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      New Techniques in the Study of the Brain Development in Newborn

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          Abstract

          In the last few decades, the survival rates of preterm babies and full-term babies with severe diseases have increased due to advances in perinatal care. Understandably however, higher survival rates have not been accompanied by an overall reduction of morbidity, so that limitation of long-term neurodevelopmental abnormalities remains a major challenge of early care (Plaisier et al., 2014). The possibility to better predict the outcome of newborns at neurodevelopmental risk is essential to inform early intervention, to allow best allocation of resources, and to minimize long-term consequences. Unfortunately, clinicians continue to possess limited ability to predict neurodevelopmental outcomes, mainly relying, in most settings, on early findings at cranial ultrasound (cUS). Recent studies (Smyser et al., 2012) have proven the power of magnetic resonance imaging (MRI) superior to other neuroimaging modalities, including cUS, in detecting cerebral injury. Neonatal MRI provides non-invasive, high-resolution images in less than 1 h; scans are performed without sedation eliminating the risk and the costs associated to it and are not associated to radiation exposure, as for computerized tomography (CT). The application of MRI in the neonatal population is rapidly increasing, making MRI one of the key diagnostic tools for the assessment of early brain development and injury. In specific clinical groups, such as for example very preterm infants, cerebral MRI should become part of standard clinical care and should be systematically performed at term equivalent age (TEA). Accurate assessment of cortical folding at TEA provides an important marker for structural brain growth and maturation. Myelination of the posterior limb of the internal capsule (PLIC) at around 36–38 weeks gestation, identifiable on T1 but also on T2-weighted images, is another important maturational hallmark, since its presence and symmetry are very powerful in predicting motor outcome. MR imaging is superior to cUS also in detecting diffuse white matter (WM) injury. Indeed, although cystic periventricular leukomalacia is seen less often, diffuse non-cystic types of WM injury, including punctate WM lesions and diffuse excessive high signal intensity, are most frequent and are considered the leading cause of disturbed brain growth, connectivity, and functionality. The predictive power of conventional MRI in this domain remains relatively low, as it is not sensitive enough to analyze changes in microstructure; however, it is greatly enhanced by the use of advanced MR techniques targeting the WM, such as diffusion tensor imaging (DTI), that can help analyzing brain growth in extremely preterm babies in the absence of evident WM abnormalities (Ramenghi et al., 2009). Diffusion tensor imaging (DTI) is a relatively new MR modality that assesses water diffusion in biological tissues at microstructural level. The diffusion tensor describes an ellipsoid in space characterized by the diffusion eigenvalues (λ1,λ2,λ3) in the three orthogonal directions and their corresponding eigenvectors. In brain WM, axial diffusivity (λ1) is oriented along the direction of the main tracts and radial diffusivity (λ2 and λ3) is oriented perpendicular to these tracts. Average diffusivity (D av) reflects the mean of these eigenvalues and it is an indicator of brain maturation and/or injury. D av decreases with increasing age probably for decreasing water content and increasing complexity of WM structures with myelination. Fractional anisotropy (FA) reflects the variance of the eigenvalues, ranging from 0 (isotropic diffusion) to 1 (anisotropic). The diffusion is mainly anisotropic because the water molecules preferentially move in the direction of fascicles of axons (Adams et al., 2010). In the white and gray matter, there is similar water content but different D av value probably because the WM is less restrictive to water motion. Brain water content decreases with increasing gestational age and this mostly increases the WM anisotropy values. This increase has also been attributed to changes in WM structure associated with histologic maturation, and it takes place at different rates in different brain areas [the main areas analyzed are in commissural tracts, the corpus callosum (CC), and in projection tracts, the corticospinal tracts (CSTs)]. Developmental changes in anisotropy of cerebral cortex reflect changes in its microstructure, such as the arborization of basal dendrites of cortical neurons, the innervation of the cortical plate by thalamocortical and cortico-cortical fibers, all processes which are important basis of later functional connectivity (Huppi and Dubois, 2006). Because there are strongly preferred directions of diffusion, it is possible to create color maps of neonatal brain with diffusion tensor post-processing techniques. The color maps are based on major orientation with red representing right–left, green representing antero–posterior, and blue representing superior–inferior anatomical directions (De Bruïne et al., 2013) (Figure 1). Figure 1 Color anisotropy maps. Preterm birth can cause white matter injuries (WMIs) and consequently can cause change in FA and diffusivity. Decreased FA in the CC of preterm babies scanned at TEA is rather common and implies less efficient transmission between the hemispheres and may lead to language problems and cognitive dysfunctions. Regions with increased FA in a preterm baby may be attributed to a loss or to an impairment of WM instead of improved WM maturation (Li et al., 2014). Disorders of motor function can be tested in clinical practice with DTI. In children with congenital hemiparesis, there are different diffusion characteristics of CSTs compared to healthy one. There is an increasing FA asymmetry and a decrease in FA value in the affected pyramidal tract. A recent extension of DTI is tractography, which is a powerful tool that offers the possibility of non-invasive identification of specific WM pathways and connections in the brain. The general principle is to connect adjacent image voxels following water diffusion. Directional coherence of the fibers in a pathway is used to determine the presence or absence of connectivity between two regions of the brain. Tracking of the fiber-trajectories is terminated when they turn of too much degrees between two successive voxels. The main regions of interest include the CSTs, the CC, and optic radiations (OR). The primary goal should be to understand the normal relationship between structural and functional networks of these structures but there are few data in preterm babies (Brown et al., 2014). Preterm birth correlates with reduced connectivity, and it is very difficult to establish normal value for all gestational ages. Maturation does not occur simultaneously in the brain infact, for example, connectivity increases earlier in the occipital lobe and then in the frontal area. The postnatal age and WMI are additional confounding factors of diffusion metrics (Pannek et al., 2014). Nevertheless, the primary difference between DTI and conventional imaging is the capability of DTI to often detect injury earlier. This could anticipate the diagnosis of brain damage and might offer advantages in the future for deciding early intervention or administration of neuroprotective agents. Further studies will be needed to confirm whether these new techniques may predict neurodevelopmental outcome and whether they are equally applicable to all the pathways of the central nervous system. Conflict of Interest Statement The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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          Diffusion tensor imaging of brain development.

          Understanding early human brain development is of great clinical importance, as many neurological and neurobehavioral disorders have their origin in early structural and functional cerebral organization and maturation. Diffusion tensor imaging (DTI), a recent magnetic resonance (MR) modality which assesses water diffusion in biological tissues at a microstructural level, has revealed a powerful technique to explore the structural basis of normal brain development. In fact, the tissue organization can be probed non-invasively, and the age-related changes of diffusion parameters (mean diffusivity, anisotropy) reveal crucial maturational processes, such as white matter myelination. Nevertheless, the developing human brain presents several challenges for DTI applications compared with the adult brain. DTI may further be used to detect brain injury well before conventional MRI, as water diffusion changes are an early indicator of cellular injury. This is particularly critical in infants in the context of administration of neuroprotective therapies. Changes in diffusion characteristics further provide early evidence of both focal and diffuse white matter injury in association with periventricular leukomalacia in the preterm infant. Finally, with the development of 3D fiber tractography, the maturation of white matter connectivity can be followed throughout infant development into adulthood with the potential to study correlations between abnormalities on DTI and ultimate neurologic/cognitive outcome.
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            Structural network analysis of brain development in young preterm neonates.

            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 full-brain 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. Copyright © 2014 Elsevier Inc. All rights reserved.
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              Fractional anisotropy alterations in individuals born preterm: a diffusion tensor imaging meta-analysis.

              This meta-analysis explored cerebral microstructural changes in individuals born preterm using fractional anisotropy from diffusion tensor imaging. 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. 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]=-0.75, 95% confidence interval [CI] -0.93 to -0.57), followed by the body (SMD=-0.73, 95% CI -1.13 to -0.32) and the genu (SMD=-0.65, 95% CI -0.97 to -0.33). Significant changes in fractional anisotropy in individuals born preterm reflect 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. © 2014 Mac Keith Press.
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                Author and article information

                Contributors
                Journal
                Front Hum Neurosci
                Front Hum Neurosci
                Front. Hum. Neurosci.
                Frontiers in Human Neuroscience
                Frontiers Media S.A.
                1662-5161
                20 January 2015
                2014
                : 8
                : 1069
                Affiliations
                [1] 1Department of Maternal and Child Health, Division of Neonatology and Neonatal Intensive Care Unit, S. Chiara Hospital, University of Pisa , Pisa, Italy
                [2] 2Department of Developmental Neuroscience, Stella Maris Scientific Institute , Pisa, Italy
                Author notes

                Edited by: Marika Berchicci, Università degli Studi di Roma “Foro Italico”, Italy

                Reviewed by: Noa Ofek-Shlomai, Hebrew University of Jerusalem, Israel

                This article was submitted to the journal Frontiers in Human Neuroscience.

                Article
                10.3389/fnhum.2014.01069
                4299644
                75b35fe1-59ff-48b8-9125-f24bdb8bc967
                Copyright © 2015 Giampietri, Bartalena, Guzzetta, Boldrini and Ghirri.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 11 November 2014
                : 23 December 2014
                Page count
                Figures: 1, Tables: 0, Equations: 0, References: 9, Pages: 2, Words: 1663
                Categories
                Neuroscience
                Opinion Article

                Neurosciences
                magnetic resonance imaging,cranial ultrasound,neurodevelopmental outcome,diffusion tensor imaging (dti),tractography

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