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INTRODUCTION:The existence of partial volume effects in brain MR images makes it challenging to understand physio-pathological alterations underlying signal changes due to pathology across groups of healthy subjects and patients. In this study, we implement a new approach to disentangle gray and white matter alterations in the thalamus and the basal ganglia. The proposed method was applied to a cohort of early multiple sclerosis (MS) patients and healthy subjects to evaluate tissue-specific alterations related to diffuse inflammatory or neurodegenerative processes. METHOD:Forty-three relapsing-remitting MS patients and nineteen healthy controls underwent 3T MRI including: (i) fluid-attenuated inversion recovery, double inversion recovery, magnetization-prepared gradient echo for lesion count, and (ii) T1 relaxometry. We applied a partial volume estimation algorithm to T1 relaxometry maps to gray and white matter local concentrations as well as T1 values characteristic of gray and white matter in the thalamus and the basal ganglia. Statistical tests were performed to compare groups in terms of both global T1 values, tissue characteristic T1 values, and tissue concentrations. RESULTS:Significant increases in global T1 values were observed in the thalamus (p = 0.038) and the putamen (p = 0.026) in RRMS patients compared to HC. In the Thalamus, the T1 increase was associated with a significant increase in gray matter characteristic T1 (p = 0.0016) with no significant effect in white matter. CONCLUSION:The presented methodology provides additional information to standard MR signal averaging approaches that holds promise to identify the presence and nature of diffuse pathology in neuro-inflammatory and neurodegenerative diseases.

The mechanisms leading to disability and the long-term efficacy and safety of disease modifying drugs (DMDs) in multiple sclerosis (MS) are unclear. We aimed at building a prospective cohort of MS patients with standardized collection of demographic, clinical, MRI data and body fluids that can be used to develop prognostic indicators and biomarkers of disease evolution and therapeutic response. The Swiss MS Cohort (SMSC) is a prospective observational study performed across seven Swiss MS centers including patients with MS, clinically isolated syndrome (CIS), radiologically isolated syndrome or neuromyelitis optica. Neurological and radiological assessments and biological samples are collected every 6-12 months. We recruited 872 patients (clinically isolated syndrome [CIS] 5.5%, relapsing-remitting MS [RRMS] 85.8%, primary progressive MS [PPMS] 3.5%, secondary progressive MS [SPMS] 5.2%) between June 2012 and July 2015. We performed 2,286 visits (median follow-up 398 days) and collected 2,274 serum, plasma and blood samples, 152 cerebrospinal fluid samples and 1,276 brain MRI scans. 158 relapses occurred and expanded disability status scale (EDSS) scores increased in PPMS, SPMS and RRMS patients experiencing relapses. Most RRMS patients were treated with fingolimod (33.4%), natalizumab (24.5%) or injectable DMDs (13.6%). The SMSC will provide relevant information regarding DMDs efficacy and safety and will serve as a comprehensive infrastructure available for nested research projects.

INTRODUCTION: Deficits in decision making (DM) are commonly associated with prefrontal cortical damage, but may occur with multiple sclerosis (MS). There are no data concerning the impact of MS on tasks evaluating DM under explicit risk, where different emotional and cognitive components can be distinguished. METHODS: We assessed 72 relapsing-remitting MS (RRMS) patients with mild to moderate disease and 38 healthy controls in two DM tasks involving risk with explicit rules: (1) The Wheel of Fortune (WOF), which probes the anticipated affects of decisions outcomes on future choices; and (2) The Cambridge Gamble Task (CGT) which measures risk taking. Participants also underwent a neuropsychological and emotional assessment, and skin conductance responses (SCRs) were recorded. RESULTS: In the WOF, RRMS patients showed deficits in integrating positive counterfactual information (p