Applying multilayer analysis to morphological, structural, and functional brain networks to identify relevant dysfunction patterns

In recent years, research on network analysis applied to MRI data has advanced significantly. However, the majority of the studies are limited to single networks obtained from resting-state fMRI, diffusion MRI, or gray matter probability maps derived from T1 images. Although a limited number of previous studies have combined two of these networks, none have introduced a framework to combine morphological, structural, and functional brain connectivity networks. The aim of this study was to combine the morphological, structural, and functional information, thus defining a new multilayer network perspective. This has proved advantageous when jointly analyzing multiple types of relational data from the same objects simultaneously using graph- mining techniques. The main contribution of this research is the design, development, and validation of a framework that merges these three layers of information into one multilayer network that links and relates the integrity of white matter connections with gray matter probability maps and resting-state fMRI. To validate our framework, several metrics from graph theory are expanded and adapted to our specific domain characteristics. This proof of concept was applied to a cohort of people with multiple sclerosis, and results show that several brain regions with a synchronized connectivity deterioration could be identified

Sistema de vigilància de vacunes de Barcelona, VigiVacBcn

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Predictors of vision impairment in Multiple Sclerosis.

Visual impairment significantly alters the quality of life of people with Multiple Sclerosis (MS). The objective of this study was to identify predictors (independent variables) of visual outcomes, and to define their relationship with neurological disability and retinal atrophy when assessed by optical coherence tomography (OCT). We performed a cross-sectional analysis of 119 consecutive patients with MS, assessing vision using high contrast visual acuity (LogMar), 2.5% and 1.25% low contrast visual acuity (Sloan charts), and color vision (Hardy-Rand-Rittler plates). Quality of vision is a patient reported outcome based on an individual's unique perception of his or her vision and was assessed with the Visual Functioning Questionnaire-25 (VFQ-25) with the 10 neuro-ophthalmologic items. MS disability was assessed using the expanded disability status scale (EDSS), the MS functional composite (MSFC) and the brief repetitive battery-neuropsychology (BRB-N). Retinal atrophy was assessed using spectral domain OCT, measuring the thickness of the peripapillar retinal nerve fiber layer (pRNFL) and the volume of the ganglion cell plus inner plexiform layer (GCIPL). The vision of patients with MS was impaired, particularly in eyes with prior optic neuritis. Retinal atrophy (pRNFL and GCIPL) was closely associated with impaired low contrast vision and color vision, whereas the volume of the GCIPL showed a trend (p = 0.092) to be associated with quality of vision. Multiple regression analysis revealed that EDSS was an explanatory variable for high contrast vision after stepwise analysis, GCIPL volume for low contrast vision, and GCIPL volume and EDSS for color vision. The explanatory variables for quality of vision were high contrast vision and color vision. In summary, quality of vision in MS depends on the impairment of high contrast visual acuity and color vision due to the disease

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

Long-Term Stability of Neuroaxonal Structure in Alemtuzumab-Treated Relapsing-Remitting Multiple Sclerosis Patients

Background: Patients with multiple sclerosis (MS) experience progressive thinning in optical coherence tomography (OCT) measures of neuroaxonal structure regardless of optic neuritis history. Few prospective studies have investigated the effects of disease-modifying therapies on neuroaxonal degeneration in the retina. Alemtuzumab is a monoclonal antibody shown to be superior to interferon β-1a in treating relapsing-remitting MS (RRMS). The purpose of this study was to assess the effects of alemtuzumab and first-line injectable treatments on OCT measures of neuroaxonal structure including peripapillary retinal nerve fiber layer (RNFL) thickness and combined ganglion cell-inner plexiform (GCIP) layer volume in RRMS patients followed up over 5 years. Methods: In this retrospective pilot study with prospectively collected double cohort data, spectral domain OCT measures of RNFL thickness and GCIP volume were compared between alemtuzumab-treated RRMS patients (N = 24) and RRMS patients treated with either interferon-β or glatiramer acetate (N = 21). Results: Over a median of 60 months (range 42-60 months), the alemtuzumab cohort demonstrated a change in the mean RNFL thickness (thinning from baseline) of -0.88 μm (95% confidence interval [CI] -2.63 to 0.86; P = 0.32) and mean GCIP volume of +0.013 mm (95% CI -0.006 to 0.032; P = 0.18). Over the same time period, the first-line therapy-treated cohort demonstrated greater degrees of RNFL thinning (mean change in RNFL thickness was -3.65 μm [95% CI -5.40 to -1.89; P = 0.0001]). There was also more prominent GCIP volume loss relative to baseline in the first-line therapy group (-0.052 mm [95% CI -0.070 to -0.034; P < 0.0001]). Conclusions: Alemtuzumab-treated patients with RRMS demonstrated relative stability of OCT-measured neuroaxonal structure compared with RRMS patients treated with either interferon-β or glatiramer acetate over a 5-year period. These findings, along with previous demonstration of improved brain atrophy rates, suggest that alemtuzumab may offer long-term preservation of neuroaxonal structure in patients with RRMS

Long-Term Stability of Neuroaxonal Structure in Alemtuzumab-Treated Relapsing-Remitting Multiple Sclerosis Patients

Background: Patients with multiple sclerosis (MS) experience progressive thinning in optical coherence tomography (OCT) measures of neuroaxonal structure regardless of optic neuritis history. Few prospective studies have investigated the effects of disease-modifying therapies on neuroaxonal degeneration in the retina. Alemtuzumab is a monoclonal antibody shown to be superior to interferon β-1a in treating relapsing-remitting MS (RRMS). The purpose of this study was to assess the effects of alemtuzumab and first-line injectable treatments on OCT measures of neuroaxonal structure including peripapillary retinal nerve fiber layer (RNFL) thickness and combined ganglion cell-inner plexiform (GCIP) layer volume in RRMS patients followed up over 5 years. Methods: In this retrospective pilot study with prospectively collected double cohort data, spectral domain OCT measures of RNFL thickness and GCIP volume were compared between alemtuzumab-treated RRMS patients (N = 24) and RRMS patients treated with either interferon-β or glatiramer acetate (N = 21). Results: Over a median of 60 months (range 42-60 months), the alemtuzumab cohort demonstrated a change in the mean RNFL thickness (thinning from baseline) of -0.88 μm (95% confidence interval [CI] -2.63 to 0.86; P = 0.32) and mean GCIP volume of +0.013 mm (95% CI -0.006 to 0.032; P = 0.18). Over the same time period, the first-line therapy-treated cohort demonstrated greater degrees of RNFL thinning (mean change in RNFL thickness was -3.65 μm [95% CI -5.40 to -1.89; P = 0.0001]). There was also more prominent GCIP volume loss relative to baseline in the first-line therapy group (-0.052 mm [95% CI -0.070 to -0.034; P < 0.0001]). Conclusions: Alemtuzumab-treated patients with RRMS demonstrated relative stability of OCT-measured neuroaxonal structure compared with RRMS patients treated with either interferon-β or glatiramer acetate over a 5-year period. These findings, along with previous demonstration of improved brain atrophy rates, suggest that alemtuzumab may offer long-term preservation of neuroaxonal structure in patients with RRMS