Diffusion-weighted MR Imaging in the Brain in Children: Findings in the Normal Brain and in the Brain with White Matter Diseases

Engelbrecht, V.; Scherer, A.; Rassek, Margarethe; Witsack, Hans J; Mödder, Ulrich

doi:10.1148/radiol.2222010492

Cited by 178 publications

(120 citation statements)

References 26 publications

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“…The present observation of significant age-related increase in FA of the CC is consistent with that reported in other studies. 8,27,28 Especially, the present work confirms the findings of Snook et al, 26 with a decided age group within a larger time period: FAgCC and FAsCC values revealed different dynamics of age dependence. Starting with a value of 0.48 at 2 months of age, the FAgCC increases remarkably until 5 years of age, with a value of 0.8, and remains nearly constant thereafter.…”

Section: Discussionsupporting

confidence: 90%

Evidence of Rapid Ongoing Brain Development Beyond 2 Years of Age Detected by Fiber Tracking

Ding

Sun²,

Braaß³

et al. 2008

AJNR Am J Neuroradiol

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Section: Discussionsupporting

confidence: 90%

Evidence of Rapid Ongoing Brain Development Beyond 2 Years of Age Detected by Fiber Tracking

Ding

Sun²,

Braaß³

et al. 2008

AJNR Am J Neuroradiol

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“…As demonstrated previously, white matter ADCs decrease logarithmically with age, but changes after 24 mo are essentially linear and weak when investigated with standard diffusion imaging methods using a b-value of 1,000 s/mm 2 or below (34,36,37). For each subject we computed the average ADC and FA at b = 1,000 s/mm 2 and average ADC at b = 3,000 s/mm 2 over all connections and plotted the results according to developmental age ( Fig.…”

Section: Resultssupporting

confidence: 63%

White matter maturation reshapes structural connectivity in the late developing human brain

Hagmann

Sporns²,

Madan³

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

635

592

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From toddler to late teenager, the macroscopic pattern of axonal projections in the human brain remains largely unchanged while undergoing dramatic functional modifications that lead to network refinement. These functional modifications are mediated by increasing myelination and changes in axonal diameter and synaptic density, as well as changes in neurochemical mediators. Here we explore the contribution of white matter maturation to the development of connectivity between ages 2 and 18 y using high b-value diffusion MRI tractography and connectivity analysis. We measured changes in connection efficacy as the inverse of the average diffusivity along a fiber tract. We observed significant refinement in specific metrics of network topology, including a significant increase in node strength and efficiency along with a decrease in clustering. Major structural modules and hubs were in place by 2 y of age, and they continued to strengthen their profile during subsequent development. Recording resting-state functional MRI from a subset of subjects, we confirmed a positive correlation between structural and functional connectivity, and in addition observed that this relationship strengthened with age. Continuously increasing integration and decreasing segregation of structural connectivity with age suggests that network refinement mediated by white matter maturation promotes increased global efficiency. In addition, the strengthening of the correlation between structural and functional connectivity with age suggests that white matter connectivity in combination with other factors, such as differential modulation of axonal diameter and myelin thickness, that are partially captured by inverse average diffusivity, play an increasingly important role in creating brain-wide coherence and synchrony.connectome | development | graph | network dynamics | tractography M ost real-world networks do not arise all at once but, guided by rules, develop through a growth process that progressively fine-tunes the configuration of nodes and edges. Thus, an important aspect in the analysis of large-scale networks is the characterization of their dynamic development and evolution. From a theoretical point of view growth rules have been shown to have a significant effect on the emergent behavior of the final large-scale structural topology. For example, the emergence of scale-free networks can be explained by a preferential attachment rule (1, 2), with important functional consequences (3). If we can measure the growth and reshaping of connectivity that occurs with maturation during the developmental process, we can begin to infer growth rules governing this complex process and examine their functional consequences. These growth rules need to be instantiated in a biological system, and therefore the functional consequences would provide hypotheses linking emergent network properties to underlying cellular and molecular mechanisms.Real-world networks rarely grow according to simple statistical models, thus necessitating empirical sampling ov...

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“…[4], ␣ now represents the respective angle between the rotated x-axes of voxels A and B. The first two terms in Eq.…”

Section: Theorymentioning

confidence: 99%

“…The first two terms in Eq. [4] are anisotropy terms; they are 0 for f a ϭ 1 or f b ϭ 1, respectively, and monotonically increase with f a(b) . This is plotted in Fig.…”

Section: Theorymentioning

confidence: 99%

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A correlative measure for processing multiangle diffusion‐weighted images

Pipe

Farthing

2003

Magnetic Resonance in Med

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A simple metric for the shared diffusion anisotropy between two voxels is proposed. The metric has large values when the diffusion is highly anisotropic in both voxels and oriented in the same direction. This metric can be used in several ways, three of which are illustrated in this article. First, the metric can be used to rapidly calculate a fractional anisotropy measure using an arbitrary number of measured diffusion values. Second, a simple way to exploit the metric for filtering DWI data with neighboring voxels with similar diffusion characteristics is shown. Third, the metric can be used to create color images that reflect tract orientation. The measurements from multiangle diffusion-weighted imaging (DWI) studies in white matter are rich with information and a great deal of research is being performed in extracting relevant information about diffusion anisotropy and direction for assessing white matter health and morphology (1-11).Many of these methods are based on a model of diffusion as a second-rank tensor. However, the tensor model is not always a valid approach, particularly for voxels containing multiple tracts (12). This work introduces a simple metric that does not rely on tensor assumptions and can be used to replace many of the tensor-based analysis methods. This metric can be used in various ways, three of which are given here. First, the characteristics of the metric are investigated analytically. Next, applications of this metric in calculating fractional anisotropy, filtering DWI data, and displaying tract orientation via color displays are shown. Because it does not involve reducing the data to a diffusion tensor, the information (e.g., degree of anisotropy) present in data for nontensor cases (such as overlying tracts in a single voxel) may be better preserved using the proposed metric than what is obtained in a tensor-based metric. Of course, this method cannot extract information which is not present in the source diffusion measurements.

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Diffusion-weighted MR Imaging in the Brain in Children: Findings in the Normal Brain and in the Brain with White Matter Diseases

Cited by 178 publications

References 26 publications

Evidence of Rapid Ongoing Brain Development Beyond 2 Years of Age Detected by Fiber Tracking

Evidence of Rapid Ongoing Brain Development Beyond 2 Years of Age Detected by Fiber Tracking

White matter maturation reshapes structural connectivity in the late developing human brain

A correlative measure for processing multiangle diffusion‐weighted images

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