IRM de diffusion

L’IRM de diffusion est une technique basée sur l' (IRM). Elle permet de calculer en chaque point de l'image la distribution des directions de diffusion des molécules d'eau. Cette diffusion étant contrainte par les tissus environnants, cette modalité d'imagerie permet d'obtenir indirectement la position, l’orientation et l’anisotropie des structures fibreuses, notamment les faisceaux de matière blanche du cerveau. Diffusion des molécules d’eau Le signal de résonance magnétique provient le plus souvent en IRM des noyaux d’hydrogène (protons). L’eau étant le constituant majoritaire des tissus biologiques, ce sont les protons des molécules d’eau qui contribuent majoritairement au signal. C’est donc essentiellement la diffusion des molécules d’eau qui est observée par l’IRM de diffusion. Diffusion isotrope Du fait que les tissus biologiques ont une température non nulle, les molécules d’eau y subissent un mouvement de diffusion à cause de l'agitation thermique. Dan

Neurite Exchange Imaging ((NEXI): A minimal model of diffusion in gray matter with inter-compartment water exchange

Alexandre Jean François Marie De Skowronski, Ileana Ozana Jelescu

Biophysical models of diffusion in white matter have been center-stage over the past two decades and are essentially based on what is now commonly referred to as the "Standard Model" (SM) of non-exchanging anisotropic compartments with Gaussian diffusion. In this work, we focus on diffusion MRI in gray matter, which requires rethinking basic microstructure modeling blocks. In particular, at least three contributions beyond the SM need to be considered for gray matter: water exchange across the cell membrane - between neurites and the extracellular space; non-Gaussian diffusion along neuronal and glial processes - resulting from structural disorder; and signal contribution from soma. For the first contribution, we propose Neurite Exchange Imaging (NEXI) as an extension of the SM of diffusion, which builds on the anisotropic Karger model of two exchanging compartments. Using datasets acquired at multiple diffusion weightings (b) and diffusion times (t) in the rat brain in vivo, we investigate the suitability of NEXI to describe the diffusion signal in the gray matter, compared to the other two possible contributions. Our results for the diffusion time window 20-45 ms show minimal diffusivity time-dependence and more pronounced kurtosis decay with time, which is well fit by the exchange model. Moreover, we observe lower signal for longer diffusion times at high b. In light of these observations, we identify exchange as the mechanism that best explains these signal signatures in both low-b and high-b regime, and thereby propose NEXI as the minimal model for gray matter microstructure mapping. We finally highlight multi-b multi-t acquisition protocols as being best suited to estimate NEXI model parameters reliably. Using this approach, we estimate the inter-compartment water exchange time to be 15 - 60 ms in the rat cortex and hippocampus in vivo, which is of the same order or shorter than the diffusion time in typical diffusion MRI acquisitions. This suggests water exchange as an essential component for interpreting diffusion MRI measurements in gray matter.

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Mapping of Structure-Function Age-Related Connectivity Changes on Cognition Using Multimodal MRI

Maria Giulia Preti, Dimitri Nestor Alice Van De Ville

The relationship between age-related changes in brain structural connectivity (SC) and functional connectivity (FC) with cognition is not well understood. Furthermore, it is not clear whether cognition is represented via a similar spatial pattern of FC and SC or instead is mapped by distinct sets of distributed connectivity patterns. To this end, we used a longitudinal, within-subject, multimodal approach aiming to combine brain data from diffusion-weighted MRI (DW-MRI), and functional MRI (fMRI) with behavioral evaluation, to better understand how changes in FC and SC correlate with changes in cognition in a sample of older adults. FC and SC measures were derived from the multimodal scans acquired at two time points. Change in FC and SC was correlated with 13 behavioral measures of cognitive function using Partial Least Squares Correlation (PLSC). Two of the measures indicate an age-related change in cognition and the rest indicate baseline cognitive performance. FC and SC-cognition correlations were expressed across several cognitive measures, and numerous structural and functional cortical connections, mainly cingulo-opercular, dorsolateral prefrontal, somatosensory and motor, and temporo-parieto-occipital, contributed both positively and negatively to the brain-behavior relationship. Whole-brain FC and SC captured distinct and independent connections related to the cognitive measures. Overall, we examined age-related function-structure associations of the brain in a comprehensive and integrated manner, using a multimodal approach. We pointed out the behavioral relevance of age-related changes in FC and SC. Taken together, our results highlight that the heterogeneity in distributed FC and SC connectivity patterns provide unique information about the variable nature of healthy cognitive aging.

FRONTIERS MEDIA SA2022

Neurite Exchange Imaging ((NEXI): A minimal model of diffusion in gray matter with inter-compartment water exchange

Alexandre Jean François Marie De Skowronski, Ileana Ozana Jelescu

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Neurite Exchange Imaging ((NEXI): A minimal model of diffusion in gray matter with inter-compartment water exchange

Identification des facteurs de succès du commerce électronique B2B; estimation de sa diffusion et de son impact

Mapping of Structure-Function Age-Related Connectivity Changes on Cognition Using Multimodal MRI

Neurite Exchange Imaging ((NEXI): A minimal model of diffusion in gray matter with inter-compartment water exchange

Identification des facteurs de succès du commerce électronique B2B; estimation de sa diffusion et de son impact

Mapping of Structure-Function Age-Related Connectivity Changes on Cognition Using Multimodal MRI