Vascular risk factors are associated with grey matter atrophy in secondary progressive multiple sclerosis.

Background: Comorbidities including vascular risk factors can be associated with whole and regional brain atrophy in multiple sclerosis (MS). This has been examined in mixed MS cohorts in prospective or observational studies; however, the association between vascular comorbidities (VCM) in secondary progressive MS (SPMS) and brain atrophy has been less well studied. The aim was to investigate the cross-sectional and longitudinal association between VCM, comorbidity burden and brain atrophy in SPMS.

White Matter Magnetic Resonance Diffusion Measures in Multiple Sclerosis with Overactive Bladder.

Background: Lower urinary tract (LUT) symptoms are reported in more than 80% of patients with multiple sclerosis (MS), most commonly an overactive bladder (OAB). The relationship between brain white matter (WM) changes in MS and OAB symptoms is poorly understood.

Objectives: We aim to evaluate (i) microstructural WM differences across MS patients (pwMS) with OAB symptoms, patients without LUT symptoms, and healthy subjects using diffusion tensor imaging (DTI), and (ii) associations between clinical OAB symptom scores and DTI indices.

Investigating the relationship between thalamic iron concentration and disease severity in secondary progressive multiple sclerosis using quantitative susceptibility mapping: Cross-sectional analysis from the MS-STAT2 randomised controlled trial.

Background: Deep grey matter pathology is a key driver of disability worsening in people with multiple sclerosis. Quantitative susceptibility mapping (QSM) is an advanced magnetic resonance imaging (MRI) technique which quantifies local magnetic susceptibility from variations in phase produced by changes in the local magnetic field. In the deep grey matter, susceptibility has previously been validated against tissue iron concentration.

Multiscale modeling of neuronal dynamics in hippocampus CA1.

The development of biologically realistic models of brain microcircuits and regions constitutes currently a very relevant topic in computational neuroscience. One of the main challenges of such models is the passage between different scales, going from the microscale (cellular) to the meso (microcircuit) and macroscale (region or whole-brain level), while keeping at the same time a constraint on the demand of computational resources. In this paper we introduce a multiscale modeling framework for the hippocampal CA1, a region of the brain that plays a key role in functions such as learning, memory consolidation and navigation.

Finding the limits of deep learning clinical sensitivity with fractional anisotropy (FA) microstructure maps.

Background: Quantitative maps obtained with diffusion weighted (DW) imaging, such as fractional anisotropy (FA) -calculated by fitting the diffusion tensor (DT) model to the data,-are very useful to study neurological diseases. To fit this map accurately, acquisition times of the order of several minutes are needed because many noncollinear DW volumes must be acquired to reduce directional biases. Deep learning (DL) can be used to reduce acquisition times by reducing the number of DW volumes.

Quantification of water exchange across the blood-brain barrier using noncontrast MR fingerprinting.

Purpose: A method is proposed to quantify cerebral blood volume ( ) and intravascular water residence time ( ) using MR fingerprinting (MRF), applied using a spoiled gradient echo sequence without the need for contrast agent.

Methods: An in silico study optimized an acquisition protocol to maximize the sensitivity of the measurement to and changes. Its accuracy in the presence of variations in , , and was evaluated.

Systemic inflammation associates with and precedes cord atrophy in progressive multiple sclerosis.

In preclinical models of multiple sclerosis, systemic inflammation has an impact on the compartmentalized inflammatory process within the central nervous system and results in axonal loss. It remains to be shown whether this is the case in humans, specifically whether systemic inflammation contributes to spinal cord or brain atrophy in multiple sclerosis. Hence, an observational longitudinal study was conducted to delineate the relationship between systemic inflammation and atrophy using magnetic resonance imaging: the SIMS (Systemic Inflammation in Multiple Sclerosis) study.

UPDATE trial: investigating the effects of ultra-processed versus minimally processed diets following UK dietary guidance on health outcomes: a protocol for an 8-week community-based cross-over randomised controlled trial in people with overweight or obesity, followed by a 6-month behavioural intervention.

Introduction: Obesity increases the risk of morbidity and mortality. A major driver has been the increased availability of ultra-processed food (UPF), now the main UK dietary energy source. The UK Eatwell Guide (EWG) provides public guidance for a healthy balanced diet but offers no UPF guidance.

Visual Snow Syndrome Improves With Modulation of Resting-State Functional MRI Connectivity After Mindfulness-Based Cognitive Therapy: An Open-Label Feasibility Study.

Background: Visual snow syndrome (VSS) is associated with functional connectivity (FC) dysregulation of visual networks (VNs). We hypothesized that mindfulness-based cognitive therapy, customized for visual symptoms (MBCT-vision), can treat VSS and modulate dysfunctional VNs.

Methods: An open-label feasibility study for an 8-week MBCT-vision treatment program was conducted.

Structural and connectivity parameters reveal spared connectivity in young patients with non-progressive compared to slow-progressive cerebellar ataxia.

Introduction: Within Pediatric Cerebellar Ataxias (PCAs), patients with non-progressive ataxia (NonP) surprisingly show postural motor behavior comparable to that of healthy controls, differently to slow-progressive ataxia patients (SlowP). This difference may depend on the building of compensatory strategies of the intact areas in NonP brain network.

Methods: Eleven PCAs patients were recruited: five with NonP and six with SlowP.

2D sodium MRI of the human calf using half-sinc excitation pulses and compressed sensing.

Purpose: Sodium MRI can be used to quantify tissue sodium concentration (TSC) in vivo; however, UTE sequences are required to capture the rapidly decaying signal. 2D MRI enables high in-plane resolution but typically has long TEs. Half-sinc excitation may enable UTE; however, twice as many readouts are necessary.

Longitudinal Metabolite Changes in Progressive Multiple Sclerosis: A Study of 3 Potential Neuroprotective Treatments.

Background: H-magnetic resonance spectroscopy (H-MRS) may provide a direct index for the testing of medicines for neuroprotection and drug mechanisms in multiple sclerosis (MS) through measures of total N-acetyl-aspartate (tNAA), total creatine (tCr), myo-inositol (mIns), total-choline (tCho), and glutamate + glutamine (Glx). Neurometabolites may be associated with clinical disability with evidence that baseline neuroaxonal integrity is associated with upper limb function and processing speed in secondary progressive MS (SPMS).

Purpose: To assess the effect on neurometabolites from three candidate drugs after 96-weeks as seen by H-MRS and their association with clinical disability in SPMS.

A multi-layer mean-field model of the cerebellum embedding microstructure and population-specific dynamics.

Mean-field (MF) models are computational formalism used to summarize in a few statistical parameters the salient biophysical properties of an inter-wired neuronal network. Their formalism normally incorporates different types of neurons and synapses along with their topological organization. MFs are crucial to efficiently implement the computational modules of large-scale models of brain function, maintaining the specificity of local cortical microcircuits.

Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias.

Introduction: Neural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission.

Methods: We used TVB to simulate brain networks, which are key for human brain function, in Alzheimer's disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel pathological hallmarks.

Normative values of the topological metrics of the structural connectome: A multi-site reproducibility study across the Italian Neuroscience network.

Purpose: The use of topological metrics to derive quantitative descriptors from structural connectomes is receiving increasing attention but deserves specific studies to investigate their reproducibility and variability in the clinical context. This work exploits the harmonization of diffusion-weighted acquisition for neuroimaging data performed by the Italian Neuroscience and Neurorehabilitation Network initiative to obtain normative values of topological metrics and to investigate their reproducibility and variability across centers.

Methods: Different topological metrics, at global and local level, were calculated on multishell diffusion-weighted data acquired at high-field (e.

Cardiovascular risk factors in secondary progressive multiple sclerosis: A cross-sectional analysis from the MS-STAT2 randomized controlled trial.

Background And Purpose: There is increasing evidence that cardiovascular risk (CVR) contributes to disability progression in multiple sclerosis (MS). CVR is particularly prevalent in secondary progressive MS (SPMS) and can be quantified through validated composite CVR scores. The aim was to examine the cross-sectional relationships between excess modifiable CVR, whole and regional brain atrophy on magnetic resonance imaging, and disability in patients with SPMS.

Quality assessment, variability and reproducibility of anatomical measurements derived from T1-weighted brain imaging: The RIN-Neuroimaging Network case study.

Initiatives for the collection of harmonized MRI datasets are growing continuously, opening questions on the reliability of results obtained in multi-site contexts. Here we present the assessment of the brain anatomical variability of MRI-derived measurements obtained from T1-weighted images, acquired according to the Standard Operating Procedures, promoted by the RIN-Neuroimaging Network. A multicentric dataset composed of 77 brain T1w acquisitions of young healthy volunteers (mean age = 29.

Feasibility of in vivo multi-parametric quantitative magnetic resonance imaging of the healthy sciatic nerve with a unified signal readout protocol.

Magnetic resonance neurography (MRN) has been used successfully over the years to investigate the peripheral nervous system (PNS) because it allows early detection and precise localisation of neural tissue damage. However, studies demonstrating the feasibility of combining MRN with multi-parametric quantitative magnetic resonance imaging (qMRI) methods, which provide more specific information related to nerve tissue composition and microstructural organisation, can be invaluable. The translation of emerging qMRI methods previously validated in the central nervous system to the PNS offers real potential to characterise in patients in vivo the underlying pathophysiological mechanisms involved in a plethora of conditions of the PNS.

Patterns of inflammation, microstructural alterations, and sodium accumulation define multiple sclerosis subtypes after 15 years from onset.

Introduction: Conventional MRI is routinely used for the characterization of pathological changes in multiple sclerosis (MS), but due to its lack of specificity is unable to provide accurate prognoses, explain disease heterogeneity and reconcile the gap between observed clinical symptoms and radiological evidence. Quantitative MRI provides measures of physiological abnormalities, otherwise invisible to conventional MRI, that correlate with MS severity. Analyzing quantitative MRI measures through machine learning techniques has been shown to improve the understanding of the underlying disease by better delineating its alteration patterns.

Aberrant olfactory network functional connectivity in people with olfactory dysfunction following COVID-19 infection: an exploratory, observational study.

Background: Olfactory impairments and anosmia from COVID-19 infection typically resolve within 2-4 weeks, although in some cases, symptoms persist longer. COVID-19-related anosmia is associated with olfactory bulb atrophy, however, the impact on cortical structures is relatively unknown, particularly in those with long-term symptoms.

Methods: In this exploratory, observational study, we studied individuals who experienced COVID-19-related anosmia, with or without recovered sense of smell, and compared against individuals with no prior COVID-19 infection (confirmed by antibody testing, all vaccine naïve).

Multimodal Analysis of the Visual Pathways in Friedreich's Ataxia Reveals Novel Biomarkers.

Background: Optic neuropathy is a near ubiquitous feature of Friedreich's ataxia (FRDA). Previous studies have examined varying aspects of the anterior and posterior visual pathways but none so far have comprehensively evaluated the heterogeneity of degeneration across different areas of the retina, changes to the macula layers and combined these with volumetric MRI studies of the visual cortex and frataxin level.

Methods: We investigated 62 genetically confirmed FRDA patients using an integrated approach as part of an observational cohort study.