Default Mode Network Structural Integrity and Cerebellar Connectivity Predict Information Processing Speed Deficit in Multiple Sclerosis

Cognitive impairment affects about 50% of multiple sclerosis (MS) patients, but the mechanisms underlying this remain unclear. The default mode network (DMN) has been linked with cognition, but in MS its role is still poorly understood. Moreover, within an extended DMN network including the cerebellum (CBL-DMN), the contribution of cortico-cerebellar connectivity to MS cognitive performance remains unexplored. The present study investigated associations of DMN and CBL-DMN structural connectivity with cognitive processing speed in MS, in both cognitively impaired (CIMS) and cognitively preserved (CPMS) MS patients. 68 MS patients and 22 healthy controls (HCs) completed a symbol digit modalities test (SDMT) and had 3T brain magnetic resonance imaging (MRI) scans that included a diffusion weighted imaging protocol. DMN and CBL-DMN tracts were reconstructed with probabilistic tractography. These networks (DMN and CBL-DMN) and the cortico-cerebellar tracts alone were modeled using a graph theoretical approach with fractional anisotropy (FA) as the weighting factor. Brain parenchymal fraction (BPF) was also calculated. In CIMS SDMT scores strongly correlated with the FA-weighted global efficiency (GE) of the network [GE(CBL-DMN): ρ = 0.87, R2 = 0.76, p < 0.001; GE(DMN): ρ = 0.82, R2 = 0.67, p < 0.001; GE(CBL): ρ = 0.80, R2 = 0.64, p < 0.001]. In CPMS the correlation between these measures was significantly lower [GE(CBL-DMN): ρ = 0.51, R2 = 0.26, p < 0.001; GE(DMN): ρ = 0.48, R2 = 0.23, p = 0.001; GE(CBL): ρ = 0.52, R2 = 0.27, p < 0.001] and SDMT scores correlated most with BPF (ρ = 0.57, R2 = 0.33, p < 0.001). In a multivariable regression model where SDMT was the independent variable, FA-weighted GE was the only significant explanatory variable in CIMS, while in CPMS BPF and expanded disability status scale were significant. No significant correlation was found in HC between SDMT scores, MRI or network measures. DMN structural GE is related to cognitive performance in MS, and results of CBL-DMN suggest that the cerebellum structural connectivity to the DMN plays an important role in information processing speed decline

Non-Linear Frequency Dependence of Neurovascular Coupling in the Cerebellar Cortex Implies Vasodilation-Vasoconstriction Competition

Neurovascular coupling (NVC) is the process associating local cerebral blood flow (CBF) to neuronal activity (NA). Although NVC provides the basis for the blood oxygen level dependent (BOLD) effect used in functional MRI (fMRI), the relationship between NVC and NA is still unclear. Since recent studies reported cerebellar non-linearities in BOLD signals during motor tasks execution, we investigated the NVC/NA relationship using a range of input frequencies in acute mouse cerebellar slices of vermis and hemisphere. The capillary diameter increased in response to mossy fiber activation in the 6-300 Hz range, with a marked inflection around 50 Hz (vermis) and 100 Hz (hemisphere). The corresponding NA was recorded using high-density multi-electrode arrays and correlated to capillary dynamics through a computational model dissecting the main components of granular layer activity. Here, NVC is known to involve a balance between the NMDAR-NO pathway driving vasodilation and the mGluRs-20HETE pathway driving vasoconstriction. Simulations showed that the NMDAR-mediated component of NA was sufficient to explain the time course of the capillary dilation but not its non-linear frequency dependence, suggesting that the mGluRs-20HETE pathway plays a role at intermediate frequencies. These parallel control pathways imply a vasodilation-vasoconstriction competition hypothesis that could adapt local hemodynamics at the microscale bearing implications for fMRI signals interpretation

An optimized framework for quantitative magnetization transfer imaging of the cervical spinal cord in vivo

Purpose To develop a framework to fully characterize quantitative magnetization transfer indices in the human cervical cord in vivo within a clinically feasible time. Methods A dedicated spinal cord imaging protocol for quantitative magnetization transfer was developed using a reduced field-of-view approach with echo planar imaging (EPI) readout. Sequence parameters were optimized based in the Cramer-Rao-lower bound. Quantitative model parameters (i.e., bound pool fraction, free and bound pool transverse relaxation times [ math formula, math formula], and forward exchange rate [kFB]) were estimated implementing a numerical model capable of dealing with the novelties of the sequence adopted. The framework was tested on five healthy subjects. Results Cramer-Rao-lower bound minimization produces optimal sampling schemes without requiring the establishment of a steady-state MT effect. The proposed framework allows quantitative voxel-wise estimation of model parameters at the resolution typically used for spinal cord imaging (i.e. 0.75 × 0.75 × 5 mm3), with a protocol duration of ∼35 min. Quantitative magnetization transfer parametric maps agree with literature values. Whole-cord mean values are: bound pool fraction = 0.11(±0.01), math formula = 46.5(±1.6) ms, math formula = 11.0(±0.2) µs, and kFB = 1.95(±0.06) Hz. Protocol optimization has a beneficial effect on reproducibility, especially for math formula and kFB. Conclusion The framework developed enables robust characterization of spinal cord microstructure in vivo using qMT. Magn Reson Med, 2017. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited

MAGNIMS recommendations for harmonization of MRI data in MS multicenter studies

There is an increasing need of sharing harmonized data from large, cooperative studies as this is essential to develop new diagnostic and prognostic biomarkers. In the field of multiple sclerosis (MS), the issue has become of paramount importance due to the need to translate into the clinical setting some of the most recent MRI achievements. However, differences in MRI acquisition parameters, image analysis and data storage across sites, with their potential bias, represent a substantial constraint. This review focuses on the state of the art, recent technical advances, and desirable future developments of the harmonization of acquisition, analysis and storage of large-scale multicentre MRI data of MS cohorts. Huge efforts are currently being made to achieve all the requirements needed to provide harmonized MRI datasets in the MS field, as proper management of large imaging datasets is one of our greatest opportunities and challenges in the coming years. Recommendations based on these achievements will be provided here. Despite the advances that have been made, the complexity of these tasks requires further research by specialized academical centres, with dedicated technical and human resources. Such collective efforts involving different professional figures are of crucial importance to offer to MS patients a personalised management while minimizing consumption of resource

Multi-centre and multi-vendor reproducibility of a standardized protocol for quantitative susceptibility Mapping of the human brain at 3T

: Quantitative Susceptibility Mapping (QSM) is an MRI-based technique allowing the non-invasive quantification of iron content and myelination in the brain. The RIN - Neuroimaging Network established an optimized and harmonized protocol for QSM across ten sites with 3T MRI systems from three different vendors to enable multicentric studies. The assessment of the reproducibility of this protocol is crucial to establish susceptibility as a quantitative biomarker. In this work, we evaluated cross-vendor reproducibility in a group of six traveling brains. Then, we recruited fifty-one volunteers and measured the variability of QSM values in a cohort of healthy subjects scanned at different sites, simulating a multicentric study. Both voxelwise and Region of Interest (ROI)-based analysis on cortical and subcortical gray matter were performed. The traveling brain study yielded high structural similarity (∼0.8) and excellent reproducibility comparing maps acquired on scanners from two different vendors. Depending on the ROI, we reported a quantification error ranging from 0.001 to 0.017 ppm for the traveling brains. In the cohort of fifty-one healthy subjects scanned at nine different sites, the ROI-dependent variability of susceptibility values, of the order of 0.005-0.025 ppm, was comparable to the result of the traveling brain experiment. The harmonized QSM protocol of the RIN - Neuroimaging Network provides a reliable quantification of susceptibility in both cortical and subcortical gray matter regions and it is ready for multicentric and longitudinal clinical studies in neurological and pychiatric diseases

Longitudinal metabolite changes in progressive multiple sclerosis:A study of 3 potential neuroprotective treatments

Background: 1 H-magnetic resonance spectroscopy (1 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 1 H-MRS and their association with clinical disability in SPMS. Study-type: Longitudinal. Population: 108 participants with SPMS randomized to receive neuroprotective drugs amiloride [mean age 55.4 (SD 7.4), 61% female], fluoxetine [55.6 (6.6), 71%], riluzole [54.6 (6.3), 68%], or placebo [54.8 (7.9), 67%]. Field strength/sequence: 3-Tesla. Chemical-shift-imaging 2D-point-resolved-spectroscopy (PRESS), 3DT1. Assessment: Brain metabolites in normal appearing white matter (NAWM) and gray matter (GM), brain volume, lesion load, nine-hole peg test (9HPT), and paced auditory serial addition test were measured at baseline and at 96-weeks. Statistical tests: Paired t-test was used to analyze metabolite changes in the placebo arm over 96-weeks. Metabolite differences between treatment arms and placebo; and associations between baseline metabolites and upper limb function/information processing speed at 96-weeks assessed using multiple linear regression models. P-value<0.05 was considered statistically significant. Results: In the placebo arm, tCho increased in GM (mean difference = -0.32 IU) but decreased in NAWM (mean difference = 0.13 IU). Compared to placebo, in the fluoxetine arm, mIns/tCr was lower (β = -0.21); in the riluzole arm, GM Glx (β = -0.25) and Glx/tCr (β = -0.29) were reduced. Baseline tNAA(β = 0.22) and tNAA/tCr (β = 0.23) in NAWM were associated with 9HPT scores at 96-weeks. Data conclusion: 1 H-MRS demonstrated altered membrane turnover over 96-weeks in the placebo group. It also distinguished changes in neuro-metabolites related to gliosis and glutaminergic transmission, due to fluoxetine and riluzole, respectively. Data show tNAA is a potential marker for upper limb function. Level of evidence: 1 TECHNICAL EFFICACY: Stage 4

Deep gray matter volume loss drives disability worsening in multiple sclerosis.

OBJECTIVE: Gray matter (GM) atrophy occurs in all multiple sclerosis (MS) phenotypes. We investigated whether there is a spatiotemporal pattern of GM atrophy that is associated with faster disability accumulation in MS. METHODS: We analyzed 3,604 brain high-resolution T1-weighted magnetic resonance imaging scans from 1,417 participants: 1,214 MS patients (253 clinically isolated syndrome [CIS], 708 relapsing-remitting [RRMS], 128 secondary-progressive [SPMS], and 125 primary-progressive [PPMS]), over an average follow-up of 2.41 years (standard deviation [SD] = 1.97), and 203 healthy controls (HCs; average follow-up = 1.83 year; SD = 1.77), attending seven European centers. Disability was assessed with the Expanded Disability Status Scale (EDSS). We obtained volumes of the deep GM (DGM), temporal, frontal, parietal, occipital and cerebellar GM, brainstem, and cerebral white matter. Hierarchical mixed models assessed annual percentage rate of regional tissue loss and identified regional volumes associated with time-to-EDSS progression. RESULTS: SPMS showed the lowest baseline volumes of cortical GM and DGM. Of all baseline regional volumes, only that of the DGM predicted time-to-EDSS progression (hazard ratio = 0.73; 95% confidence interval, 0.65, 0.82; p < 0.001): for every standard deviation decrease in baseline DGM volume, the risk of presenting a shorter time to EDSS worsening during follow-up increased by 27%. Of all longitudinal measures, DGM showed the fastest annual rate of atrophy, which was faster in SPMS (-1.45%), PPMS (-1.66%), and RRMS (-1.34%) than CIS (-0.88%) and HCs (-0.94%; p < 0.01). The rate of temporal GM atrophy in SPMS (-1.21%) was significantly faster than RRMS (-0.76%), CIS (-0.75%), and HCs (-0.51%). Similarly, the rate of parietal GM atrophy in SPMS (-1.24-%) was faster than CIS (-0.63%) and HCs (-0.23%; all p values <0.05). Only the atrophy rate in DGM in patients was significantly associated with disability accumulation (beta = 0.04; p < 0.001). INTERPRETATION: This large, multicenter and longitudinal study shows that DGM volume loss drives disability accumulation in MS, and that temporal cortical GM shows accelerated atrophy in SPMS than RRMS. The difference in regional GM atrophy development between phenotypes needs to be taken into account when evaluating treatment effect of therapeutic interventions. Ann Neurol 2018;83:210-222

Quantitative MRI Harmonization to Maximize Clinical Impact: The RIN-Neuroimaging Network

Neuroimaging studies often lack reproducibility, one of the cardinal features of the scientific method. Multisite collaboration initiatives increase sample size and limit methodological flexibility, therefore providing the foundation for increased statistical power and generalizable results. However, multisite collaborative initiatives are inherently limited by hardware, software, and pulse and sequence design heterogeneities of both clinical and preclinical MRI scanners and the lack of benchmark for acquisition protocols, data analysis, and data sharing. We present the overarching vision that yielded to the constitution of RIN-Neuroimaging Network, a national consortium dedicated to identifying disease and subject-specific in-vivo neuroimaging biomarkers of diverse neurological and neuropsychiatric conditions. This ambitious goal needs efforts toward increasing the diagnostic and prognostic power of advanced MRI data. To this aim, 23 Italian Scientific Institutes of Hospitalization and Care (IRCCS), with technological and clinical specialization in the neurological and neuroimaging field, have gathered together. Each IRCCS is equipped with high- or ultra-high field MRI scanners (i.e., ≥3T) for clinical or preclinical research or has established expertise in MRI data analysis and infrastructure. The actions of this Network were defined across several work packages (WP). A clinical work package (WP1) defined the guidelines for a minimum standard clinical qualitative MRI assessment for the main neurological diseases. Two neuroimaging technical work packages (WP2 and WP3, for clinical and preclinical scanners) established Standard Operative Procedures for quality controls on phantoms as well as advanced harmonized quantitative MRI protocols for studying the brain of healthy human participants and wild type mice. Under FAIR principles, a web-based e-infrastructure to store and share data across sites was also implemented (WP4). Finally, the RIN translated all these efforts into a large-scale multimodal data collection in patients and animal models with dementia (i.e., case study). The RIN-Neuroimaging Network can maximize the impact of public investments in research and clinical practice acquiring data across institutes and pathologies with high-quality and highly-consistent acquisition protocols, optimizing the analysis pipeline and data sharing procedures