Diffusion tensor imaging with tract-based spatial statistics reveals local white matter abnormalities in preterm infants

Anjari, Mustafa; Srinivasan, Latha; Allsop, Joanna; Hajnal, Joseph V.; Rutherford, Mary A.; Edwards, A. David; Counsell, Serena J.

doi:10.1016/j.neuroimage.2007.01.035

Cited by 290 publications

(270 citation statements)

References 32 publications

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“…It has been well-established that preterm birth is associated with reduced FA and increased mean diffusivity, suggesting reduced structural connectivity [1,3,24]. Our results may complement those findings by further showing that this reduced connectivity does not affect the overall organization of the connectome, or that the differences in organization are subtle enough that they cannot be discerned from measures of the backbone network.…”

Section: Discussionsupporting

confidence: 86%

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Structural network analysis of brain development in young preterm neonates

et al. 2014

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Preterm infants develop differently than those born at term and are at higher risk of brain pathology. Thus, an understanding of their development is of particular importance. Diffusion tensor imaging (DTI) of preterm infants offers a window into brain development at a very early age, an age at which that development is not yet fully understood. Recent works have used DTI to analyze structural connectome of the brain scans using network analysis. These studies have shown that, even from infancy, the brain exhibits small-world properties. Here we examine a cohort of 47 normal preterm neonates (i.e., without brain injury and with normal neurodevelopment at 18 months of age) scanned between 27 and 45 weeks post-menstrual age to further the understanding of how the structural connectome develops. We use fullbrain tractography to find white matter tracts between the 90 cortical and sub-cortical regions defined in the University of North Carolina Chapel Hill neonatal atlas. We then analyze the resulting connectomes and explore the differences between weighting edges by tract count versus fractional anisotropy. We observe that the brain networks in preterm infants, much like infants born at term, show high efficiency and clustering measures across a range of network scales. Further, the development of many individual region-pair connections, particularly in the frontal and occipital lobes, is significantly correlated with age. Finally, we observe that the preterm infant connectome remains highly efficient yet becomes more clustered across this age range, leading to a significant increase in its small-world structure.

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Section: Discussionsupporting

confidence: 86%

“…While the cohort in this study was screened thoroughly to be normative, we still expect known effects of preterm birth, like reduced overall FA and increased MD, to have some effect on brain network connectivity [1,3,24]. A future direction is to examine the relationships between birth age, age at time of scan and connectome topology.…”

Section: Discussionmentioning

confidence: 99%

Structural network analysis of brain development in young preterm neonates

et al. 2014

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“…Although all infants were scanned at term-equivalent age and we took precautions to exclude subjects who showed signs of WM abnormalities or who otherwise showed abnormal brain development, it cannot be ruled out that preterm birth or perinatal factors as such might influence the observed patterns of resting-state activity in the infant brain. For example, diffusion tensor MRIs have detected subtle regional changes in specific WM regions, including the corpus callosum and internal capsule in unselected preterm infants at term compared with term-born infants (30,31). Such abnormalities could potentially have influenced our results (see also refs.…”

Section: Discussionmentioning

confidence: 90%

Resting-state networks in the infant brain

Fransson

Skiöld²,

Horsch³

et al. 2007

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

604

527

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In the absence of any overt task performance, it has been shown that spontaneous, intrinsic brain activity is expressed as systemwide, resting-state networks in the adult brain. However, the route to adult patterns of resting-state activity through neuronal development in the human brain is currently unknown. Therefore, we used functional MRI to map patterns of resting-state activity in infants during sleep. We found five unique resting-states networks in the infant brain that encompassed the primary visual cortex, bilateral sensorimotor areas, bilateral auditory cortex, a network including the precuneus area, lateral parietal cortex, and the cerebellum as well as an anterior network that incorporated the medial and dorsolateral prefrontal cortex. These results suggest that resting-state networks driven by spontaneous signal fluctuations are present already in the infant brain. The potential link between the emergence of behavior and patterns of resting-state activity in the infant brain is discussed.development ͉ functional MRI ͉ spontaneous activity R ecent research on functional connectivity in the brain, in particular during resting-state conditions, has come to focus on low-frequency (Ͻ0.1 Hz), spontaneous fluctuations in the functional MRI (fMRI) signal. Discovered by Biswal et al. (1), it has been shown that systemwide networks in the resting brain are synchronized in time through intrinsic low-frequency signal fluctuations. Whereas early fMRI studies demonstrated synchronicity of intrinsic brain activity across hemispheres in primary sensory cortices (2, 3), succeeding studies have shown temporal synchronization in a resting-state network encompassing higher-order cortices (4). A systematic investigation of resting-state activity in the adult human brain was recently presented by Damoiseaux et al. (5). Using independentcomponent analysis (ICA), a data-driven explorative data analysis approach, they showed that there are numerous networks in the brain that are driven by spontaneous activity. Besides networks that are in part or fully described by the previously reported default mode (6) and task-positive network (7, 8), they found consistent patterns of resting-state activity in the visual cortex, sensorimotor areas, auditory areas, as well as extrastriate brain regions. These findings together with previous investigations on spontaneous activity suggest that the assumption that the brain during rest is idle and waiting to be triggered and respond to changes in the environment is not strictly valid. Rather, in addition to responding to changes in external stimuli or tasks, the brain is characterized by intrinsic dynamics in the form of coherent and spontaneous fluctuations, clustered together in networks that are credible from an anatomical and functional perspective.Interestingly, recent studies have presented evidence that spontaneous activity is relevant for human behavior. Momentary lapses of attention, affecting goal-oriented behavior on a global/ local selective attention task, were related to a fai...

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“…There were three studies that contained both coordinates and fractional anisotropies of the corpus callosum, and therefore a total of 13 studies were included. 20,[29][30][31][32][33][34][35][36][37][38][39][40] The included studies involved a total of 513 children, adolescents or young adults who were born prematurely and were matched with 309 healthy comparison participants. The process of study selection is shown in Figure 1.…”

Section: Resultsmentioning

confidence: 99%

Fractional anisotropy alterations in individuals born preterm: a diffusion tensor imaging meta‐analysis

Sun

Han

et al. 2014

Develop Med Child Neuro

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ALEActivation likelihood estimate DTI Diffusion tensor imaging SMD Standardized mean difference AIM This meta-analysis explored cerebral microstructural changes in individuals born preterm using fractional anisotropy from diffusion tensor imaging.METHOD We used the activation likelihood estimate (ALE) method for the meta-analysis to locate anatomical regions with white matter abnormalities in a group of individuals born preterm and in term-born comparison participants. A statistical analysis of fractional anisotropy was conducted to quantitatively explore the extent of fractional anisotropy changes in the three subregions of the corpus callosum in the preterm group.RESULTS ALE analysis identified 11 regions of decreased fractional anisotropy and four regions of increased fractional anisotropy. Analysis of the corpus callosum revealed the largest decrease in fractional anisotropy in the splenium (standardized mean difference [SMD]=À0.75, 95% confidence interval [CI] À0.93 to À0.57), followed by the body (SMD=À0.73, 95% CI À1.13 to À0.32) and the genu (SMD=À0.65, 95% CI À0.97 to À0.33). INTERPRETATION Significant changes in fractional anisotropy in individuals born pretermreflect white matter abnormalities from childhood to young adulthood, and the mechanism of fractional anisotropy alterations in preterm infants may vary during different stages of white matter development. Furthermore, the variability of fractional anisotropy between studies can primarily be attributed to the age of the individuals at scanning and to the field strength of magnetic resonance scanners.Preterm birth is frequently accompanied by a variety of disabilities, such as cerebral palsy, intellectual disability, deafness, or blindness. The incidence of preterm birth has increased significantly in the past decades, but is associated with higher survival rates 1 and a lower incidence of major disabilities than in the past.2 However, there is strong evidence that preterm survivors without brain malformations, congenital infection, or metabolic disease and with normal outcomes or mild abnormalities on structural brain magnetic resonance imaging (MRI) may experience more problems of motor, cognitive, language, and behavioural functioning throughout childhood and young adulthood. [3][4][5][6] These sequelae have been attributed to perinatal brain injuries, 7,8 which frequently involve white matter, 9 during normal brain maturation. 10 Nevertheless, the location, severity, and mechanism of white matter injuries on neurodevelopment and their impact on future function have not been conclusively determined.11 Additional neuroimaging evidence is necessary to explain the mechanism of white matter injuries and to predict the future influence of these impairments in individuals who are born preterm.Diffusion tensor imaging (DTI), a novel MRI technique, can quantify the fibre orientation and integrity of white matter pathways within neural networks. This technique is superior to conventional MRI methods for the detection of white matter abnormalities becaus...

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Diffusion tensor imaging with tract-based spatial statistics reveals local white matter abnormalities in preterm infants

Cited by 290 publications

References 32 publications

Structural network analysis of brain development in young preterm neonates

Structural network analysis of brain development in young preterm neonates

Resting-state networks in the infant brain

Fractional anisotropy alterations in individuals born preterm: a diffusion tensor imaging meta‐analysis

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