Spatial navigation involves multiple cognitive processes including multisensory integration, visuospatial coding, memory, and decision-making. These functions are mediated by the interplay of cerebral structures that can be broadly separated into a posterior network (subserving visual and spatial processing) and an anterior network (dedicated to memory and navigation planning). Within these networks, areas such as the hippocampus (HC) are known to be affected by aging and to be associated with cognitive decline and navigation impairments. However, age-related changes in brain connectivity within the spatial navigation network remain to be investigated. For this purpose, we performed a neuroimaging study combining functional and structural connectivity analyses between cerebral regions involved in spatial navigation. Nineteen young (μ = 27 years, σ = 4.3; 10 F) and 22 older (μ = 73 years, σ = 4.1; 10 F) participants were examined in this study. Our analyses focused on the parahippocampal place area (PPA), the retrosplenial cortex (RSC), the occipital place area (OPA), and the projections into the visual cortex of central and peripheral visual fields, delineated from independent functional localizers. In addition, we segmented the HC and the medial prefrontal cortex (mPFC) from anatomical images. Our results show an age-related decrease in functional connectivity between low-visual areas and the HC, associated with an increase in functional connectivity between OPA and PPA in older participants compared to young subjects. Concerning the structural connectivity, we found age-related differences in white matter integrity within the navigation brain network, with the exception of the OPA. The OPA is known to be involved in egocentric navigation, as opposed to allocentric strategies which are more related to the hippocampal region. The increase in functional connectivity between the OPA and PPA may thus reflect a compensatory mechanism for the age-related alterations around the HC, favoring the use of the preserved structural network mediating egocentric navigation. Overall, these findings on age-related differences of functional and structural connectivity may help to elucidate the cerebral bases of spatial navigation deficits in healthy and pathological aging.
Myelin loss is associated with axonal damage in established multiple sclerosis. This relationship is challenging to study in vivo in early disease. Here, we ask whether myelin loss is associated with axonal damage at diagnosis, by combining non-invasive neuroimaging and blood biomarkers. We performed quantitative microstructural MRI and single molecule ELISA plasma neurofilament measurement in 73 patients with newly diagnosed, immunotherapy naïve relapsing-remitting multiple sclerosis. Myelin integrity was evaluated using aggregate g-ratios, derived from magnetization transfer saturation (MTsat) and neurite orientation dispersion and density imaging (NODDI) diffusion data. We found significantly higher g-ratios within cerebral white matter lesions (suggesting myelin loss) compared with normal-appearing white matter (0.61 vs 0.57, difference 0.036, 95% CI 0.029 to 0.043, p < 0.001). Lesion volume (Spearman’s rho rs= 0.38, p < 0.001) and g-ratio (rs= 0.24 p < 0.05) correlated independently with plasma neurofilament. In patients with substantial lesion load (n = 38), those with higher g-ratio (defined as greater than median) were more likely to have abnormally elevated plasma neurofilament than those with normal g-ratio (defined as less than median) (11/23 [48%] versus 2/15 [13%] p < 0.05). These data suggest that, even at multiple sclerosis diagnosis, reduced myelin integrity is associated with axonal damage. MRI-derived g-ratio may provide useful additional information regarding lesion severity, and help to identify individuals with a high degree of axonal damage at disease onset. York, Martin et al. simultaneously measured g-ratio and plasma neurofilament in 73 relapsing-remitting multiple sclerosis patients at diagnosis using advanced MRI and single molecule ELISA. They demonstrate that g-ratio of cerebral white matter lesions varies at diagnosis, and show that high g-ratio of lesions is associated with elevated plasma neurofilament.
Background Recent findings from several studies have shown that paramagnetic rim lesions identified using susceptibility-based MRI could represent potential diagnostic and prognostic biomarkers in multiple sclerosis (MS). Here, we perform a systematic review and meta-analysis of the existing literature to assess their pooled prevalence at lesion-level and patient-level. Methods Both database searching (PubMed and Embase) and handsearching were conducted to identify studies allowing the lesion-level and/or patient-level prevalence of rim lesions or chronic active lesions to be calculated. Pooled prevalence was estimated using the DerSimonian-Laird random-effects model. Subgroup analysis and meta-regression were performed to explore possible sources of heterogeneity. PROSPERO registration: CRD42020192282. Results 29 studies comprising 1230 patients were eligible for analysis. Meta-analysis estimated pooled prevalences of 9.8% (95% CI: 6.6–14.2) and 40.6% (95% CI: 26.2–56.8) for rim lesions at lesion-level and patient-level, respectively. Pooled lesion-level and patient-level prevalences for chronic active lesions were 12.0% (95% CI: 9.0–15.8) and 64.8% (95% CI: 54.3–74.0), respectively. Considerable heterogeneity was observed across studies (I2>75%). Subgroup analysis revealed a significant difference in patient-level prevalence between studies conducted at 3T and 7T (p = 0.0312). Meta-regression analyses also showed significant differences in lesion-level prevalence with respect to age (p = 0.0018, R2 = 0.20) and disease duration (p = 0.0018, R2 = 0.48). Other moderator analyses demonstrated no significant differences according to MRI sequence, gender and expanded disability status scale (EDSS). Conclusion In this study, we show that paramagnetic rim lesions may be present in an important proportion of MS patients, notwithstanding significant variation in their assessment across studies. In view of their possible clinical relevance, we believe that clear guidelines should be introduced to standardise their assessment across research centres to in turn facilitate future analyses.
Synopsis Nitrogen, calcium, magnesium, boron and sulfur deficiencies appeared rapidly after the respective elements were withheld from the culture solution. Phosphorus, potassium, manganese, iron, copper, zinc and molybdenum supplied early in the season were sufficient to complete the life cycle although growth and fruit formation were reduced.
Multiple sclerosis (MS) is a chronic neuroinflammatory and neurodegenerative disease. MS prevalence varies geographically, both between and within countries and is notably high in Scotland. Disease trajectory varies significantly between individuals and the causes for this are largely unclear. Biomarkers predictive of disease course are urgently needed to allow improved stratification for current disease modifying therapies and future targeted treatments aimed at neuroprotection and remyelination, and as endpoints for clinical trials. Magnetic resonance imaging (MRI) can detect disease activity and underlying neurological damage non-invasively in vivo at the micro and macro structural level. FutureMS is a prospective Scottish longitudinal multi-centre cohort study which focuses on deeply phenotyping and genotyping patients with recently diagnosed relapsing-remitting MS (RRMS) to identify predictors of disease activity and severity. Neuroimaging is a central component of the study and provides two main primary endpoints for disease activity and neurodegeneration. The aim of the current paper is to provide an overview of MRI data acquisition, management and processing in FutureMS. MRI is acquired at baseline (N=431) and 1-year follow-up, in Dundee, Glasgow and Edinburgh (3T Siemens) and in Aberdeen (3T Philips), and managed and processed in Edinburgh. The core structural MRI protocol comprises T1-weighted, T2-weighted, 2D/3D FLAIR and proton density images. The original study primary imaging outcome measures are new/enlarging white matter lesions (WML) assessed by neuroradiological visual read and reduction in brain volume over one year. Secondary imaging outcomes comprise WML volume as an additional quantitative structural MRI outcome measure, rim lesions on susceptibility-weighted imaging (SWI), and microstructural MRI measures, including diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics, relaxometry, magnetisation transfer (MT) ratio, MT saturation and derived g-ratio measures. FutureMS aims to reduce uncertainty around disease course and allow for targeted treatment in RRMS by exploring the role of conventional and advanced MRI measures as biomarkers of disease severity and progression in a large population of RRMS patients in Scotland.
Myelin-sensitive MRI such as magnetisation transfer imaging has been widely used in multiple sclerosis. The influence of methodology and differences in disease subtype on imaging findings is, however, not well established. Here, we systematically review magnetisation transfer brain imaging findings in relapsing-remitting multiple sclerosis. We examine how methodological differences, disease effects and their interaction influence magnetisation transfer imaging measures. Articles published before 06/01/2021 were retrieved from online databases (PubMed, EMBASE and Web of Science) with search terms including ‘magnetisation transfer’ and ‘brain’ for systematic review, according to a pre-defined protocol. Only studies which used human in vivo quantitative magnetisation transfer imaging in adults with relapsing-remitting multiple sclerosis (with or without healthy controls) were included. Additional data from relapsing-remitting multiple sclerosis subjects acquired in other studies comprising mixed disease subtypes were included in meta-analyses. Data including sample size, MRI acquisition protocol parameters, treatments and clinical findings were extracted and qualitatively synthesised. Where possible, effect sizes were calculated for meta-analyses to determine magnetisation transfer (1) differences between patients and healthy controls; (2) longitudinal change; and, (3) relationships with clinical disability in relapsing-remitting multiple sclerosis. Eighty-six studies met inclusion criteria. MRI acquisition parameters varied widely, and were also underreported. The majority of studies examined the magnetisation transfer ratio in white matter, but magnetisation transfer metrics, brain regions examined and results were heterogeneous. Analysis demonstrated a risk of bias due to selective reporting and small sample sizes. The pooled random-effects meta-analysis across all brain compartments revealed magnetisation transfer ratio was 1.17 percent units [95% CI -1.42 to -0.91] lower in relapsing-remitting multiple sclerosis than healthy controls (z-value: -8.99, p<0.001, 46 studies). Linear mixed-model analysis did not show a significant longitudinal change in magnetisation transfer ratio across all brain regions (β=0.12 [-0.56 to 0.80], t-value=0.35, p=0.724, 14 studies) or normal-appearing white matter alone (β=0.037 [-0.14 to 0.22], t-value=0.41, p=0.68, 8 studies). There was a significant negative association between the magnetisation transfer ratio and clinical disability, as assessed by the Expanded Disability Status Scale (r=-0.32 [95% CI -0.46 to -0.17]; z-value=-4.33, p<0.001, 13 studies). Evidence suggests that magnetisation transfer imaging metrics are sensitive to pathological brain changes in relapsing-remitting multiple sclerosis, although effect sizes were small in comparison to inter-study variability. Recommendations include: better harmonised magnetisation transfer acquisition protocols with detailed methodological reporting standards; larger, well-phenotyped cohorts, including healthy controls; and, further exploration of techniques such as magnetisation transfer saturation or inhomogeneous magnetisation transfer ratio.
Purpose Rim lesions, characterised by a paramagnetic rim on susceptibility-based MRI, have been suggested to reflect chronic inflammatory demyelination in multiple sclerosis (MS) patients. Here, we assess, through susceptibility-weighted imaging (SWI), the prevalence, longitudinal volume evolution and clinical associations of rim lesions in subjects with early relapsing–remitting MS (RRMS). Methods Subjects (n = 44) with recently diagnosed RRMS underwent 3 T MRI at baseline (M0) and 1 year (M12) as part of a multi-centre study. SWI was acquired at M12 using a 3D segmented gradient-echo echo-planar imaging sequence. Rim lesions identified on SWI were manually segmented on FLAIR images at both time points for volumetric analysis. Results Twelve subjects (27%) had at least one rim lesion at M12. A linear mixed-effects model, with ‘subject’ as a random factor, revealed mixed evidence for the difference in longitudinal volume change between rim lesions and non-rim lesions (p = 0.0350 and p = 0.0556 for subjects with and without rim lesions, respectively). All 25 rim lesions identified showed T1-weighted hypointense signal. Subjects with and without rim lesions did not differ significantly with respect to age, disease duration or clinical measures of disability (p > 0.05). Conclusion We demonstrate that rim lesions are detectable in early-stage RRMS on 3 T MRI across multiple centres, although their relationship to lesion enlargement is equivocal in this small cohort. Identification of SWI rims was subjective. Agreed criteria for defining rim lesions and their further validation as a biomarker of chronic inflammation are required for translation of SWI into routine MS clinical practice.
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