Diffusion tensor imaging of normal brain development

The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, 210 Traylor Building, 720 Rutland Ave., Baltimore, MD, 21205, USA.
Pediatric Radiology (Impact Factor: 1.57). 01/2013; 43(1):15-27. DOI: 10.1007/s00247-012-2496-x
Source: PubMed


Diffusion tensor imaging (DTI) is an MRI technique that can measure the macroscopic structural organization in brain tissues. DTI has been shown to provide information complementary to relaxation-based MRI about the changes in the brain's microstructure. In the pediatric population, DTI enables quantitative observation of the maturation process of white matter structures. Its ability to delineate various brain structures during developmental stages makes it an effective tool with which to characterize both the normal and abnormal anatomy of the developing brain. This review will highlight the advantages, as well as the common technical pitfalls of pediatric DTI. In addition, image quantification strategies for various DTI-derived parameters and the normal brain developmental changes associated with these parameters are discussed.

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    • "For uniformity, we will use gestational weeks (rather than conceptional weeks calculated from the day of conception) throughout this review. measure of relative degree of directionality of diffusion in a voxel) increases in a posterior-to-anterior and a central-to-peripheral order (Hüppi et al., 1998a; Berman et al., 2005; Yoshida et al., 2013). "
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    ABSTRACT: The mysteries of early development of cortical processing in humans have started to unravel with the help of new non-invasive brain research tools like multichannel magnetoencephalography (MEG). In this review, we evaluate, within a wider neuroscientific and clinical context, the value of MEG in studying normal and disturbed functional development of the human somatosensory system. The combination of excellent temporal resolution and good localization accuracy provided by MEG has, in the case of somatosensory studies, enabled the differentiation of activation patterns from the newborn's primary (SI) and secondary somatosensory (SII) areas. Furthermore, MEG has shown that the functioning of both SI and SII in newborns has particular immature features in comparison with adults. In extremely preterm infants, the neonatal MEG response from SII also seems to potentially predict developmental outcome: those lacking SII responses at term show worse motor performance at age 2 years than those with normal SII responses at term. In older children with unilateral early brain lesions, bilateral alterations in somatosensory cortical activation detected in MEG imply that the impact of a localized insult may have an unexpectedly wide effect on cortical somatosensory networks. The achievements over the last decade show that MEG provides a unique approach for studying the development of the somatosensory system and its disturbances in childhood. MEG well complements other neuroimaging methods in studies of cortical processes in the developing brain.
    Frontiers in Human Neuroscience 03/2014; 8:158. DOI:10.3389/fnhum.2014.00158 · 2.99 Impact Factor
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    • "Axial diffusivity (AD) is the rate of diffusion along the orientation of white matter fibers within a tract, whereas radial diffusivity (RD) is the rate of diffusion orthogonal to the fiber orientation. Normal white matter maturation during childhood produces increasing FA, decreasing MD and decreasing RD, with relatively smaller changes in AD (Mukherjee and McKinstry, 2006; Mukherjee et al., 2001, 2002; Yoshida et al., 2013). Conversely, white matter pathology typically causes decreased FA, elevated MD and elevated RD, collectively referred to as reduced " microstructural integrity " . "
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    ABSTRACT: Sensory processing disorders (SPD) affect 5-16% of school-aged children and can cause long-term deficits in intellectual and social development. Current theories of SPD implicate primary sensory cortical areas and higher-order multisensory integration (MSI) cortical regions. We investigate the role of white matter microstructural abnormalities in SPD using diffusion tensor imaging (DTI). DTI was acquired in 16 boys, 8-11 years old, with SPD and 24 age-, gender-, handedness- and IQ-matched neurotypical controls. Behavior was characterized using a parent report sensory behavior measure, the Sensory Profile. Fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD) were calculated. Tract-based spatial statistics were used to detect significant group differences in white matter integrity and to determine if microstructural parameters were significantly correlated with behavioral measures. Significant decreases in FA and increases in MD and RD were found in the SPD cohort compared to controls, primarily involving posterior white matter including the posterior corpus callosum, posterior corona radiata and posterior thalamic radiations. Strong positive correlations were observed between FA of these posterior tracts and auditory, multisensory, and inattention scores (r = 0.51-0.78; p < 0.001) with strong negative correlations between RD and multisensory and inattention scores (r = - 0.61-0.71; p < 0.001). To our knowledge, this is the first study to demonstrate reduced white matter microstructural integrity in children with SPD. We find that the disrupted white matter microstructure predominantly involves posterior cerebral tracts and correlates strongly with atypical unimodal and multisensory integration behavior. These findings suggest abnormal white matter as a biological basis for SPD and may also distinguish SPD from overlapping clinical conditions such as autism and attention deficit hyperactivity disorder.
    Clinical neuroimaging 12/2013; 2(1):844-53. DOI:10.1016/j.nicl.2013.06.009 · 2.53 Impact Factor
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    • "The recent development of non-invasive techniques (magnetic resonance imaging (MRI), electroencephalography (EEG), magnetoencephalography (MEG)) has further enabled to relate maturation of cerebral structures to infants' neurodevelopment and behavior. In particular, several MRI techniques available on clinical scanners (section 'Structural MRI techniques and developmental specificities') enable to investigate and follow longitudinally the brain development and plasticity of healthy and at-risk children (Barkovich, 2000; Paus et al., 2001; Neil et al., 2002; Prayer and Prayer, 2003; Huppi and Dubois, 2006; Yoshida et al., 2013). But when these imaging techniques are applied to babies, many difficulties arise and require adapting data acquisition and post-processing to different developmental periods (fetus, preterm or at-term newborn, infant, toddler, etc.). "
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    ABSTRACT: Studying how the healthy human brain develops is important to understand early pathological mechanisms and to assess the influence of fetal or perinatal events on later life. Brain development relies on complex and intermingled mechanisms especially during gestation and first post-natal months, with intense interactions between genetic, epigenetic and environmental factors. Although the baby's brain is organized early on, it is not a miniature adult brain: regional brain changes are asynchronous and protracted, i.e. sensory-motor regions develop early and quickly, whereas associative regions develop later and slowly over decades. Concurrently, the infant/child gradually achieves new performances, but how brain maturation relates to changes in behaviour is poorly understood, requiring non-invasive in vivo imaging studies such as MRI. Two main processes of early white matter development are reviewed: 1) establishment of connections between brain regions within functional networks, leading to adult-like organisation during the last trimester of gestation, 2) maturation (myelination) of these connections during infancy to provide efficient transfers of information. Current knowledge from post-mortem descriptions and in vivo MRI studies is summed up, focusing on T1- and T2-weighted imaging, diffusion tensor imaging, and quantitative mapping of T1/T2 relaxation times, myelin water fraction and magnetization transfer ratio.
    Neuroscience 12/2013; 276. DOI:10.1016/j.neuroscience.2013.12.044 · 3.36 Impact Factor
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