurite density index compared with healthy (P < 0.0001) and peri-plaque white matter (P < 0.0001). Periventricular lesions showed decreased myelin water fraction and neurite density index compared with lesions in the juxtacortical region (P < 0.0001 and P < 0.05). Similarly, lesions with paramagnetic rims showed decreased myelin water fraction and neurite density index relative to lesions without a rim (P < 0.0001). Also, in 75% of white matter lesions, the reduction in neurite density index was higher than the reduction in the myelin water fraction. Besides, normal-appearing white and grey matter revealed diffuse reduction of myelin water fraction and neurite density index in multiple sclerosis compared to healthy controls (P < 0.01). Further, a more extensive reduction in myelin water fraction and neurite density index in normal-appearing cortex was observed in progressive versus relapsing-remitting participants. Neurite density index in white matter lesions correlated with disability in patients with clinical deficits (P < 0.01, beta = -10.00); and neurite density index and myelin water fraction in white matter lesions were associated to serum neurofilament light chain in the entire patient cohort (P < 0.01, beta = -3.60 and P < 0.01, beta = 0.13, respectively). These findings suggest that (i) myelin and axon pathology in multiple sclerosis is extensive in both lesions and normal-appearing tissue; (ii) particular types of lesions exhibit more damage to myelin and axons than others; (iii) progressive patients differ from relapsing-remitting patients because of more extensive axon/myelin damage in the cortex; and (iv) myelin and axon pathology in lesions is related to disability in patients with clinical deficits and global measures of neuroaxonal damage.

The central vein sign in multiple sclerosis patients with vascular comorbidities.

BACKGROUND: The central vein sign (CVS) is an imaging biomarker able to differentiate multiple sclerosis (MS) from other conditions causing similar appearance lesions on magnetic resonance imaging (MRI), including cerebral small vessel disease (CSVD). However, the impact of vascular risk factors (VRFs) for CSVD on the percentage of CVS positive (CVS+) lesions in MS has never been evaluated. OBJECTIVE: To investigate the association between different VRFs and the percentage of CVS+ lesions in MS. METHODS: In 50 MS patients, 3T brain MRIs (including high-resolution 3-dimensional T2*-weighted images) were analyzed for the presence of the CVS and MRI markers of CSVD. A backward stepwise regression model was used to predict the combined predictive effect of VRF (i.e. age, hypertension, diabetes, obesity, ever-smoking, and hypercholesterolemia) and MRI markers of CSVD on the CVS. RESULTS: The median frequency of CVS+ lesions was 71% (range: 35%-100%). In univariate analysis, age (p < 0.0001), hypertension (p < 0.001), diabetes (p < 0.01), obesity (p < 0.01), smoking (p < 0.05), and the presence of enlarged-perivascular-spaces on MRI (p < 0.005) were all associated with a lower percentage of CVS+ lesions. The stepwise regression model showed that age and arterial hypertension were both associated with the percentage of CVS+ lesions in MS (adjusted R2 = 0.46; p < 0.0001 and p = 0.01, respectively). CONCLUSION: The proportion of CVS+ lesions significantly decreases in older and hypertensive MS patients. Although this study was conducted in patients with an already established MS diagnosis, the diagnostic yield of the previously proposed 35% CVS proportion-based diagnostic threshold appears to be not affected. Overall these results suggest that the presence of VRF for CSVD should be taken into account during the CVS assessment.

Immune-mediated neurological syndromes in SARS-CoV-2-infected patients.

BACKGROUND: Evidence of immune-mediated neurological syndromes associated with the severe acute respiratory syndrome coronavirus (SARS-CoV-2) infection is limited. We therefore investigated clinical, serological and CSF features of coronavirus disease 2019 (COVID-19) patients with neurological manifestations. METHODS: Consecutive COVID-19 patients with neurological manifestations other than isolated anosmia and/or non-severe headache, and with no previous neurological or psychiatric disorders were prospectively included. Neurological examination was performed in all patients and lumbar puncture with CSF examination was performed when not contraindicated. Serum anti-gangliosides antibodies were tested when clinically indicated. RESULTS: Of the 349 COVID-19 admitted to our center between March 23rd and April 24th 2020, 15 patients (4.3%) had neurological manifestations and fulfilled the study inclusion/exclusion criteria. CSF examination was available in 13 patients and showed lymphocytic pleocytosis in 2 patients: 1 with anti-contactin-associated protein 2 (anti-Caspr2) antibody encephalitis and 1 with meningo-polyradiculitis. Increased serum titer of anti-GD1b antibodies was found in three patients and was associated with variable clinical presentations, including cranial neuropathy with meningo-polyradiculitis, brainstem encephalitis and delirium. CSF PCR for SARS-CoV-2 was negative in all patients. CONCLUSIONS: In SARS-Cov-2 infected patients with neurological manifestations, CSF pleocytosis is associated with para- or post-infectious encephalitis and polyradiculitis. Anti-GD1b and anti-Caspr2 autoantibodies can be identified in certain cases, raising the question of SARS-CoV-2-induced secondary autoimmunity.

RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis.

OBJECTIVES: In multiple sclerosis (MS), the presence of a paramagnetic rim at the edge of non-gadolinium-enhancing lesions indicates perilesional chronic inflammation. Patients featuring a higher paramagnetic rim lesion burden tend to have more aggressive disease. The objective of this study was to develop and evaluate a convolutional neural network (CNN) architecture (RimNet) for automated detection of paramagnetic rim lesions in MS employing multiple magnetic resonance (MR) imaging contrasts. MATERIALS AND METHODS: Imaging data were acquired at 3 Tesla on three different scanners from two different centers, totaling 124 MS patients, and studied retrospectively. Paramagnetic rim lesion detection was independently assessed by two expert raters on T2*-phase images, yielding 462 rim-positive (rim+) and 4857 rim-negative (rim-) lesions. RimNet was designed using 3D patches centered on candidate lesions in 3D-EPI phase and 3D FLAIR as input to two network branches. The interconnection of branches at both the first network blocks and the last fully connected layers favors the extraction of low and high-level multimodal features, respectively. RimNet's performance was quantitatively evaluated against experts' evaluation from both lesion-wise and patient-wise perspectives. For the latter, patients were categorized based on a clinically relevant threshold of 4 rim+ lesions per patient. The individual prediction capabilities of the images were also explored and compared (DeLong test) by testing a CNN trained with one image as input (unimodal). RESULTS: The unimodal exploration showed the superior performance of 3D-EPI phase and 3D-EPI magnitude images in the rim+/- classification task (AUC = 0.913 and 0.901), compared to the 3D FLAIR (AUC = 0.855, Ps < 0.0001). The proposed multimodal RimNet prototype clearly outperformed the best unimodal approach (AUC = 0.943, P < 0.0001). The sensitivity and specificity achieved by RimNet (70.6% and 94.9%, respectively) are comparable to those of experts at the lesion level. In the patient-wise analysis, RimNet performed with an accuracy of 89.5% and a Dice coefficient (or F1 score) of 83.5%. CONCLUSIONS: The proposed prototype showed promising performance, supporting the usage of RimNet for speeding up and standardizing the paramagnetic rim lesions analysis in MS.

Paramagnetic Rim Lesions are Specific to Multiple Sclerosis: An International Multicenter 3T MRI Study.

In multiple sclerosis (MS), a subset of chronic active white matter lesions are identifiable on magnetic resonance imaging by their paramagnetic rims, and increasing evidence supports their association with severity of clinical disease. We studied their potential role in differential diagnosis, screening an international multicenter clinical research-based sample of 438 individuals affected by different neurological conditions (MS, other inflammatory, infectious, and non-inflammatory conditions). Paramagnetic rim lesions, rare in other neurological conditions (52% of MS vs 7% of non-MS cases), yielded high specificity (93%) in differentiating MS from non-MS. Future prospective multicenter studies should validate their role as a diagnostic biomarker. ANN NEUROL 2020;88:1034-1042.

CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis.

The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter-rater variability and the expenditure of time associated with manual assessment. We describe a deep learning-based prototype for automated assessment of the CVS in white matter MS lesions using data from three different imaging centers. We retrospectively analyzed data from 3 T magnetic resonance images acquired on four scanners from two different vendors, including adults with MS (n = 42), MS mimics (n = 33, encompassing 12 distinct neurological diseases mimicking MS) and uncertain diagnosis (n = 5). Brain white matter lesions were manually segmented on FLAIR* images. Perivenular assessment was performed according to consensus guidelines and used as ground truth, yielding 539 CVS-positive (CVS+ ) and 448 CVS-negative (CVS- ) lesions. A 3D convolutional neural network ("CVSnet") was designed and trained on 47 datasets, keeping 33 for testing. FLAIR* lesion patches of CVS+ /CVS- lesions were used for training and validation (n = 375/298) and for testing (n = 164/150). Performance was evaluated lesion-wise and subject-wise and compared with a state-of-the-art vesselness filtering approach through McNemar's test. The proposed CVSnet approached human performance, with lesion-wise median balanced accuracy of 81%, and subject-wise balanced accuracy of 89% on the validation set, and 91% on the test set. The process of CVS assessment, in previously manually segmented lesions, was ~ 600-fold faster using the proposed CVSnet compared with human visual assessment (test set: 4 seconds vs. 40 minutes). On the validation and test sets, the lesion-wise performance outperformed the vesselness filter method (P < 0.001). The proposed deep learning prototype shows promising performance in differentiating MS from its mimics. Our approach was evaluated using data from different hospitals, enabling larger multicenter trials to evaluate the benefit of introducing the CVS marker into MS diagnostic criteria.

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.

Human Leukocyte Antigen Genotype as a Marker of Multiple Sclerosis Prognosis.

OBJECTIVE: In a previous pilot monocentric study, we investigated the relation between human leukocyte antigen (HLA) genotype and multiple sclerosis (MS) disease progression over 2 years. HLA-A*02 allele was correlated with better outcomes, whereas HLA-B*07 and HLA-B*44 were correlated with worse outcomes. The objective of this extension study was to further investigate the possible association of HLA genotype with disease status and progression in MS as measured by sensitive and complex clinical and imaging parameters. METHODS: Hundred and forty-six MS patients underwent HLA typing. Over a 4-year period of follow-up, we performed three clinical and magnetic resonance imaging (MRI) assessments per patient, which respectively included Expanded Disability Status Scale, Multiple Sclerosis Severity Scale, Timed-25-Foot-Walk, 9-Hole Peg Test, Symbol Digit Modalities Test, Brief Visual Memory Test, California Verbal Learning Test-II, and whole-brain atrophy, fluid-attenuated inversion recovery (FLAIR) lesion volume change and number of new FLAIR lesions using icobrain. We then compared the clinical and MRI outcomes between predefined HLA patient groups. RESULTS: Results of this larger study with a longer follow-up are in line with what we have previously shown. HLA-A*02 allele is associated with potentially better MS outcomes, whereas HLA-B*07, HLA-B*44, HLA-B*08, and HLA-DQB1*06 with a potential negative effect. Results for HLA-DRB1*15 are inconclusive. CONCLUSION: In the era of MS treatment abundance, HLA genotype might serve as an early biomarker for MS outcomes to inform individualized treatment decisions.

Central vein sign differentiates Multiple Sclerosis from central nervous system inflammatory vasculopathies.

OBJECTIVES: In multiple sclerosis (MS), magnetic resonance imaging (MRI) is a sensitive tool for detecting white matter lesions, but its diagnostic specificity is still suboptimal; ambiguous cases are frequent in clinical practice. Detection of perivenular lesions in the brain (the "central vein sign") improves the pathological specificity of MS diagnosis, but comprehensive evaluation of this MRI biomarker in MS-mimicking inflammatory and/or autoimmune diseases, such as central nervous system (CNS) inflammatory vasculopathies, is lacking. In a multicenter study, we assessed the frequency of perivenular lesions in MS versus systemic autoimmune diseases with CNS involvement and primary angiitis of the CNS (PACNS). METHODS: In 31 patients with inflammatory CNS vasculopathies and 52 with relapsing-remitting MS, 3-dimensional T2*-weighted and T2-fluid-attenuated inversion recovery images were obtained during a single MRI acquisition after gadolinium injection. For each lesion, the central vein sign was evaluated according to consensus guidelines. For each patient, lesion count, volume, and brain location, as well as fulfillment of dissemination in space MRI criteria, were assessed. RESULTS: MS showed higher frequency of perivenular lesions (median = 88%) than did inflammatory CNS vasculopathies (14%), without overlap between groups or differences between 3T and 1.5T MRI. Among inflammatory vasculopathies, Behçet disease showed the highest median frequency of perivenular lesions (34%), followed by PACNS (14%), antiphospholipid syndromes (12%), Sjögren syndrome (11%), and systemic lupus erythematosus (0%). When a threshold of 50% perivenular lesions was applied, central vein sign discriminated MS from inflammatory vasculopathies with a diagnostic accuracy of 100%. INTERPRETATION: The central vein sign differentiates inflammatory CNS vasculopathies from MS at standard clinical magnetic field strengths. Ann Neurol 2018;83:283-294.

Magnetic resonance imaging of experimental autoimmune encephalomyelitis in the common marmoset.

Magnetic resonance imaging (MRI) is an invaluable tool for the diagnosis and monitoring of patients with multiple sclerosis (MS) as well as for the study of the disease pathophysiology. Because of its strong clinical, radiological and histopathological similarities with the human disease, experimental autoimmune encephalomyelitis (EAE) in the common marmoset has been studied more intensively over the past several years. Here, we review the current knowledge on MRI in the marmoset EAE, and we outline the physiopathological significance and translational values of these studies with respect to MS. Accumulating evidences suggest that the application of conventional, as well as non-conventional, MRI techniques in the marmoset EAE is a promising approach to elucidate the pathological processes underlying the development of inflammatory demyelinated lesions in the central nervous system, potentially improving the identification and development of new therapeutics.

SWI enhances vein detection using gadolinium in multiple sclerosis.

Susceptibility weighted imaging (SWI) combined with the FLAIR sequence provides the ability to depict in vivo the perivenous location of inflammatory demyelinating lesions - one of the most specific pathologic features of multiple sclerosis (MS). In addition, in MS white matter (WM) lesions, gadolinium-based contrast media (CM) can increase vein signal loss on SWI. This report focuses on two cases of WM inflammatory lesions enhancing on SWI images after CM injection. In these lesions in fact the CM increased the contrast between the parenchyma and the central vein allowing as well, in one of the two cases, the detection of a vein not visible on the same SWI sequence acquired before CM injection.