Diffusion tensor imaging (DTI) studies have provided much evidence of white and subcortical gray matter changes during late childhood and early adolescence that suggest increasing myelination, axon density, and/or fiber coherence. Neurite orientation dispersion and density imaging (NODDI) can be used to further characterize development in white and subcortical grey matter regions in the brain by improving specificity of the MRI signal compared to conventional DTI. We used measures from NODDI and DTI to examine white and subcortical gray matter development in a group of 27 healthy participants aged 8–13 years. Neurite density index (NDI) was strongly correlated with age in nearly all regions, and was more strongly associated with age than fractional anisotropy (FA). No significant correlations were observed between orientation dispersion index (ODI) and age. This suggests that white matter and subcortical gray matter changes during late childhood and adolescence are dominated by changes in neurite density (i.e., axon density and myelination), rather than increasing coherence of axons. Within brain regions, FA was correlated with both ODI and NDI while mean diffusivity was only related to neurite density, providing further information about the structural variation across individuals. Data-driven clustering of the NODDI parameters showed that microstructural profiles varied along layers of white matter, but that that much of the white and subcortical gray matter matured in a similar manner. Clustering highlighted isolated brain regions with decreasing NDI values that were not apparent in region-of-interest analysis. Overall, these results help to more specifically understand patterns of white and gray matter development during late childhood and early adolescence.
Sensitive and specific biomarkers of myelin can help define baseline brain health and development, identify and monitor disease pathology, and evaluate response to treatment where myelin content is affected. Diffusion measures such as radial diffusivity (RD) are commonly used to assess myelin content, but are not specific to myelin. Inhomogeneous magnetization transfer (ihMT) and multicomponent driven equilibrium single-pulse observation of T1 and T2 (mcDESPOT) offer quantitative parameters (qihMT and myelin volume fraction/VF, respectively) which are suggested to have improved sensitivity to myelin. We compared RD, qihMT, and VF in a cohort of 23 healthy children aged 8-13 years to evaluate the similarities and differences across these measures. All 3 measures were significantly related across brain voxels, but VF and qihMT were significantly more strongly correlated (qihMT-VF r = 0.89) than either measure was with RD (RD-qihMT r = -0.66, RD-VF r = -0.74; all p < 0.001). Mean parameters differed in several regions, especially in subcortical gray matter. These differences can likely be explained by unique sensitivities of each measure to non-myelin factors, such as crossing fiber geometry, axonal packing, fiber orientation, glial density, or magnetization transfer effects in a voxel. We also observed an orientation dependence of qihMT in white matter, such that qihMT decreased as fiber orientation went from parallel to perpendicular to B. All measures appear to be sensitive to myelin content, though qihMT and VF appear to be more specific to it than RD. Scan time, noise tolerance, and resolution requirements may inform researchers of the appropriate measure to choose for a specific application.
Introduction: Young children are often unable to remain still for magnetic resonance imaging (MRI), leading to unusable images. Various preparation methods may increase success, though it is unclear which factors best predict success. Here, in a retrospective sample, we describe factors associated with successful scanning in unsedated young children. We hypothesized that the mock scanner training and fewer behavior problems would result in higher success rates.Methods: We recruited 134 children aged 2.0–5.0 years for an MRI study. We compared success between children whose parents opted for mock scanner training (n = 20) or not (n = 114), and evaluated demographic and cognitive factors that predicted success.Results: Ninety-seven children (72%) completed at least one MRI sequence successfully on their first try; 64 children (48%) provided high-quality data for all 3 structural imaging sequences. Cognitive scores were higher in successful than unsuccessful children. Children who received mock scanner training were no more likely to be successful than children without, though they had slightly higher scores on T1 image quality.Conclusions: Our data shows that scanning with minimial preparation is possible in young children, and suggests limited advantages of mock scanner preparation for healthy young children.Cognitive ability may predict success.
Objective. Young children are often unable to remain still for magnetic resonance imaging (MRI).Various preparation methods have been reported to avoid sedation or anesthesia, with mixed success rates and feasibility. Here we describe a time-efficient preparation method and factors associated with successful scanning in young chdilren.We recruited 134 children aged 2.0-5.0 years for an MRI study. Some children completed a training session on a mock scanner, and all children received a 15-20 minute introduction to scanning procedures immediately before their scan. We compared success between children receiving mock scanner training or not, and evaluated demographic or cognitive factors that predicted success.Results. 97 children (72%) completed at least one sequence successfully; 64 children provided highquality data for all 3 sequences. Cognitive scores were higher in successful children, but children who received mock scanner training were less likely to be successful. A case-controlled comparison of children matched on age, gender, and cognitive scores found no differences between children receiving training or not.We present a quick method for preparing young children for awake MRI scans. Our data suggests limited advantages of mock scanner preparation for healthy young children, and that cognitive abilities may help predict success.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.