Background

Background: Diffusion magnetic resonance imaging can reveal quantitative information about the tissue changes in multiple sclerosis. The recently developed multi-compartment spherical mean technique can map different microscopic properties based only on local diffusion signals, and it may provide specific information on the underlying microstructural modifications that arise in multiple sclerosis.

Objectives

Objective: Given that the lesions in multiple sclerosis may reflect different degrees of damage, we hypothesized that quantitative diffusion maps may help characterize the severity of lesions “in vivo” and correlate these to an individual’s clinical profile.

Methods

Methods: We evaluated a cohort of 59 MS patients (62% female, mean age 44.7 years), for whom demographic and disease information was obtained, and who underwent a comprehensive physical and cognitive evaluation. MRI protocol included conventional sequences to define focal lesions and multi-shell diffusion imaging. Quantitative diffusion properties were used to discriminate distinct types of lesions through a k-means clustering algorithm, and the number and volume of those lesions were correlated with parameters of the disease.

Results

Results: The combination of microscopic and macroscopic diffusion properties differentiated two types of lesions, with a prediction strength of 0.931. The type B lesions had larger diffusion changes compared to the type A lesions, irrespective of their location (P <0.001). The number and volume of type B lesions was related to the severity of disease evolution, clinical disability and cognitive decline (P =0.004, Bonferroni correction). Specifically, more and larger type B lesions were correlated with a worse Multiple Sclerosis Severity Score, cerebellar function and cognitive performance, and a greater need for high-efficacy treatments.

Conclusions

Conclusions: The severity of damage within focal lesions have the potential to permit more specific understanding of the mechanisms that drive disease evolution.

Background

People with MS present disruption of structural brain networks, but the differential characteristics of such changes among MS phenotypes and their clinical impact are not well elucidated.

Objectives

To characterize diffusion-based brain connectivity abnormalities in different MS phenotypes and their relation with disability in a large cohort of patients.

Methods

In this multicenter, retrospective, cross-sectional study, we collected clinical and brain MRI data from 344 patients with MS [median Expanded Disability Status Scale, EDSS 2.0 (range 0-7.0)] and 91 healthy volunteers (HV) from four MAGNIMS centers. Cognition was assessed with the Paced Auditory Serial Addition Test (PASAT) and Symbol Digits Modalities Test (SDMT) in 298 patients. We collected 3D-T1, FLAIR, diffusion-weighted images (DWI) and T2 or field maps acquisitions. FSL and ANTs packages were used to carry out DWI preprocessing and MRtrix software to generate connectivity matrices based on fractional anisotropy values. We computed six network measures (strength, global and local efficiency, clustering coefficient, assortativity and transitivity), and applied the ComBat tool to reduce inter-site variability. We calculated age-adjusted differences in graphs between groups using Mann-Whitney with FDR correction or Kruskal-Wallis with Dunn’s Test when necessary. Associations with clinical features were explored with Spearman’s rank correlation.

Results

Thirty-eight (11%) patients presented a clinically isolated syndrome (CIS), 262 (76%) had relapsing-remitting (RR) and 44 (13%) secondary progressive (SP) MS. CIS patients showed reduced global and local efficiency, clustering coefficient and transitivity compared to HV (corrected p<0.001), whilst RRMS did not differ from CIS patients. Compared with CIS and RRMS, patients with SPMS showed larger changes for the same previous graphs measures (corrected p<0.05), and lower strength than RRMS (corrected p=0.019).

In patients, reduced measures of strength, global and local efficiency, clustering and transitivity correlated with higher EDSS (rho:-0.12–-0.16, corrected p<0.034), lower PASAT (rho:0.26–0.30, corrected p<0.001) and worse SDMT scores (rho:0.28–0.32, corrected p<0.001).

Conclusions

Structural network integrity at the whole brain level is already widely reduced in people with MS from the earliest phases of the disease and becomes more abnormal in SPMS. Network modifications may contribute to the clinical manifestations of the disease.

Background

Magnetic resonance imaging (MRI) is widely used for the diagnosis and follow-up of patients with multiple sclerosis (MS). It is considered the most reliable and accurate paraclinical tool to evaluate disease activity and progression due to the high sensitivity to detect demyelinating lesions. Coordination between Neurology and Neuroradiology departments is essential to ensure that radiological studies are effectively performed and interpreted. However, in clinical practice, this coordination can be improved to maximize MS management and care.

Objectives

To establish a set of organizational recommendations focused on the coordination between neurologists and neuroradiologists to improve MS management in clinical practice.

Methods

A panel of 17 experts, including neurologists and neuroradiologists, from eight Spanish academic hospitals participated in the study. The Consensus Recommendation Guideline was conducted in four phases: 1) definition of the scope and methodology of the study; 2) review of the literature on good practices or recommendations in the use of MRI in MS; 3) discussion of drafted recommendations to achieve a consensus between the authors; 4) formalization and validation of the contents in a set of recommendations.

Results

We provide nine recommendations to improve the coordination between Neurology and Neuroradiology departments, which can be summarized as follows: 1) standardize the MRI requests, reports and schedules, 2) create shared protocols for MRI studies, 3) establish multidisciplinary working committees and coordination sessions, and 4) generate formal communication channels to improve the coordination between professionals from both departments. These recommendations are based on the available scientific evidence, international good practice guidelines and the experience of the panel experts.

Conclusions

We propose a series of recommendations expected to serve as a functional guide to implement improvements in the coordination between neurologists and neuroradiologists that will ultimately lead to improve the diagnosis and follow-up of MS patients.

Background

Clinical and imaging features of myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) may overlap with those of aquaporin 4-neuromyelitis optica spectrum disorder (AQP4-NMOSD) and relapsing remitting multiple sclerosis (RRMS). There is an unmet need for MRI biomarkers which reflect biological mechanisms involved in MOGAD and can help in the differential diagnosis.

Objectives

We aim to identify imaging features able to differentiate between non-acute MOG-antibody disease, AQP4-NMOSD and RRMS.

Methods

In this ongoing retrospective, cross-sectional MAGNIMS study, we analyzed data collected from 8 centers. All subjects (n=352) had brain and cervical cord 3T MRI. Quantification of MRI biomarkers included brain white matter lesions (WMLs), cortical lesions (CL), brain parenchymal fraction (BPF), white matter fraction (WMF), cortical and deep grey matter fractions (GMF) and cross-sectional cervical cord area (CSA) at C1-C2. Linear regression models were used to compare MRI measures between groups, corrected for age, sex, and centre. Statistical significance was considered when p was <0.05.

Results

91 patients with MOGAD (50F, mean age: 41yrs [±15]), 85 with AQP4-NMOSD (68F, 49yrs [±14]), 90 with RRMS (56F, 41yrs [±11]) and 87 healthy controls (HCs) (54F, 36yrs [±11.6]) were collected. The most common phenotypes at onset were optic neuritis and transverse myelitis in MOGAD (93%) and AQP4-NMOSD (87%). WMLs were detected in 57% MOGAD, 79% AQP4-NMOSD, all RRMS (100%) patients, and in 15% HCs. The mean lesion load and number of lesions were higher in RRMS than both MOGAD (p=0.007, p<0.001) and AQP4-NMOSD (p=0.001, p<0.001). At least one CL was seen in 8% patients with MOGAD (total n=8), 10% patients with AQP4-NMOSD (n=7), and in 69% patients with RRMS (n=150). All patient groups showed lower BPF than HCs, with lower WMF in MOGAD and RRMS than HCs (all p<0.01). Between groups, deep GMF was lower in RRMS than MOGAD (p<0.001) and AQP4-NMOSD (p=0.001). CSA was reduced in all disease groups when compared to HCs (all p<0.01) and lower in AQP4-NMOSD than RRMS (p=0.01).

Conclusions

This ongoing study indicates that MOGAD and AQP4-NMOSD share similar MRI features, and no specific MRI biomarker can distinguish between them. Patients with AQP4-NMOSD showed greater spinal cord atrophy than RRMS, and RRMS patients had a higher number of cortical lesions, and greater deep GM atrophy than AQP4-NMOSD and MOGAD. The next step is to investigate whether lesion distribution differs between the two antibody-mediated disease.

Background

Cognitive decline is frequent in patients with multiple sclerosis (MS). The cognitive trajectory is not well understood and a global overview throughout the disease course needs to be elucidated. Besides, predictors of future cognitive decline are still needed.

Objectives

We aim to (a) assess the temporal dynamics of cognitive function through disease course, and (b) explore different clinical and MRI predictors of cognitive decline in a large cohort of patients with MS.

Methods

Longitudinal study with 212 MS patients who performed a total of 605 neurological, cognitive and MRI examinations at different times of the disease [examinations per patient: 3 (IQR:2-3); baseline age: 40.2 (IQR:34.5-47.6) years; baseline disease duration: 8.2 (IQR:2.3-13.9) years]. A z-score for global cognition (z-BRB) and for each cognitive domain was obtained from the Rao's Battery, and a 3D-structural MRI was acquired to calculate regional gray matter (GM) volumes. We modelled the dynamics of cognition throughout the MS course using age at MS onset, education and sex adjusted mixed-effects linear spline models with knots at 5 and 15 years. An age and sex adjusted multivariate regression model was performed to determine which factors at the first examination best predict cognitive performance at last follow-up in the entire sample.

Results

In the first 5 years of MS, we detected an increase in z-BRB (β=0.050, p=0.004) and z-attention (β=0.048, p=0.013), followed by a decline in z-BRB (β=-0.029, p=0.005) and z-verbal memory (β=-0.049, p=0.001) between the 5-15 years of the disease. During the 15-30 years of MS course, the cognitive decline was maintained, but also involved z-attention (β=-0.035, p=0.012). Lower education, higher EDSS and volumetric changes at right parahippocampus, left parsorbitalis, left superior, left middle and right inferior temporal, and right superior parietal areas at the first examination were associated with worse z-BRB at the last follow-up (adjR2=0.48, β=-0.652–0.863, p=<0.001–0.024).

Conclusions

In MS, cognition deteriorates after the first 5 years of the disease, with a steady decline over the next 25 years. The verbal memory is affected earlier and more markedly, followed by involvement of attention and information processing speed. Moreover, education, clinical disability and GM volume at baseline are associated with future cognitive outcomes.

Background

Around 50% of patients with multiple sclerosis (MS) present a decline in cognitive behavior that impacts negatively on their autonomy, social and working skills. The benefits of cognitive rehabilitation on cognition and brain plasticity are not well understood due to methodological limitations of most studies, such the use of an inappropriate control group or the small number of patients included.

Objectives

To study the efficacy on attention, processing speed and working memory of a cognitive training program in patients with MS.

Methods

Multi-center, phase II, double-blind and randomized clinical trial to a treatment group (upward intensity training) or control group (low intensity static training). Patients were assessed using Rao's battery before and after 12 weeks of online training with the Guttmann, NeuroPersonalTrainer® (GNPT). The main objective was to demonstrate an improvement in attention and working memory tests (Pasat Auditory Serial Addition Test, PASAT, and Symbol Digit Modalities Test, SDMT) in the treatment group.

Results

The recruitment is still active. In an interim analysis on May 2020, 61 patients had been evaluated, of whom 35 fulfilled the inclusion criteria, and 23 had completed the follow-up period (age 48.8±7.4, disease duration 19.2±9.3 years). Ten patients had been assigned to the treatment group and 13 to the control group. The treatment group showed a significant reduction in z-scores of attention and working memory tests (z-score=-1.68±0.90 at baseline and -1.26±1.05 at follow up) compared to the control group (-1.78±0.63 at baseline and -1.45±1.06 at follow up), p corrected=0.003, and a trend for verbal memory (treatment group z-score -2.19±1.14 and -1.61±1.68 and sham group z-score -1.38±1.32 and -1.34±1.5 at baseline and follow up respectively, corrected p=0.074). There were no significant changes in other cognitive domains (verbal, visual, and fluency memory).

Conclusions

This preliminary analysis shows that intensive rehabilitation focused on attention, information processing speed and working memory can improve these cognitive functions.

Background

Background: Diffusion magnetic resonance imaging can reveal quantitative information about the tissue changes in multiple sclerosis. The recently developed multi-compartment spherical mean technique can map different microscopic properties based only on local diffusion signals, and it may provide specific information on the underlying microstructural modifications that arise in multiple sclerosis.

Objectives

Objective: Given that the lesions in multiple sclerosis may reflect different degrees of damage, we hypothesized that quantitative diffusion maps may help characterize the severity of lesions “in vivo” and correlate these to an individual’s clinical profile.

Methods

Methods: We evaluated a cohort of 59 MS patients (62% female, mean age 44.7 years), for whom demographic and disease information was obtained, and who underwent a comprehensive physical and cognitive evaluation. MRI protocol included conventional sequences to define focal lesions and multi-shell diffusion imaging. Quantitative diffusion properties were used to discriminate distinct types of lesions through a k-means clustering algorithm, and the number and volume of those lesions were correlated with parameters of the disease.

Results

Results: The combination of microscopic and macroscopic diffusion properties differentiated two types of lesions, with a prediction strength of 0.931. The type B lesions had larger diffusion changes compared to the type A lesions, irrespective of their location (P <0.001). The number and volume of type B lesions was related to the severity of disease evolution, clinical disability and cognitive decline (P =0.004, Bonferroni correction). Specifically, more and larger type B lesions were correlated with a worse Multiple Sclerosis Severity Score, cerebellar function and cognitive performance, and a greater need for high-efficacy treatments.

Conclusions

Conclusions: The severity of damage within focal lesions have the potential to permit more specific understanding of the mechanisms that drive disease evolution.

Background

Magnetic resonance imaging (MRI) is widely used for the diagnosis and follow-up of patients with multiple sclerosis (MS). It is considered the most reliable and accurate paraclinical tool to evaluate disease activity and progression due to the high sensitivity to detect demyelinating lesions. Coordination between Neurology and Neuroradiology departments is essential to ensure that radiological studies are effectively performed and interpreted. However, in clinical practice, this coordination can be improved to maximize MS management and care.

Objectives

To establish a set of organizational recommendations focused on the coordination between neurologists and neuroradiologists to improve MS management in clinical practice.

Methods

A panel of 17 experts, including neurologists and neuroradiologists, from eight Spanish academic hospitals participated in the study. The Consensus Recommendation Guideline was conducted in four phases: 1) definition of the scope and methodology of the study; 2) review of the literature on good practices or recommendations in the use of MRI in MS; 3) discussion of drafted recommendations to achieve a consensus between the authors; 4) formalization and validation of the contents in a set of recommendations.

Results

We provide nine recommendations to improve the coordination between Neurology and Neuroradiology departments, which can be summarized as follows: 1) standardize the MRI requests, reports and schedules, 2) create shared protocols for MRI studies, 3) establish multidisciplinary working committees and coordination sessions, and 4) generate formal communication channels to improve the coordination between professionals from both departments. These recommendations are based on the available scientific evidence, international good practice guidelines and the experience of the panel experts.

Conclusions

We propose a series of recommendations expected to serve as a functional guide to implement improvements in the coordination between neurologists and neuroradiologists that will ultimately lead to improve the diagnosis and follow-up of MS patients.