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The COVID-19 pandemic and its lockdown in March 2020 have led to changes in lifestyle and heightened levels of anxiety, depression, and fatigue. This survey examined the factors (affective state, sleep quality, daily activities, mental load, work-related variables) influencing mental and physical fatigue during lockdown and how these relations have evolved one year later. A cohort of 430 workers and 124 retirees were recruited in April-May 2020 (lockdown period, dataset 1), and a subsample (133 workers and 40 retirees) completed the same questionnaire in April-May 2021 (dataset 2). Generalized linear mixed model (GLMM) analyses showed a significant subjective increase in both physical and mental fatigue in both worker and retiree groups during lockdown, and a supplementary increase in physical fatigue and anxiety level at spring 2021 compared to the lockdown period. During lockdown, anxiety level, concerns about COVID-19, work flexibility, mental load, and sleep metrics were associated with the evolution of fatigue among workers. For retirees, only anxiety and physical activity levels were linked to changes in physical fatigue. In April-May 2021, the only associations which remained significant were those in workers between fatigue and anxiety level and workload. These findings suggest that factors accounting for an increased fatigue level during the lockdown seems to be related to the rapid lifestyle adjustments to the sanitary crisis. On the other hand, the increase in fatigue observed one year after the beginning of the pandemic seems to result from more psychological factors associated to the health situation.

Introduction:Quantitative MRI quantifies tissue microstructural properties and supports the characterization of cerebral tissue damages. With an MPM protocol, 4 parameter maps are constructed: MTsat, PD, R1 and R2*, reflecting tissue physical properties associated with iron and myelin contents. Thus, qMRI is a good candidate for in vivo monitoring of cerebral damage and repair mechanisms related to MS. Here, we used qMRI to investigate the longitudinal microstructural changes in MS brain.Methods: Seventeen MS patients (age 25-65, 11 RRMS) were scanned on a 3T MRI, in two sessions separated with a median of 30 months, and the parameters evolution was evaluated within several tissue classes: NAWM, NACGM and NADGM, as well as focal WM lesions. An individual annual rate of change for each qMRI parameter was computed, and its correlation to clinical status was evaluated. For WM plaques, three areas were defined, and a GLMM tested the effect of area, time points, and their interaction on each median qMRI parameter value.Results: Patients with a better clinical evolution, that is, clinically stable or improving state, showed positive annual rate of change in MTsat and R2* within NAWM and NACGM, suggesting repair mechanisms in terms of increased myelin content and/or axonal density as well as edema/inflammation resorption. When examining WM lesions, qMRI parameters within surrounding NAWM showed microstructural modifications, even before any focal lesion is visible on conventional FLAIR MRI. Conclusion:The results illustrate the benefit of multiple qMRI data in monitoring subtle changes within normal appearing brain tissues and plaque dynamics in relation with tissue repair or disease progression.Emilie Lommers and Christophe Phillips equally contributed to the work.

Objectives: Contrary to conventional MRI (cMRI), quantitative MRI (qMRI) quantifies tissue physical microstructural properties and improves the characterization of cerebral damages in relation with various neurological diseases. With a multi-parameter mapping (MPM) protocol, 4 parameter maps are constructed: saturated magnetization transfer (MTsat), proton density (PD), longitudinal relaxation (R1) and effective transverse relaxation (R2*) rates, reflecting tissue physical properties associated with iron and myelin contents. Here, we used qMRI to investigate the microstructural changes happening over time in multiple sclerosis (MS). Methods: Seventeen MS patients (age 25-65, 11 RRMS) were scanned on a 3T MRI, with at least one year separation between two acquisition sessions, and the evolution of their parameters was evaluated within several tissue classes: normal-appearing white matter (NAWM), normal-appearing cortical and deep gray matter (NACGM and NADGM) as well as focal white matter (WM) lesions. Brain tissue segmentation was performed using US-with-Lesion, an adapted version of the Unified Segmentation (US) algorithm accounting for the lesion tissue class, based on qMRI and FLAIR images. An individual annual rate of change for each qMRI parameter was computed, and its correlation to clinical status was evaluated. As for WM plaques, three areas were defined within them. A Generalized Linear Mixed Model (GLMM) tested the effect of area and time points, as well as their interaction on each median qMRI parameter value. Results: Patients with a better clinical evolution showed positive annual rate of change in MT and R2* within NAWM and NACGM, suggesting repair mechanisms in terms of increased myelin content and/or axonal density. When examining focal WM lesions, qMRI parameters within surrounding NAWM showed modification in terms of reduction in MT, R1 and R2* combined with increased of PD even before any focal lesion is visible on conventional FLAIR MRI. Conclusion: The results illustrate the benefit of multiple qMRI data in monitoring subtle changes within normal appearing brain tissues and plaque dynamics in relation with tissue repair or disease progression.

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