The relationship between white matter fiber damage and gray matter perfusion in large-scale functionally defined networks in multiple sclerosis

The Prevalence of Cognitive Impairment in Relapsing-Remitting Multiple Sclerosis: A Systematic Review and Meta-analysis

It is increasingly recognized that cognitive symptoms are a common sequelae of relapsing-remitting multiple sclerosis and are associated with adverse functional consequences. However, estimates of cognitive impairment (CIm) prevalence vary widely. This study aimed to determine the pooled prevalence of CIm among adults with RRMS and investigate moderators of prevalence rates. Following prospective registration (PROSPERO; CRD42021281815), electronic databases (Embase, Scopus, Medline, and PsycINFO) were searched from inception until March 2023. Eligible studies reported the prevalence of CIm among adults with RRMS, as determined through standardized neuropsychological testing and defined as evidence of reduced performance across at least two cognitive domains (e.g., processing speed, attention) relative to normative samples, healthy controls, or premorbid estimates. The electronic database search yielded 8695 unique records, of which 50 met selection criteria. The pooled prevalence of cognitive impairment was 32.5% (95% confidence interval 29.3-36.0%) across 5859 participants. Mean disease duration and age were significant predictors of cognitive impairment prevalence, with samples with longer disease durations and older age reporting higher prevalence rates. Studies which administered more extensive test batteries also reported significantly higher cognitive impairment prevalence. Approximately one third of adults with RRMS experience clinical levels of CIm. This finding supports the use of routine cognitive testing to enable early detection of CIm, and to identify individuals who may benefit from additional cognitive and functional support during treatment planning.

Relationship between MRI perfusion and clinical severity in multiple sclerosis

Perfusion alterations within several brain regions have been shown in multiple sclerosis patients using different magnetic resonance imaging (MRI) techniques. Furthermore, MRI-derived brain perfusion metrics have been investigated in association with multiple sclerosis phenotypes, physical disability, and cognitive impairment. However, a review focused on these aspects is still missing. Our aim was to review all the studies investigating the relationship between perfusion MRI and clinical severity during the last fifteen years to understand the clinical relevance of these findings. Perfusion differences among phenotypes were observed both with 1.5T and 3T scanners, with progressive multiple sclerosis presenting with lower perfusion values than relapsing-remitting multiple sclerosis patients. However, only 3T scanners showed a statistically significant distinction. Controversial results about the association between MRI-derived perfusion metrics and physical disability scores were found. However, the majority of the studies showed that lower brain perfusion and longer transit time are associated with more severe physical disability and worse cognitive performances.

Vascular aspects of multiple sclerosis: emphasis on perfusion and cardiovascular comorbidities

INTRODUCTION

Multiple sclerosis (MS) is a chronic inflammatory, demyelinating, and neurodegenerative disease of the central nervous system. Over the last two decades, more favorable MS long-term outcomes have contributed toward increase in prevalence of the aged MS population. Emergence of age-associated pathology, such as cardiovascular diseases, may interact with the MS pathophysiology and further contribute to disease progression. Areas covered: This review summarizes the cardiovascular involvement in MS pathology, its disease activity, and progression. The cardiovascular health, the presence of various cardiovascular diseases, and their effect on MS cognitive performance are further explored. In similar fashion, the emerging evidence of a higher incidence of extracranial arterial pathology and its association with brain MS pathology are discussed. Finally, the authors outline the methodologies behind specific perfusion magnetic resonance imaging (MRI) and ultrasound Doppler techniques, which allow measurement of disease-specific and age-specific vascular changes in the aging population and MS patients. Expert opinion: Cardiovascular pathology significantly contributes to worse clinical and MRI-derived disease outcomes in MS. Global and regional cerebral hypoperfusion may be associated with poorer physical and cognitive performance. Prevention, improved detection, and treatment of the cardiovascular-based pathology may improve the overall long-term health of MS patients.

Probabilistic White Matter Atlases of Human Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Visual and Visuospatial Networks

Background: Despite the popularity of functional connectivity analyses and the well-known topology of several intrinsic cortical networks, relatively little is known about the white matter regions (i.e., structural connectivity) underlying these networks. In the current study, we have therefore performed fMRI-guided diffusion tensor imaging (DTI) tractography to create probabilistic white matter atlases for eight previously identified functional brain networks, including the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks.

Methods: Whole-brain diffusion imaging data were acquired from a cohort of 32 healthy volunteers, and were warped to the ICBM template using a two-stage, high-dimensional, non-linear spatial normalization procedure. Deterministic tractography, with fractional anisotropy (FA) ≥0.15 and deviation angle <50°, was then performed using the Fiber Association by Continuous Tracking (FACT) algorithm, and a multi-ROI approach to identify tracts of interest. Regions-of-interest (ROIs) for each of the eight networks were taken from a pre-existing atlas of functionally defined regions to explore all ROI-to-ROI connections within each network, and all resulting streamlines were saved as binary masks to create probabilistic atlases (across participants) for tracts between each ROI-to-ROI pair.

Results: The resulting functionally-defined white matter atlases (i.e., for each tract and each network as a whole) were saved as NIFTI images in stereotaxic ICBM coordinates, and have been added to the UManitoba-JHU Functionally-Defined Human White Matter Atlas (http://www.nitrc.org/projects/uofm_jhu_atlas/).

Conclusion: To the best of our knowledge, this work represents the first attempt to comprehensively identify and map white matter connectomes for the Auditory, Basal Ganglia, Language, Precuneus, Sensorimotor, Primary Visual, Higher Visual and Visuospatial Networks. Therefore, the resulting probabilistic atlases represent a unique tool for future neuroimaging studies wishing to ascribe voxel-wise or ROI-based changes (i.e., in DTI or other quantitative white matter imaging signals) to these functional brain networks.