Diffusion Imaging in the Developing Brain

C H A P T E R

13 Diffusion Imaging in the Developing Brain Serena J. Counsell, Gareth Ball, Anand Pandit, A. David Edwards Centre for the Developing Brain, Department of Perinatal Imaging, Division of Imaging Sciences & Biomedical Engineering, St Thomas’ Hospital Kings College London, London, UK

O U T L I N E 13.1 Changes in Diffusion Measures with Increasing Gestational Age 13.2 Abnormal White Matter and Cortical Gray Matter Development in Preterm Infants at Term

283

285

13.3 Assessing the Connectome in the Developing Brain 286 13.4 DTI in Preterm Brain Injury 13.4.1 Periventricular Leukomalacia 13.4.2 Punctate White Matter Lesions 13.4.3 Periventricular Hemorrhagic Infarction 13.4.4 Diffuse White Matter Abnormality (DEHSI)

288 288 290 291

292

13.6 MRI in the Term Infant with Perinatal Brain Injury 13.6.1 Perinatal Arterial Stroke 13.6.2 Hypoxic Ischemic Encephalopathy (HIE)

294 294 295

13.7 Future Directions

296

13.8 Conclusions

297

References

297

292

13.1 CHANGES IN DIFFUSION MEASURES WITH INCREASING GESTATIONAL AGE Diffusion magnetic resonance imaging (MRI) of the human brain in vivo is currently possible from the third trimester of pregnancy onwards. Brain growth and maturation during this period is rapid: thalamocortical, cortico-cortical and callosal-cortical fibers form synapses with subplate neurons situated in the transient subplate layer; subplate neurons send axons to the developing cortex; and axons descend from the cortex to the basal ganglia and corticospinal tracts. Premyelinating oligodendrocytes ensheath these afferent and efferent fibers (Volpe, 2009). Imaging the fetal brain is technically very challenging, primarily due to fetal motion, although recent advances in acquisition and Diffusion MRI http://dx.doi.org/10.1016/B978-0-12-396460-1.00013-5

13.5 Diffusion MRI Studies of the Developing Preterm Brain and Association with Neurodevelopmental Outcome

reconstruction strategies are having some success in addressing this issue (Jiang et al., 2009). Consequently most of the imaging studies assessing the developing brain have been performed in infants born preterm, and the installation of MRI scanners within Neonatal Intensive Care Units has allowed maturational changes in white matter and cortex to be assessed from as young as 25 weeks gestational age postmenstrual age (PMA), when these infants are still undergoing intensive care (Maalouf et al., 1999). Diffusivity in the developing preterm brain is closely associated with age. Most studies have used the diffusion tensor model (see Chapter 5) to estimate local diffusion parameters. In preterm infants between 28 and 30 weeks (PMA), apparent diffusion coefficient (ADC) values in the central white matter approach 2 mm2/s and relative anisotropy around 10% (Huppi et al.,

283

Copyright Ó 2014 Elsevier Inc. All rights reserved.

284

13. DIFFUSION IMAGING IN THE DEVELOPING BRAIN

1998). With increasing maturity, decreasing ADC parallels increasing anisotropy (Neil et al., 1998; Miller et al., 2002; Mukherjee et al., 2002; Dudink et al., 2007). Maturational changes in diffusivity and anisotropy are not uniform across the brain. Early myelinating structures such as the posterior limb of the internal capsule demonstrate higher anisotropy and lower diffusivity from around 30 weeks PMA (Figure 13.1). In contrast, diffusivity in some association tracts can remain relatively high up to term-equivalent age (Huppi et al., 1998; Partridge et al., 2004). Anisotropy values in the subplate, a transient laminar compartment of the human fetal cerebral wall that plays an important role in the developing cortical architecture, are low, consistent with the observation of more randomly scattered cells seen on histology and the mixture of interdigitating radial and tangential fibers within this lamina. Dudink and colleagues (2010) found an increase of ADC values in the region of the subplate between 26 and 31 weeks PMA, perhaps due to a decrease in cellularity (associated with programmed cell death) in certain areas or due to the loss of interconnections in this region of the brain which could outweigh the decrease in overall water content during brain maturation (Dudink et al., 2010). The relationship between tissue microstructure, diffusivity and anisotropic diffusion is complex and multifactorial and is likely to involve a combination of decreasing tissue water content and increasing complexity of white matter structures with age. Significant decreases in water content occur across the whole brain during the preterm period (Dobbing and Sands,

1973). This process is thought to increase the density of cellular barriers in the parenchyma, reducing spin displacement due to diffusion and resulting in decreased ADC. Diffusion tensor imaging (DTI) has revealed diffusivity decreases predominantly in the directions perpendicular to underlying white matter tracts (i.e. along the shortest axes of the diffusion tensor, l2 and l3 (Mukherjee et al., 2002; Partridge et al., 2004; Anjari et al., 2007)), changes that are reflected in increasing anisotropy observed over the same period. Experimentally, anisotropy is predominantly dependent on the packing of parallel neuronal axons, axonal thickness, and myelination (Sakuma et al., 1991; Takagi et al., 2009). In the preterm brain, however, anisotropic diffusion is observed before myelin is evident either histologically or on conventional MRI (Yakolev and Lecours, 1967; Wimberger et al., 1995). Most regions in the telencephalon are at a stage of premyelination, characterized by various processes including axonal widening and packing, association with immature oligodendroglia and altered axonal membrane permeability (Jessen and Mirsky 1991; Wimberger et al., 1995). These processes are likely to contribute substantially to anisotropic diffusion in the developing preterm brain. Nonstructural changes may also contribute to anisotropy as inhibition of the normal functioning of the sodium-channel pump results in reduced anisotropy in the developing rat brain (Prayer et al., 2001). Unlike the changes observed in white matter, anisotropy in the developing cortical gray matter

FIGURE 13.1 Population-averaged FA maps at seven developmental time points in the (a) coronal, (b) axial, and (c) sagittal planes. Intensity bar indicates FA value. Courtesy R. Braga.

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

13.2. ABNORMAL WHITE MATTER AND CORTICAL GRAY MATTER DEVELOPMENT IN PRETERM INFANTS AT TERM

peaks at 26 weeks PMA (Figure 13.1) and decreases with maturity, reaching values close to zero by around 36 weeks (McKinstry et al., 2002; Trivedi et al., 2009; Dudink et al., 2010). Diffusivity follows a similar pattern, increasing between 26 and 32 weeks before decreasing in a manner similar to that of the white matter (McKinstry et al., 2002; Dudink et al., 2010). The changes in cortical anisotropy observed during this period appear to demonstrate regional specificity: some reports suggest that this occurs first in the sensorimotor cortex and initially on the right hemisphere (Deipolyi et al., 2005; Trivedi et al., 2009); our own data show the frontal lobe lagging significantly behind other regions, then developing rapidly before termcorrected age (Ball et al., 2013). Anisotropy appears to be dependent on diffusivity along the principal vector of the diffusion tensor (l1) which, during the preterm period, is aligned radially to the pial surface of the brain (McKinstry et al., 2002; Maas et al., 2004; Deipolyi et al., 2005). During this anisotropic period, cortical cytoarchitecture is dominated by neurons migrating towards the cerebral cortex along radially orientated glial fibers (Rakic, 2003). This process continues until the third trimester when maturational processes, including dendritic growth from cell bodies, in-growth of thalamocortical afferents, synapse formation, and proliferation of glial cells take over to produce a complex multidirectional fiber arrangement and an overall reduction of diffusion anisotropy and diffusivity (Sidman and Rakic 1973; Marin-Padilla 1992; Kostovic et al., 2002; Trivedi et al., 2009). Animal studies have been able to correlate these changes in cortical diffusivity with histology (Sizonenko et al., 2007). ADC and FA changes in the developing rat brain between postnatal days 3 and 6 mirrored the developmental changes observed in the human brain. The radial organization, with the primary eigenvector perpendicular to the pial surface, was apparent throughout the cortical layers, but was most prominent in the external cortical layers (1–3) compared to the deep cortical layers (4–6). ADC decreased with maturation, but FA decreased only in the deep layers of the cortex. Increased neurodendritic density and a reduction in radial glial scaffolding was observed on histology with increasing maturation (Sizonenko et al., 2007). As with white matter, regional patterns of cortical maturation can be identified. A rostrolateral to caudal/medial gradient in cortical diffusion anisotropy has been observed, which appears to mirror patterns of neurogenesis and synapse formation (Kroenke et al., 2007; Huang et al., 2008). In the developing ferret brain, decreases in anisotropy were observed in primary cortical areas prior to neighboring nonprimary areas, suggesting early innervation by axonal fibers within

285

primary cortical areas prior to other areas (Kroenke et al., 2009).

13.2 ABNORMAL WHITE MATTER AND CORTICAL GRAY MATTER DEVELOPMENT IN PRETERM INFANTS AT TERM The preterm brain is susceptible to injury from ischemic, hemorrhagic, inflammatory, and infective insults (Volpe, 2009): immature oligodendrocytes are particularly sensitive to injury (Agresti et al., 1996; Volpe, 2001; Back et al., 2005; Talos et al., 2006), as are subplate neurons which form synapses with thalamocortical afferents in the transient subplate layer that are essential for normal cortical development (Ghosh and Shatz, 1993; McQuillen et al., 2003). These vulnerabilities may help explain the abnormalities in brain growth and development observed on DTI in infants and children who were born preterm. By term-equivalent age, the preterm brain is clearly different from that of a healthy term-born infant. Compared to their term-born peers, preterm infants display significantly lower anisotropy in the centrum semiovale, corpus callosum, and posterior limb of the internal capsule, even in the absence of white matter abnormalities visible on conventional MRI (Huppi et al., 1998; Skio¨ld et al., 2010). Increasingly advanced computational techniques provide mechanisms to examine group-wise DTI metrics in an objective, exploratory manner. Tract-based spatial statistics (TBSS; Smith et al., 2006) in particular, has proven amenable to adaptation for neonatal DTI analyses (Anjari et al., 2007, 2009; Ball et al., 2010; van Kooij et al., 2012). Through the projection of individual fractional anisotropy (FA) data onto a skeletonized representation of the major white matter tracts, this technique provides robust DTI analysis that negates the need for time-consuming, manual region of interest (ROI) measurement. Using this technique, Anjari et al. (2007) observed lower FA in the centrum semiovale, frontal white matter, and genu of the corpus callosum compared to age- and sex-matched term-born controls. The most immature infants, born below 28 weeks PMA, displayed further reductions in FA at term. In addition, it was shown that this reduction in FA was associated with elevated l2 and l3 eigenvalues, findings that signify an increase in radial diffusivity, consistent with previous regional-based DTI analysis (Counsell et al., 2006). Using TBSS to survey the major white matter tracts in the preterm brain shows a dose-dependent effect of prematurity on white matter development, with the infants who are most immature at birth displaying lower FA in the corpus callosum, internal capsule,

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

286

13. DIFFUSION IMAGING IN THE DEVELOPING BRAIN

external capsule, optic radiations, and centrum semiovale (Figure 13.2) (Ball et al., 2010). DTI studies in gyrencephalic animal models are proving useful in elucidating the underlying neurobiology associated with the observed impaired white matter development in preterm infants. In a preterm baboon model, elevated ADC values in white matter were associated with diffuse astrogliosis and reduced FA and increased radial diffusivity was associated with oligodendrocyte loss, although the precision of these correlations was less than complete, demonstrating the complexity of the biology interrogated by DTI (Griffith et al., 2012). Studies of cortical anisotropy have shown that cortical microstructure in the preterm brain differs to that of healthy term controls. At term-equivalent age, both FA and ADC values are elevated in the preterm population, consistent with dysmaturation of apical and basal dendrites (Ball et al., 2013). The developing preterm cortex displayed regional heterogeneity in FA values, as has been shown in the developing baboon (Kroenke et al., 2007) and ferret (Kroenke et al., 2009). Our data suggest that elevated ADC values in the cortex at termequivalent age predict lower neurodevelopmental performance scores at 2 years of age (Ball et al., 2013). These complex diffusion changes are part of more global differences in brain development following premature delivery. Immaturity at birth is associated with reductions in the volume of thalamus, hippocampus, orbitofrontal lobe, posterior cingulate cortex, and centrum semiovale, suggesting that preterm delivery disrupts specific aspects of cerebral development. In addition, abnormal thalamic growth is associated with

FIGURE 13.2

TBSS analysis of a group of 93 preterm infants born between 24 and 35 weeks gestational age, who were imaged at termequivalent age. Regions in blue show white matter tracts where FA values were significantly correlated with gestational age at birth, following correction for age at scan (Ball et al., 2010).

impaired white matter microstructural development as assessed by TBSS, suggesting that thalamocortical connectivity is disrupted following preterm birth (Ball et al., 2012). Alongside prematurity at birth, a number of perinatal factors may contribute to the etiology of subsequent neurodevelopmental disorders commonly seen in preterm survivors. Recent studies have shown that the degree of prematurity at birth, chronic lung disease, and the need for respiratory support (Figure 13.3) are all associated with widespread decreases in FA with concomitant increases in radial diffusivity, suggestive of diffuse white matter damage (Anjari et al., 2009; Ball et al., 2010). Postnatal infection, which is not uncommon in the preterm infant, is associated with an increased risk of white matter injury and elevated ADC values and reduced FA values throughout the white matter, independent of extreme prematurity and common neonatal comorbidities. These data support the hypothesis that infection and inflammation are major initiating mechanisms in the pathogenesis of injury to the immature brain (Chau et al., 2012).

13.3 ASSESSING THE CONNECTOME IN THE DEVELOPING BRAIN Recent studies in adults have implemented approaches for studying macroscopic whole-brain connectivity (see Chapters 16 and 18; Hagmann et al., 2007; Iturria-Medina et al., 2008) and work is now underway to investigate the connectome in the developing brain. These whole-brain connectome approaches allow the integration of distributed neural systems to be studied during development, and may provide additional information on brain plasticity following injury and on the neural substrates underlying the pervasive neurocognitive impairments observed in children who were born preterm. One method by which connectome data can be studied involves its analysis as a network using measures from graph theory. In graph theory, a graph is defined as a representation of a network involving a set of nodes with interlinking edges (Bullmore and Sporns, 2009). While regions of gray matter are normally defined as nodes, edges can be constructed by several means, including inference of structural connections from diffusion tractography, correlation of regional volume development, and the correlation of functional activation detected by blood oxygen level–dependent (BOLD) signals. Networks are commonly described on the basis of both their local elements and their overall global topology, and it has been observed that both functional and structural brain networks are inherently small world, and that in adults reductions in “small worldness” occur

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

287

13.3. ASSESSING THE CONNECTOME IN THE DEVELOPING BRAIN

p value

(a)

0

0.05 0

(b)

0.05

(c)

0

(d)

0.05

0.0000

–0.0001

–0.0002

0.0001

0.0000

–0.0001

0.06 Fractional anisotropy | GA,PMA

0.0001

0.0002 Radial diffusivity | GA,PMA

Axial diffusivity | GA,PMA

0.0002

0.02 0.00

–0.02 –0.04

–0.0002

–60 –40 –20 0 20 40 60 Days on respiratory support | GA,PMA

0.04

–60 –40 –20 0 20 40 60 Days on respiratory support | GA,PMA

–60 –40 –20 0 20 40 60 Days on respiratory support | GA,PMA

FIGURE 13.3 Increased length of neonatal respiratory support is associated with altered white matter microstructure. Increasing axial (a) and radial (b) diffusivity, and decreasing FA (c) is associated with increasing respiratory support requirements, independent of GA (gestational age) at birth and postmenstrual age at scan (FWE-corrected, p < 0.05; colour bars indicate p-value). Axial diffusivity, radial diffusivity, and FA was extracted from each significant voxel in (a), (b), and (c), respectively, and entered into linear regression with length of respiratory support, GA at birth and PMA at scan. Partial regression plots showing the relationship between respiratory support and axial diffusivity, radial diffusivity, and FA are shown in (d).

in a variety of disease states, which may be caused by a breakdown in connective microstructure (Lazar, 2010). A handful of studies have investigated the effect of maturation or injury on connectome-derived structural networks derived from diffusion imaging in the infant

brain. Fan et al. (2011) analysed early developmental patterns in a small group of infants using anatomical networks derived from morphological correlations of brain regional volumes in a longitudinal MRI data set comprising infants at 1 month, 1 year, and 2 years.

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

288

13. DIFFUSION IMAGING IN THE DEVELOPING BRAIN

Results from this study showed that brain networks of 1-month-old infants demonstrated economic, modular small-world topology and that both modularity and efficiency increase with development. Using an approach which captured the common connectivity patterns using deterministic tractography in a group at similar time points (2 weeks, 1 year, and 2 years), Yap et al. (2011) showed similar results with regard to the increasing efficiency and small-world topology in the early postnatal years. These network level changes are suggested to reflect consolidation and myelination of white matter fibers, in particular of long white matter connections with a local-to-distributed organization growth trend. In addition, the authors demonstrated, using graph theoretical metrics, consistent cerebral asymmetry and sexual dimorphism across time points. Whereas Yap and Fan and colleagues defined nodes or anatomical brain regions using a prior template, Tymofiyeva et al. (2012) proposed an automated framework for generating anatomical networks using two anatomically unconstrained parcellation schemes where networks are derived from deterministic tractography and in a report of 17 six-month-old infants who had sustained perinatal hypoxic ischemic encephalopathy reported that network descriptors correlated with neuromotor score. As studies of the developing connectome begin to be published, a number of technical considerations and limitations are becoming apparent. A question arises about the number of subjects required for these analysesdproposed connectome studies in adults such as the Human Connectome Project propose the use of data from many hundreds of datasets (www. humanconnectomeproject.org). Another issue is the parcellation scheme used to define nodes. Tymofiyeva et al. (2012) parcellated the brain using a scheme that is not imposed by any anatomical constraints. This approach is particularly suitable for the rapidly changing newborn brain. However, the lack of correspondence of regions across subjects means that observations of local changes are not possible. Having a finite number of registered, anatomically correspondent nodes across subjects also has limitations. The size of the parcellation scale has been shown to strongly influence network metrics (Zalesky et al., 2012) and therefore influences the number of nodes. In addition, there is not yet a unified approach to deal with weighted structural data. All three studies noted above (Tymofiyeva et al., 2012; Fan et al., 2011; Yap et al., 2011) used thresholded, binarized connectomes (or adjacency matrices), which cause a degree of data redundancy. Although the choice of threshold is not entirely arbitrary (Yap et al. and Fan et al. produce connectomes at a threshold where brain regions become fully connected in all age group networks), the difference in threshold between studies makes comparison difficult.

An alternative approach is to combine connectome data with sophisticated statistical tools, which may overcome some of these limitations. We have explored the influence of preterm birth on the partial thalamocortical connectome by comparing thalamocortical connectivity in healthy term-born control infants and preterm infants at term, who had no evidence of abnormality on MRI (Ball et al., 2013). In this study, we divided the cortex into many small seed regions (> 500 regions per hemisphere) and performed a modified probabilistic tractography approach (Robinson et al., 2010) to explore the strength of connection between cortical regions and the thalamus. Widespread thalamocortical connectivity was evident in the preterm group, with highly significant differences being observed in the frontal lobe, the supplementary motor and pre-motor regions, and in the medial occipital lobe (Ball et al., 2013) (Figure 13.4). These neural systems sub-serve executive, coordination, and sensory functions that are frequently impaired in survivors of preterm birth. We have also explored whole-brain structural connectivity in young children who were born preterm and observed significant correlations between the strength of connection between regions and age at scan and degree of prematurity at birth (Pandit et al., 2013). Employing novel statistical techniques, sparse-penalized regression, and stability selection, we identified connections associated with development and prematurity (Figure 13.5). Tracts connecting frontal regions showed the strongest assocation with age at scan between 11 and 31 months of age, which is consistent with the later maturation of frontal white matter in both histology and imaging studies (Yakolev and Lecours, 1967; Hermoye et al., 2006; Gao et al., 2009). In contrast, connections associated with prematurity at birth were widespread and appeared to affect all cortical lobes and several subcortical structures and highlighted the diffuse nature of the disease. Connectomic analysis is in its infancy, and much work remains to be done to develop and refine the tools and techniques as well as the interpretation of the results. These approaches hold promise for understanding the immense complexity of brain networks, however, and when allied to connectivity data at the microscopic level offer a conceptual framework to assess the development of whole-brain connectivity in the infant brain and the impact of aberrant development.

13.4 DTI IN PRETERM BRAIN INJURY 13.4.1 Periventricular Leukomalacia Periventricular leukomalacia (PVL) is a histopathological term that does not imply a particular etiology and typically affects the immature brain over a limited

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

13.4. DTI IN PRETERM BRAIN INJURY

289

FIGURE 13.4 Thalamocortical connectivity maps showing differences in thalamocortical connectivity between preterm infants at term and healthy term control infants. These regions include the frontal lobe, the supplementary motor area and the medial occipital lobe (Ball et al., 2013).

gestational age range of 26–32 weeks. There is now a wealth of data on the clinical antecedents of PVL, with combinations of infection, inflammation, and ischemia being major factors in animal models. In infants with PVL, it is recognized that the brain may show a diffuse component around and at a distance from the focal cystic lesions (Volpe, 2003; Back, 2006) which is seen as high signal intensity on T2-weighted and low signal intensity on T1-weighted imaging. This is confirmed by in vivo imaging studies where there may be both acute and chronic changes in diffusion parameters in non-cystic tissue (Counsell et al., 2006). DWI shows restricted diffusion prior to cyst formation and that the evolution of the lesions may be heterogeneous, with established cysts being demonstrated adjacent to more recently involved regions of white matter still showing restricted diffusion (Inder et al., 1999; Roelants-van Rijn et al., 2001). Roelants-van Rijn and colleagues reported high signal intensity on DWI adjacent to cystic areas. On histology, these areas were found to be undergoing active degeneration with cytotoxic edema, apoptosis, and macrophage infiltration (Roelants-van Rijn et al., 2001). By termequivalent age, the cystic lesions are often incorporated

into the lateral ventricles, resulting in the characteristic squared off appearance of the posterior horns. Using DTI, Nagae et al. (2007) identified white matter tracts in 24 children with PVL-associated cerebral palsy and graded them according to abnormalities. Although highly variable, the most common injury sites were the retrolenticular internal capsule, posterior thalamic radiation, and corona radiata. Three-dimensional visualization of the posterior thalamic radiations in two infants with PVL revealed striking abnormalities compared to a normal control. In a similar study, DTI tractography in 12 children with PVL and clear motor deficits revealed significantly lower FA at the site of injury and in the fibers of the corticospinal tract in the posterior limb of the internal capsule and corona radiata and prominent abnormalities in fiber tracts projecting to and from the occipital and parietal cortices (Fan et al., 2006). These preliminary data are valuable but more systematic surveys in larger patient groups are still needed. By combining DTI, functional MRI, voxel-based morphometry, and positron emission tomography (PET) in children and adults with PVL, Lee and colleagues assessed the correlation between motor

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

290

13. DIFFUSION IMAGING IN THE DEVELOPING BRAIN

FIGURE 13.5 Population connectivity map showing white matter regions where anisotropy correlated with age at scan in children who were born preterm and imaged between 11 and 31 months of age (Pandit et al., 2013).

impairment and FA values in major white matter tracts, regional cortical gray matter volume, and GABA receptor binding (Lee et al., 2011). TBSS analysis showed that FA values were lower in the PVL subjects than in controls in most of the major white matter pathways; however, the white matter of the corpus callosum and corticospinal tracts showed the strongest correlations with motor dysfunction. They also observed that the volume of the pre- and post-central gyri were negatively correlated with motor function and that functional connectivity was decreased in sensorimotor and visuomotor regions. These data suggest that descending motor pathways are most severely affected in PVL, although white matter anisotropy is diminished throughout the brain, consistent with diffuse white matter injury.

13.4.2 Punctate White Matter Lesions In the preterm brain nonspecific focal lesions with high signal intensity on T1-weighted imaging and frequently low signal on T2-weighted imaging are common, and for want of a more definite term usually referred to as punctate lesions (Childs et al., 2001; Cornette et al., 2002; Dyet et al., 2006; Ramenghi et al., 2007). These lesions may be seen at any gestational age up to and including term, and have also been associated

with congenital heart disease (Miller and McQuillen, 2007). In the preterm population, punctate lesions are most frequently detected along the corona radiata, in the posterior periventricular white matter, and along the optic radiation. The neuropathology of these lesions in human infants is obscure as they are not associated with mortality. In the fetal sheep model, these small focal regions of T1 hypointensity and T2 hyperintensity are indicative of focal necrotic lesions, with low FA values and elevated radial diffusivity. On histology, these lesions are characterized by reduced glial fibrillary acidic protein (GFAP) and neurofilament staining, suggesting astrocyte and axonal damage (van de Looij et al., 2012). It is not clear if punctate lesions are prognostic of later neurodevelopmental problems. Reports of neurodevelopmental outcome in infants showing these lesions have not shown an excess of adverse outcomes. However in general these studies are small and probably underpowered. A recent diffusion MRI study using TBSS and tractography assessed differences in FA between preterm infants with and without punctuate lesions at term-equivalent age, finding significantly lower FA values in the posterior limb of the internal capsule, the cerebral peduncles, decussation of the superior cerebellar peduncles, superior cerebellar peduncles and in

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

13.4. DTI IN PRETERM BRAIN INJURY

the pontine crossing tract in the punctate lesions group (Figure 13.6). In addition, there was a significant negative correlation between lesion load at term and mean FA in the corticospinal tracts defined by probabilistic tractography, suggesting that punctate lesions are associated with altered microstructure (Bassi et al., 2011).

13.4.3 Periventricular Hemorrhagic Infarction Diffusion tractography of the corticospinal tract has been shown to successfully predict hemiparesis in expreterm infants, by detecting asymmetric corticospinal tract disruption at the level of the periventricular white matter that was not apparent on conventional MRI (Son et al., 2009). In concordance with earlier work detailing the relationship between PVL and altered diffusion metrics in the posterior limb of the internal capsule and the predictive nature of these measurements for subsequent motor dysfunction (Arzoumanian et al., 2003), Son et al. (2007, 2009) also observed tract-specific FA asymmetry along the corticospinal tract present before the onset of hemiparesis. Probabilistic tractography has also shown disrupted thalamocortical connectivity at sites distant from the initial infarct in unilateral periventricular hemorrhagic infarction (Counsell et al., 2007).

291

In adolescents with hemiplegia caused by unilateral periventricular white matter injury, Thomas et al. (2005) performed tractography of a number of corticofugal, thalamocortical, and association tracts to analyze fiber count and tract-specific diffusion parameters. In patients, there was a significant reduction in fiber count in the corticospinal tract, corticobulbar tract, and superior thalamic radiation on the ipsilesional side compared with controls. Direct regional measurements at the primary lesion site and the thalamus revealed significantly increased diffusivity and decreased FA, suggestive of primary degeneration, with evidence of secondary degeneration in the corticospinal tract, brainstem, corpus callosum, and basal ganglia. By combining functional MRI and diffusion tractography, the early structural and functional responses to perinatal cerebral injury can be characterized. We have studied BOLD functional MRI and DTI in a small group of infants who had a unilateral porencephalic cyst following perinatal hemorrhagic parenchymal infarction. Serial imaging was obtained at term-corrected age and again at approximately 1 year of age. Functional responses were stimulated using a programmable inflatable balloon in the hand contralateral to the affected hemisphere (Arichi et al., 2010). Structural and functional connectivity to the activated regions was further

FIGURE 13.6

TBSS analysis between infants with punctate lesions and those with no evidence of punctate lesions. Voxels showing a significant reduction in FA in the punctate lesion group are shown in red–yellow and include the posterior limb of the internal capsule (a), the cerebral peduncles and the decussation of the superior cerebellar peduncles (b), superior cerebellar peduncles (c), and pontine crossing tract (d) (Bassi et al., 2011).

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

292

13. DIFFUSION IMAGING IN THE DEVELOPING BRAIN

characterized with probabilistic tractography and correlated low-frequency (0.01–0.1 Hz) BOLD fluctuations. In all infants studied, functional activity was identified in the affected hemisphere and probabilistic tractography delineated connectivity pathways circumventing the focal areas of damage. Activation and connectivity increased with age (Figure 13.7) (Arichi et al., 2011). These data suggest that compensatory patterns of connectivity are already present at term-equivalent age in preterm infants who had perinatal focal lesions in the early neonatal period.

13.4.4 Diffuse White Matter Abnormality (DEHSI) Diffuse excessive high signal intensity (DEHSI) is an imaging term that describes a common appearance within the white matter on a T2-weighted MR image of preterm images at term-equivalent age. The white matter shows low signal intensity on corresponding T1-weighted images. DEHSI is present in 55–80% of extremely preterm infants, when imaged at termequivalent age (Maalouf et al., 1999; Dyet et al., 2006, Skio¨ld et al., 2010). The neuropathological basis for DEHSI remains unclear but DTI studies have shown that DEHSI is associated with an increase in ADC and a decrease in FA (Counsell et al., 2006; Skio¨ld et al., 2010). These observations are indicative of subtle microstructural alterations of the developing white matter that may reflect disturbance of normal maturational processes, possibly due to loss of premyelinating, immature oligodendrocytes from excitotoxic or ischemic pathways

FIGURE 13.7

Functional activity (orange) and connectivity distributions (green and yellow) identified in the ipsilesional hemisphere in a single infant at term corrected age (a) and at 11 months corrected age (c); correlated low frequency (0.01–0.1 Hz) BOLD fluctuations in the same infant at term-corrected postmenstrual age (b) and 11 months (d).

(Volpe, 2001; Back and Rivkees, 2004; Back 2006). Using a rat model of gestational hypoxia to produce a milder white matter injury (Baud et al., 2004), in vivo imaging of the brain showed an increase in ADC values, as found in both DEHSI and diffuse PVL (Counsell et al., 2006). At histology, the white matter of these rat pups showed white matter cell death identified by TUNEL staining and increased numbers of activated microglia (Baud et al., 2004).

13.5 DIFFUSION MRI STUDIES OF THE DEVELOPING PRETERM BRAIN AND ASSOCIATION WITH NEURODEVELOPMENTAL OUTCOME Diffusion MRI has provided insight into the underlying brain tissue microstructural alterations that are associated with preterm birth. These studies have demonstrated a correlation between reduced FA in white matter regions and lower cognitive abilities in children and adolescents. Impaired visual function as early as term-equivalent age is associated with lower FA values in the optic radiations (Figure 13.8) (Bassi et al., 2008; Berman et al., 2009; Groppo et al., 2012). This relationship is independent of gestational age at birth, and the presence of lesions on conventional MRI (Bassi et al., 2008). Quantitative imaging tools are ideally suited for longitudinal studies. We explored the development of the optic radiations using DTI in preterm infants who were scanned twice, the first time in the early neonatal period and again at term-equivalent age. Visual function was not predicted by FA on the images obtained in the early neonatal period, but was significantly related to the rate of increase in FA between scans (p ¼ 0.027) and to FA on the second image (p ¼ 0.015), suggesting that microstructural maturation of the optic radiations during the late preterm period is important for normal visual function (Groppo et al., 2012). Neurodevelopmental performance in infants born preterm who have no evidence of abnormality on conventional MRI is related to FA values in a number of white matter tracts including cingulum, fornix, anterior commissure, corpus callosum, and right uncinate fasciculus, as determined with TBSS (Counsell et al., 2008). Furthermore, decreased FA and increased radial diffusivity in specific white matter regions in preterm infants as young as term-equivalent age were related to cognitive, fine-motor, and gross-motor outcome at 2-year corrected age. These findings support the potential of diffusion parameters, obtained in preterm infants at term-equivalent age, as biomarkers for subsequent neurodevelopmental performance (van Kooij et al., 2012). Using the same technique, Nagy et al. (2009) observed reduced FA bilaterally in the corpus

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

13.5. DIFFUSION MRI STUDIES OF THE DEVELOPING PRETERM BRAIN AND ASSOCIATION WITH NEURODEVELOPMENTAL OUTCOME

293

FIGURE 13.8 (a) Connectivity distributions in the optic radiations in an infant who was born at 26 weeks GA and imaged at 40 weeks postmenstrual age, overlaid on the infant’s native T2-weighted image (Bassi et al., 2008). (b) Graph showing FA versus visual assessment score. The visual assessment score counts the number of tests (out of 9) on which performance fell outside the 90th centile for term-born infants, so that higher scores represent worse performance. Black circles indicate infants with no evidence of abnormality on MRI and white circles indicate infants with evidence of focal lesions.

callosum, fornix and external capsule in a cohort of expreterm adolescents, who had previously been shown to exhibit deficits in working memory and executive functions compared to their term-born peers (Bo¨hm et al., 2004). In a separate cohort of adolescents who

were born preterm, FA values were reduced in the internal and external capsule, corpus callosum and superior and inferior longitudinal fasciculus compared to an age matched group who were born at term. Reduced FA values in specific white matter regions were related to

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

294

13. DIFFUSION IMAGING IN THE DEVELOPING BRAIN

motor, cognitive, perceptual, and mental health impairments (Skranes et al., 2007). In a more recent study by the same group, executive function in adolescents born preterm was associated with white matter integrity in the left cingulum and bilaterally in the inferior fronto-occipital fasciculi (Skranes et al., 2009). In addition, the mean FA of the whole brain white matter in children (aged between 8.8 and 11.5 years) who were born preterm correlated with full-scale IQ scores (Yung et al., 2007).

13.6 MRI IN THE TERM INFANT WITH PERINATAL BRAIN INJURY In addition to providing rich information about infant brain development, diffusion-weighted imaging/DTI is useful for assessing perinatal brain injury such as perinatal arterial stroke and hypoxic ischemic encephalopathy in the term-born infant, providing additional information to that obtained by conventional MRI and allowing the effects of neuroprotective therapies to be observed.

13.6.1 Perinatal Arterial Stroke In perinatal arterial stroke, diffusion-weighted imaging can identify injury in the acute phase when the extent of injury may not be evident on conventional MRI. The region of infarction is demonstrated as restricted diffusion (high signal intensity on the diffusion-weighted image and low signal on the ADC map), which is caused by cytotoxic edema, that is the abnormal uptake of fluid in the cytoplasm due to disrupted cellular osmoregulation. In arterial infarction the mechanism of ischemic damage in the developing brain is complex and different from mechanisms described in the adult. Current data suggest a simplified scheme in which the initial mechanism of injury is energy failure with impairment of energy-dependent ion transport disrupting homeostasis and allowing increased intracellular volume and cell swelling that results in a reduction in the extracellular space and impedes the diffusion of water molecules. This diminishes the normal signal reduction due to water diffusion observed on DWI, and hence the area of abnormality appears as higher signal intensity compared to adjacent tissue. This is followed by a prolonged phase of cell death that is predominantly apoptotic and associated with an increase in the extracellular space and increased water diffusion, resulting in a decrease in signal intensity on DWI and an increase in measured ADC values. In imaging terms the area of injury becomes less obvious on DWI towards the end of the first week, however by this time, the lesion is clearly seen on

conventional T1- and T2-weighted images. The changes in signal intensity in a cohort of 21 infants with neonatal MCA infarction have recently been systematically described (Dudink et al., 2009). On T1-weighted imaging the cortex of the infarcted hemisphere had higher signal intensity than contralateral cortex for the first 6 days and the white matter of the infarcted hemisphere had higher signal intensity than contralateral white matter for the first 9 days. Following these times the signal intensity differences were reversed with the cortex and white matter having lower signal than the contralateral side. On T2-weighted imaging, the cortex on the infarcted hemisphere had high signal intensity until around 5 days, from when it had low signal compared to the contralateral side. The affected white matter had high signal for 2–3 weeks, then became isointense relative to the contralateral side. The regions of infarction demonstrated on MRI evolved into regions of tissue loss and cysts 1–2 months after birth. DWI showed high signal intensity until 4 days after birth, from then the high signal became less apparent and by 12 days was equal or below that of the contralateral hemisphere. The region of high signal on early DWI frequently appeared larger than the region of tissue loss at 4–8 weeks (Dudink et al., 2009). DWI has also been shown to be sensitive to damage beyond the region of primary infarction in perinatal stroke. Govaert et al. (2008) described a pattern of injury to the pulvinar, characterized by hyperintensity on DWI, that occurred following focal infarction involving the cortex and white matter of the parietal, occipital and/ or temporal regions. The pulvinar injury appeared not to result directly from the primary lesion as most of the infants in their study had middle cerebral artery branch involvement and the pulvinar is supplied by the posterior cerebral artery. They proposed that this hyperintensity on DWI is an acute, secondary injury following damage to cortical targets and/or connecting axons (Govaert et al., 2008). DWI can demonstrate changes in the descending corticospinal tracts in acute perinatal arterial stroke that precede Wallerian degeneration on subsequent conventional MRI. In a study of 15 infants with perinatal arterial stroke, increased signal intensity in the ipsilateral descending corticospinal tract was seen in 8 infants at the level of the posterior limb of the internal capsule and in 5 infants at the level of the cerebral peduncles. Abnormal signal intensity in the posterior limb of the internal capsule and cerebral peduncle was followed by Wallerian degeneration and the development of a hemiplegia (de Vries et al., 2005). Also using DWI, combined with a computer-assisted technique, Kirton et al. (2007) assessed the descending corticospinal tract in 14 infants following neonatal stroke. They found their approach added predictive information over and above visual inspection of DWIs alone. They observed that, while

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

13.6. MRI IN THE TERM INFANT WITH PERINATAL BRAIN INJURY

infarct volume was not well correlated with motor outcome (p ¼ 0.45), the volume of affected descending corticospinal tract was highly correlated with motor outcome (p ¼ 0.002). All of the infants in this study who did not have involvement of the descending corticospinal tract (n ¼ 4) had normal motor outcome (assessed between 12 and 63 months of age). Diffusion tractography of the corticospinal tracts aids prognostication following perinatal arterial stroke and unilateral venous infarction (Roze et al., 2012; van der Aa et al., 2011). Asymmetries in FA, radial diffusivity, and ADC values in the corticospinal tracts were associated with hemiplegia. Asymmetries in radial diffusivity alone were associated with a subsequent mild asymmetry. In a small study looking at the prognostic value of tractography measures in the corticospinal tract to predict abnormal motor outcome, sensitivity was 91% and specificity 100% (Roze et al., 2012).

13.6.2 Hypoxic Ischemic Encephalopathy (HIE) Perinatal hypoxic ischemic brain injury remains an important cause of neurologic disability, accounting for 15–28% of children with cerebral palsy (Himmelmann et al., 2005). MRI provides excellent detail of the brain lesions characteristic of perinatal hypoxic ischemic injury. However, following a perinatal hypoxic ischemic insult, abnormalities detected with conventional MRI may take several days to evolve, a period during which maximum benefit from neuroprotective strategies, such as hypothermia, to modify brain injury may be obtained and when important clinical decisions have to be made. Diffusion MRI offers an additional and more objective method of assessing tissue integrity early after injury. We have studied the relationship between contemporaneous DWI and conventional MRI in 63 term-born neonates infants with HIE and compared the results to 15 healthy control term-born infants during the neonatal period (Rutherford et al., 2004). On DWI, early visual analysis may be particularly misleading when there have been widespread imaging abnormalities to both white matter and basal ganglia and thalami, probably because there is no normal tissue for comparison. In these infants measuring the ADC values identifies the presence of ischemic tissue. As with unilateral infarction, signal intensity changes on DWI will normalize by the end of the first week, both visually and in terms of ADC values. In infants with HIE, ADC values were significantly reduced in the first week following severe injury to either white matter (p < 0.0001) or basal ganglia and thalami (p < 0.0001) but values normalized at the end of the first week and then increased during week 2, after which time ADC values were either normal or

295

increased in infants with moderate basal ganglia and thalami and white matter lesions when compared to controls. ADC values <1.1  103 mm2/s were always associated with white matter infarction and values of <0.8  103 mm2/s with thalamic infarction. However, we found that DWI was not particularly useful for confirming the presence of moderate basal ganglia and thalami lesions (Rutherford et al., 2004). Hunt et al. (2004) studied 28 infants with perinatal HIE and found a correlation between ADC value in the posterior limb of the internal capsule and neuromotor outcome at early assessment (12.9  7 months) (Hunt et al., 2004). Vermeulen et al. (2008) also assessed the predictive value of DWI following HIE. They found that infants with poor outcome had significantly lower ADC values at early imaging in a number of regions including thalamus, putamen, Rolandic cortex, hippocampus, and posterior limb of the internal capsule, and that, of these, low ADC values in the posterior limb of the internal capsule were the best predictor of poor motor outcome (p ¼ 0.017) and that all infants who had an ADC value of < 0.85  103 mm2/s in the posterior limb of the internal capsule had poor outcome (Vermeulen et al., 2008). We have shown that during the first week after birth FA values in the white matter were significantly decreased not only in infants with severe abnormality but also in those with moderate abnormality (Ward et al., 2006). Of particular interest, given the phenomenon of pseudo-normalization that occurs with ADC values, is that in severe white matter injury FA values remained significantly decreased during the second and third weeks from delivery. FA was significantly decreased in the first week throughout the basal ganglia and thalami and became progressively more abnormal within the region of the ventrolateral nuclei. These findings suggest that a combination of ADC and FA values derived from DTI combined with visual analysis of conventional imaging currently offers the best approach for identifying abnormal tissue and estimating the timing of the insult (Ward et al., 2006). All of the diffusion MRI studies of HIE discussed above have used an ROI-based approach which is timeconsuming and potentially introduces observer error. We have recently performed a feasibility study to assess the use of TBSS in infants with HIE (Porter et al., 2010). Compared with controls, infants with HIE had reduced FA in several white matter tracts: posterior limb of the internal capsule, the external capsule, the corpus callosum, the fornix, the cingulum, the superior longitudinal fasciculus, the superior corona radiata, and the inferior longitudinal fasciculus. With an increase in the number of studies using targeted interventions following perinatal injury, such as hypothermia and xenon, there is a growing need for an imaging biomarker than can assess treatment efficacy in the neonatal period. Using TBSS, we

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

296

13. DIFFUSION IMAGING IN THE DEVELOPING BRAIN

FIGURE 13.9 Correlation between FA values in the early neonatal period and subsequent performance scores. Mean FA-skeleton (yellow) overlaid on mean FA image. Voxels where FA is significantly correlated to performance scores in infants following therapeutic hypothermia are shown in blue (Tusor et al., 2012).

observed widespread correlations between FA values in the perinatal period and early neurodevelopmental outcome in infants who had suffered HIE and who had been treated with therapeutic hypothermia (Figure 13.9) (Tusor et al., 2012). This study suggests that voxel-wise analysis tools for diffusion imaging data, such as TBSS, have the potential to assess treatment response or compare treated and control groups and it is possible that they may, following appropriate validation, provide surrogate markers of outcome.

13.7 FUTURE DIRECTIONS From the above discussion it is clear that diffusion MRI provides useful information regarding white matter microstructure, is able to objectively assess differences between groups, and that measures derived from diffusion MRI are associated with neurodevelopmental performance. However, diffusion MRI approaches have some limitations. In particular, the diffusion tensor model effectively measures the net microscopic diffusion of water in a voxel, but its ability to resolve multiple fiber bundle orientations inside an imaging voxel is limited. However, crossing, kissing, branching, and inter-digitating fibers exist throughout the brain and studying such complex white matter architecture may provide important information regarding brain development and plasticity. The challenge to identify the multiple fiber directions contained within a single voxel has

led to recent developments of diffusion MRI techniques towards seeking alternative algorithms, models, or encoding schemes in order to gain more detailed information about the underlying orientation of white matter fibers. These approaches include diffusion spectrum imaging and q-ball imaging, which are described elsewhere in this book (see Chapter 6). They essentially create orientation distribution functions (ODFs) that provide a distribution of possible directions for the directional bias of diffusion-enabling crossing fibers to be resolved. Disadvantages of diffusion spectrum imaging and q-ball imaging are that they require the application of much stronger diffusion-encoding gradients and the acquisition of many more gradient directions. The constrained spherical deconvolution model aims to produce an estimate of fiber orientations within an imaging voxel (Tournier et al., 2007). The data are considered to be the convolution of a fiber ODF with a response function, where the response function can be estimated from single-fiber high-anisotropy voxels in the data. The data can therefore be deconvolved with the response function, yielding the fiber ODF which can then be used for tractography. We have recently applied this approach to analyze neonatal and pediatric diffusion MRI data (64 directions, b-value ¼ 2500 s/mm2, acquired at 3 tesla) (Figure 13.10). Our results show that it is possible to model multiple fiber directions in an imaging voxel in the immature brain. However, the scanning time for this sequence was approximately

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

13.8. CONCLUSIONS

297

spherical deconvolution and whole-brain connectome approaches, which may improve our understanding of the impact of prematurity or perinatal brain injury on subsequent axonal and neuronal development and thereby help inform decisions about future therapeutic targets.

(a)

References

(b)

FIGURE 13.10 Constrained spherical deconvolution images obtained in a term control infant. (a) Coronal image showing corpus callosum (red), corticospinal tracts (blue), and anterior limb of the internal capsule (green). (b) Axial view of the cerebellum. Images courtesy of Donald Tournier.

16 min, which is longer than most diffusion MRI acquisitions currently used in the pediatric population and may be not always be suitable for imaging uncooperative neonates and children, where image artifact due to motion is frequently a problem.

13.8 CONCLUSIONS Diffusion MRI has provided valuable information on alterations in the underlying tissue microstructure during brain development and in perinatal brain injury. In combination with computerized analysis techniques, diffusion MRI data can be used as an imaging biomarker to assess the efficacy of treatment and can be used as a surrogate measure of subsequent performance. More advanced techniques are beginning to be employed to assess the infant brain, such as constrained

Agresti, C., D’Urso, D., Levi, G., 1996. Reversible inhibitory effects of interferon-gamma and tumour necrosis factor-alpha on oligodendroglial lineage cell proliferation and differentiation in vitro. Eur. J. Neurosci. 8, 1106–1116. Anjari, M., Srinivasan, L., Allsop, J.M., Hajnal, J.V., Rutherford, M.A., Edwards, A.D., Counsell, S.J., 2007. Diffusion tensor imaging with tract-based spatial statistics reveals local white matter abnormalities in preterm infants. NeuroImage 35, 1021–1027. Anjari, M., Counsell, S.J., Srinivasan, L., Allsop, J.M., Hajnal, J.V., Rutherford, M.A., Edwards, A.D., 2009. The association of lung disease with cerebral white matter abnormalities in preterm infants. Pediatrics 124, 268–276. Arichi, T., Moraux, A., Melendez, A., Doria, V., Groppo, M., Merchant, N., Combs, S., Burdet, E., Larkman, D.J., Counsell, S.J., Beckmann, C.F., Edwards, A.D., 2010. Somatosensory cortical activation identified by functional MRI in preterm and term infants. NeuroImage 49, 2063–2071. Arichi, T., Counsell, S.J., Merchant, N., Tusor, N., Cowan, F.M., Rutherford, M.A., Beckmann, C.F., Burdet, E., Edwards, A.D., 2011. Characterization of early sonatosensory functional and structural cerebral organization following neonatal haemorrhagic parenchymal infarction with functional magnetic resonance imaging and probabilistic tractography. Dev. Med. Child Neurol. 1 (Suppl 53), 4–8. Arzoumanian, Y., Mirmiran, M., Barnes, P.D., Woolley, K., Ariagno, R.L., Moseley, M.E., Fleisher, B.E., Atlas, S.W., 2003. Diffusion tensor brain imaging findings at term-equivalent age may predict neurologic abnormalities in low birth weight preterm infants. AJNR 24 (8), 1646–1653. Back, S.A., Rivkees, S.A., 2004. Emerging concepts in periventricular white matter injury. Semin Perinatol 28 (6), 405–414. Back, S.A., Luo, N.L., Mallinson, R.A., O’Malley, J.P., Wallen, L.D., Frei, B., Morrow, J.D., Petito, C.K., Roberts Jr, C.T., Murdoch, G.H., Montine, T.J., 2005. Selective vulnerability of preterm white matter to oxidative damage defined by F2-isoprostanes. Ann. Neurol. 58, 108–120. Back, S.A., 2006. Perinatal white matter injury: the changing spectrum of pathology and emerging insights into pathogenetic mechanisms. Ment. Retard. Dev. Disabil. Res. Rev. 12, 129–140. Ball, G., Boardman, J.P., Aljabar, P., Pandit, A., Arichi, T., Merchant, N., Rueckert, D., Edwards, A.D., Counsell, S.J., 2003. The influence of preterm birth on the developing thalamocortical connectome. Cortex 49 (6), 1711–1721 [E pub ahead of print]. Ball, G., Counsell, S.J., Anjari, M., Merchant, N., Arichi, T., Doria, V., Rutherford, M.A., Edwards, A.D., Rueckert, D., Boardman, J.P., 2010. An optimised tract-based spatial statistics protocol for neonates: Applications to prematurity and chronic lung disease. NeuroImage 53, 94–102. Ball, G., Boardman, J.P., Rueckert, D., Aljabar, P., Arichi, T., Merchant, N., Gousias, I.S., Edwards, A.D., Counsell, S.J., 2012. The effect of preterm birth on thalamic and cortical development. Cerebr. Cortex. 12, 1016–1024. Ball, G., Srinivasan, L., Aljabar, P., Counsell, S.J., Durighel, G., Hajnal, J.V., Rutherford, M.A., Edwards, A.D., 2013. Development

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

298

13. DIFFUSION IMAGING IN THE DEVELOPING BRAIN

of cortical microstructure in the preterm human brain. PNAS 110 (23), 9541–9546. Bassi, L., Ricci, D., Volzone, A., Allsop, J.M., Srinivasan, L., Pai, A., Ribes, C., Ramenghi, L.A., Mercuri, E., Mosca, F., Edwards, A.D., Cowan, F.M., Rutherford, M.A., Counsell, S.J., 2008. Probabilistic diffusion tractography of the optic radiations and visual function in preterm infants at term equivalent age. Brain 131, 573–582. Bassi, L., Chew, A., Merchant, N., Ball, G., Ramenghi, L., Boardman, J., Allsop, J.M., Doria, V., Arichi, T., Mosca, F., Edwards, A.D., Cowan, F.M., Rutherford, M.A., Counsell, S.J., 2011. Diffusion tensor imaging in preterm infants with punctate white matter lesions. Pediatr. Res. 69, 561–566. Baud, O., Daire, J.L., Dalmaz, Y., Fontaine, R.H., Krueger, R.C., Sebag, G., Evrard, P., Gressens, P., Verney, C., 2004. Gestational hypoxia induces white matter damage in neonatal rats: a new model of periventricular leukomalacia. Brain Pathol. 14 (1), 1–10. Berman, J.I., Glass, H.C., Miller, S.P., Mukherjee, P., Ferriero, D.M., Barkovich, A.J., Vigneron, D.B., Henry, R.G., 2009. Quantitative fiber tracking analysis of the optic radiation correlated with visual performance in premature newborns. Am. J. Neuroradiol. 30, 120–124. Bo¨hm, B., Smedler, A.C., Forssberg, H., 2004. Impulse control, working memory and other executive functions in preterm children when starting school. Acta Paediatr. 93 (10), 1363–1371. Bullmore, E., Sporns, O., 2009. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10 (3), 186–198. Chau, V., Brant, R., Poskitt, K.J., Tam, E.W., Synnes, A., Miller, S.P., 2012. Postnatal infection is associated with widespread abnormalities of brain development in premature newborns. Pediatr. Res. 71 (3), 274–279. Childs, A.M., Ramenghi, L.A., Cornette, L., Tanner, S.F., Arthur, R.J., Martinez, D., Levene, M.I., 2001. Cerebral maturation in premature infants: quantitative assessment using MR imaging. AJNR Am. J. Neuroradiol. 22 (8), 1577–1582. Cornette, L.G., Tanner, S.F., Ramenghi, L.A., Miall, L.S., Childs, A.M., Arthur, R.J., Martinez, D., Levene, M.I., 2002. Magnetic resonance imaging of the infant brain: anatomical characteristics and clinical significance of punctate lesions. Arch. Dis. Child Fetal. Neonatal. Educ. 86 (3), F171–F177. Counsell, S.J., Shen, Y., Boardman, J.P., Larkman, D.J., Kapellou, O., Ward, P., Allsop, J.M., Cowan, F.M., Hajnal, J.V., Edwards, A.D., Rutherford, M.A., 2006. Axial and radial diffusivity in preterm infants who have diffuse white matter changes on magnetic resonance imaging at term-equivalent age. Pediatrics 117, 376–386. Counsell, S.J., Dyet, L.E., Larkman, D.J., Nunes, R.G., Boardman, J.P., Allsop, J.M., Fitzpatrick, J.A., Srinivasan, L., Cowan, F.M., Hajnal, J.V., Rutherford, M.A., Edwards, A.D., 2007. Thalamocortical connectivity in children born preterm mapped using probabilistic magnetic resonance tractography. NeuroImage 34 (3), 896–904. Counsell, S.J., Edwards, A.D., Chew, A.T., Anjari, M., Dyet, L.E., Srinivasan, L., Boardman, J.P., Allsop, J.M., Hajnal, J.V., Rutherford, M.A., Cowan, F.M., 2008. Specific relations between neurodevelopmental abilities and white matter microstructure in children born preterm. Brain 131, 3201–3208. Deipolyi, A.R., Mukherjee, P., Gill, K., Henry, R.G., Partridge, S.C., Veeraraghavan, S., Jin, H., Lu, Y., Miller, S.P., Ferriero, D.M., Vigneron, D.B., Barkovich, A.J., 2005. Comparing microstructural and macrostructural development of the cerebral cortex in premature newborns: diffusion tensor imaging versus cortical gyration. NeuroImage 27 (3), 579–586. de Vries, L.S., Van der, G.J., Van, H.I, Groenendaal, F., 2005. Prediction of outcome in new-born infants with arterial ischaemic stroke

using diffusion-weighted magnetic resonance imaging. Neuropediatrics 36 (1), 12–20. Dobbing, J., Sands, J., 1973. Quantitative growth and development of human brain. Arch. Dis. Child 48 (10), 757–767. Dudink, J., Lequin, M., van Pul, C., Buijs, J., Conneman, N., van Goudoever, J., Govaert, P., 2007. Fractional anisotropy in white matter tracts of very-low-birth-weight infants. Pediatr. Radiol. 37, 1216–1223. Dudink, J., Mercuri, E., Al-Nakib, L., Govaert, P., Counsell, S.J., Rutherford, M.A., Cowan, F.M., 2009. Evolution of unilateral perinatal arterial ischemic stroke on conventional and diffusion weighted magnetic resonance imaging. AJNR Am. J. Neuroradiol. 30 (5), 998–1004. Dudink, J., Buijs, J., Govaert, P., van Zwol, A.L., Conneman, N., van Goudoever, J.B., Lequin, M., 2010. Diffusion tensor imaging of the cortical plate and subplate in very-low-birth-weight infants. Pediatr. Radiol. 40 (8), 1397–1404. Dyet, L., Kennea, N., Counsell, S.J., Maalouf, E., Ajaye-Obe, M., Duggan, P., Harrison, M., Allsop, J., Hajnal, J., Herlihy, A., Edwards, B., Laroche, S., Cowan, F., Rutherford, M., Edwards, A.D., 2006. The natural history of brain lesions in extremely preterm infants investigated by MR imaging. Pediatrics 118, 536–548. Fan, G.G., Yu, B., Quan, S.M., Sun, B.H., Guo, Q.Y., 2006. Potential of diffusion tensor MRI in the assessment of periventricular leukomalacia. Clin. Radiol. 61 (4), 358–364. Fan, Y., Shi, F., Smith, J.K., Lin, W., Gilmore, J.H., Shen, D., 2011. Brain anatomical networks in early human brain development. NeuroImage 54 (3), 1862–1871. Gao, W., Lin, W., Chen, Y., Gerig, G., Smith, J.K., Jewells, V., Gilmore, J.H., 2009. Temporal and spatial development of axonal maturation and myelination of white matter in the developing brain. AJNR Am. J. Neuroradiol. 30 (2), 290–296. Govaert, P., Zingman, A., Jung, Y.H., Dudink, J., Swarte, R., Zecic, A., Meersschaut, V., van Engelen, S., Lequin, M., 2008. Network injury to pulvinar with neonatal arterial ischemic stroke. NeuroImage 39 (4), 1850–1857. Ghosh, A., Shatz, C.J., 1993. A role for subplate neurons in the patterning of connections from thalamus to neocortex. Development 117 (3), 1031–1047. Griffith, J.L., Shimony, J.S., Cousins, S.A., Rees, S.E., McCurnin, D.C., Inder, T.E., Neil, J.J., 2012. MR imaging correlates of white-matter pathology in a preterm baboon model. Pediatr. Res. 71 (2), 185–191. Groppo, M., Ricci, D., Bassi, L., Merchant, N., Doria, V., Arichi, T., Allsop, J.M., Ramenghi, L., Fox, M.J., Cowan, F.M., Counsell, S.J., Edwards, A.D., 2012. Development of the optic radiations and visual function after premature birth. Cortex. http://dx.doi.org/ 10.1016/j.cortex.2012.02.008, 2012. [Epub ahead of print]. Hagmann, P., Kurant, M., Gigandet, X., Thiran, P., Wedeen, V.J., Meuli, R., Thiran, J.P., 2007. Mapping human whole-brain structural networks with diffusion MRI. PLoS One 2 (7), e597. Hermoye, L., Saint-Martin, C., Cosnard, G., Lee, S.K., Kim, J., Nassogne, M.C., Menten, R., Clapuyt, P., Donohue, P.K., Hua, K., Wakana, S., Jiang, H., van Zijl, P.C., Mori, S., 2006. Pediatric diffusion tensor imaging: normal database and observation of the white matter maturation in early childhood. NeuroImage 29 (2), 493–504. Himmelmann, K., Hagberg, G., Beckung, E., Hagberg, B., Uvebrant, P., 2005. The changing panorama of cerebral palsy in Sweden. IX. Prevalence and origin in the birth-year period 1995–1998. Acta. Paediatr. 94 (3), 287–294. Huang, H., Yamamoto, A., Hossain, M.A., Younes, L., Mori, S., 2008. Quantitative cortical mapping of fractional anisotropy in developing rat brains. J. Neurosci. 28 (6), 1427–1433. Hunt, R.W., Neil, J.J., Coleman, L.T., Kean, M.J., Inder, T.E., 2004. Apparent diffusion coefficient in the posterior limb of the internal

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

13.8. CONCLUSIONS

capsule predicts outcome after perinatal asphyxia. Pediatrics 114 (4), 999–1003. Huppi, P.S., Maier, S.E., Peled, S., Zientara, G.P., Barnes, P.D., Jolesz, F.A., Volpe, J.J., 1998. Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging. Pediatr. Res. 44, 584–590. Inder, T., Huppi, P.S., Zientara, G.P., Maier, S.E., Jolesz, F.A., di Salvo, D., Robertson, R., Barnes, P.D., Volpe, J.J., 1999. Early detection of periventricular leukomalacia by diffusion-weighted magnetic resonance imaging techniques. J. Pediatr. 134 (5), 631–634. Iturria-Medina, Y., Sotero, R.C., Canales-Rodrı´guez, E.J., Alema´nGo´mez, Y., Melie-Garcı´a, L., 2008. Studying the human brain anatomical network via diffusion-weighted MRI and Graph Theory. NeuroImage 40 (3), 1064–1076. Jessen, K.R., Mirsky, R., 1991. Schwann cell precursors and their development. Glia 4 (2), 185–194. Jiang, S., Xue, H., Counsell, S., Anjari, M., Allsop, J., Rutherford, M., Rueckert, D., Hajnal, J.V., 2009. Diffusion tensor imaging (DTI) of the brain in moving subjects: Application to in-utero fetal and exutero studies. Magn. Reson. Med. 62 (3), 645–655. Kirton, A., Shroff, M., Visvanathan, T., deVeber, G., 2007. Quantified corticospinal tract diffusion restriction predicts neonatal stroke outcome. Stroke 38 (3), 974–980. Kostovic, I., Judas, M., Rados, M., Hrabac, P., 2002. Laminar organization of the human fetal cerebrum revealed by histochemical markers and magnetic resonance imaging. Cereb. Cortex. 12 (5), 536–544. Kroenke, C.D., Van Essen, D.C., Inder, T.E., Rees, S., Bretthorst, G.L., Neil, J.J., 2007. Microstructural changes of the baboon cerebral cortex during gestational development reflected in magnetic resonance imaging diffusion anisotropy. J. Neurosci. 27 (46), 12506–12515. Kroenke, C.D., Taber, E.N., Leigland, L.A., Knutsen, A.K., Bayly, P.V., 2009. Regional patterns of cerebral cortical differentiation determined by diffusion tensor MRI. Cereb. Cortex. 19 (12), 2916–2929. Lazar, M., 2010. Mapping brain anatomical connectivity using white matter tractography. NMR Biomed. 23 (7), 821–835. Lee, J.D., Park, H.J., Park, E.S., Oh, M.K., Park, B., Rha, D.W., Cho, S.R., Kim, E.Y., Park, J.Y., Kim, C.H., Kim, D.G., Park, C.I., 2011. Motor pathway injury in patients with periventricular leucomalacia and spastic diplegia. Brain 134 (Pt 4), 1199–1210. Maalouf, E.F., Duggan, P.J., Rutherford, M.A., Counsell, S.J., Fletcher, A.M., Battin, M., Cowan, F., Edwards, A.D., 1999. Magnetic resonance imaging of the brain in a cohort of extremely preterm infants. J. Pediatr. 135, 351–357. Maas, L.C., Mukherjee, P., Carballido-Gamio, J., Veeraraghavan, S., Miller, S.P., Partridge, S.C., Henry, R.G., Barkovich, A.J., Vigneron, D.B., 2004. Early laminar organization of the human cerebrum demonstrated with diffusion tensor imaging in extremely premature infants. NeuroImage 22 (3), 1134–1140. Marin-Padilla, M., 1992. Ontogenesis of the pyramidal cell of the mammalian neocortex and developmental cytoarchitectonics: a unifying theory. J. Comp. Neurol. 321 (2), 223–240. McKinstry, R.C., Mathur, A., Miller, J.H., Ozcan, A., Snyder, A.Z., Schefft, G.L., Almli, C.R., Shiran, S.I., Conturo, T.E., Neil, J.J., 2002. Radial organization of developing preterm human cerebral cortex revealed by non-invasive water diffusion anisotropy MRI. Cereb. Cortex. 12 (12), 1237–1243. McQuillen, P.S., Sheldon, R.A., Shatz, C.J., Ferriero, D.M., 2003. Selective vulnerability of subplate neurons after early neonatal hypoxia-ischemia. J. Neurosci. 23 (8), 3308–3315. Miller, S.P., McQuillen, P.S., 2007. Neurology of congenital heart disease: insight from brain imaging. Arch. Dis. Child Fetal. Neonatal. Educ. 92 (6), F435–F437.

299

Miller, S.P., Vigneron, D.B., Henry, R.G., Bohland, M.A., CeppiCozzio, C., Hoffman, C., Newton, N., Partridge, J.C., Ferriero, D.M., Barkovich, A.J., 2002. Serial quantitative diffusion tensor MRI of the premature brain: development in newborns with and without injury. J. Magn. Reson. Imaging 16, 621–632. Mukherjee, P., Miller, J.H., Shimony, J.S., Philip, J.V., Nehra, D., Snyder, A.Z., Conturo, T.E., Neil, J.J., McKinstry, R.C., 2002. Diffusion-tensor MR imaging of gray and white matter development during normal human brain maturation. Am. J. Neuroradiol. 23, 1445–1456. Nagae, L.M., Hoon Jr, A.H., Stashinko, E., Lin, D., Zhang, W., Levey, E., Wakana, S., Jiang, H., Leite, C.C., Lucato, L.T., van Zijl, P.C., Johnston, M.V., Mori, S., 2007. Diffusion tensor imaging in children with periventricular leukomalacia: variability of injuries to white matter tracts. AJNR Am. J. Neuroradiol. 28 (7), 1213–1222. Nagy, Z., Ashburner, J., Andersson, J., Jbabdi, S., Draganski, B., Skare, S., Bo¨hm, B., Smedler, A.C., Forssberg, H., Lagercrantz, H., 2009. Structural correlates of preterm birth in the adolescent brain. Pediatrics 124 (5), e964–e972. Neil, J.J., Shiran, S.I., McKinstry, R.C., Schefft, G.L., Snyder, A.Z., Almli, C.R., Akbudak, E., Aronovitz, J.A., Miller, J.P., Lee, B.C., Conturo, T.E., 1998. Normal brain in human newborns: apparent diffusion coefficient and diffusion anisotropy measured by using diffusion tensor MR imaging. Radiology 209, 57–66. Pandit, A.S., Robinson, E., Aljabar, P., Ball, G., Gousias, I.S., Wang, Z., Hajnal, J.V., Rueckert, D., Counsell, S.J., Montana, G., Edwards, A.D., 2013. Cerebral Cortex. doi:10.1093/cercor/bht086. Partridge, S.C., Mukherjee, P., Henry, R.G., Miller, S.P., Berman, J.I., Jin, H., Lu, Y., Glenn, O.A., Ferriero, D.M., Barkovich, A.J., Vigneron, D.B., 2004. Diffusion tensor imaging: serial quantitation of white matter tract maturity in premature newborns. NeuroImage 22 (3), 1302–1314. Porter, E.J., Counsell, S.J., Edwards, A.D., Allsop, J., Azzopardi, D., 2010. Tract based spatial statistics of magnetic resonance images to assess disease and treatment effects in perinatal asphyxial encephalopathy. Pediatr. Res. 68 (3), 205–209. Prayer, D., Barkovich, A.J., Kirschner, D.A., Prayer, L.M., Roberts, T.P., Kucharczyk, J., Moseley, M.E., 2001. Visualization of nonstructural changes in early white matter development on diffusion-weighted MR images: evidence supporting premyelination anisotropy. AJNR Am. J. Neuroradiol. 22 (8), 1572–1576. Rakic, P., 2003. Developmental and evolutionary adaptations of cortical radial glia. Cereb. Cortex. 13 (6), 541–549. Ramenghi, L.A., Fumagalli, M., Righini, A., Bassi, L., Groppo, M., Parazzini, C., Bianchini, E., Triulzi, F., Mosca, F., 2007. Magnetic resonance imaging assessment of brain maturation in preterm neonates with punctate white matter lesions. Neuroradiology 49 (2), 161–167. Robinson, E.C., Hammers, A., Ericsson, A., Edwards, A.D., Rueckert, D., 2010. Identifying population differences in wholebrain structural networks: a machine learning approach. NeuroImage 50 (3), 910–919. Roelants-van Rijn, A.M., Nikkels, P.G., Groenendaal, F., van Der Grond, J., Barth, P.G., Snoeck, I., Beek, F.J., de Vries, L.S., 2001. Neonatal diffusion-weighted MR imaging: relation with histopathology or follow-up MR examination. Neuropediatrics 32 (6), 286–294. Roze, E., Harris, P.A., Ball, G., Elorza, L.Z., Braga, R.M., Allsop, J.M., Merchant, N., Porter, E., Arichi, T., Edwards, A.D., Rutherford, M.A., Cowan, F.M., Counsell, S.J., 2012. Tractography of the corticospinal tracts in infants with focal perinatal injury: comparison with normal controls and to motor development. Neuroradiology 54 (5), 507–516.

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT

300

13. DIFFUSION IMAGING IN THE DEVELOPING BRAIN

Rutherford, M., Counsell, S., Allsop, J., Boardman, J., Kapellou, O., Larkman, D., Hajnal, J., Edwards, D., Cowan, F., 2004. Diffusionweighted magnetic resonance imaging in term perinatal brain injury: a comparison with site of lesion and time from birth. Pediatrics 114, 1004–1014. Sakuma, H., Nomura, Y., Takeda, K., Tagami, T., Nakagawa, T., Tamagawa, Y., Ishii, Y., Tsukamoto, T., 1991. Adult and neonatal human brain: diffusional anisotropy and myelination with diffusion-weighted MR imaging. Radiology 180 (1), 229–233. Sidman, R.L., Rakic, P., 1973. Neuronal migration, with special reference to developing human brain: a review. Brain Res. 62 (1), 1–35. Sizonenko, S.V., Camm, E.J., Garbow, J.R., Maier, S.E., Inder, T.E., Williams, C.E., Neil, J.J., Huppi, P.S., 2007. Developmental changes and injury induced disruption of the radial organization of the cortex in the immature rat brain revealed by in vivo diffusion tensor MRI. Cereb. Cortex. 17 (11), 2609–2617. Skio¨ld, B., Horsch, S., Hallberg, B., Engstro¨m, M., Nagy, Z., Mosskin, M., Blennow, M., Ade´n, U., 2010. White matter changes in extremely preterm infants, a population-based diffusion tensor imaging study. Acta. Paediatr. 99 (6), 842–849. Skranes, J., Vangberg, T.R., Kulseng, S., Indredavik, M.S., Evensen, K.A., Martinussen, M., Dale, A.M., Haraldseth, O., Brubakk, A.M., 2007. Clinical findings and white matter abnormalities seen on diffusion tensor imaging in adolescents with very low birth weight. Brain 130 (Pt 3), 654–666. Skranes, J., Lohaugen, G.C., Martinussen, M., Indredavik, M.S., Dale, A.M., Haraldseth, O., Vangberg, T.R., Brubakk, A.M., 2009. White matter abnormalities and executive function in children with very low birth weight. Neuroreport 20 (3), 263–266. Smith, S.M., Jenkinson, M., Johansen-Berg, H., Rueckert, D., Nichols, T.E., Mackay, C.E., Watkins, K.E., Ciccarelli, O., Cader, M.Z., Matthews, P.M., Behrens, T.E., 2006. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. NeuroImage 31 (4), 1487–1505. Son, S.M., Ahn, Y.H., Sakong, J., Moon, H.K., Ahn, S.H., Lee, H., Yu, I.K., Shin, Y.J., Jang, S.H., 2007. Diffusion tensor imaging demonstrates focal lesions of the corticospinal tract in hemiparetic patients with cerebral palsy. Neurosci. Lett. 420 (1), 34–38. Son, S.M., Park, S.H., Moon, H.K., Lee, E., Ahn, S.H., Cho, Y.W., Byun, W.M., Jang, S.H., 2009. Diffusion tensor tractography can predict hemiparesis in infants with high risk factors. Neurosci. Lett. 451 (1), 94–97. Takagi, T., Nakamura, M., Yamada, M., Hikishima, K., Momoshima, S., Fujiyoshi, K., Shibata, S., Okano, H.J., Toyama, Y., Okano, H., 2009. Visualization of peripheral nerve degeneration and regeneration: monitoring with diffusion tensor tractography. NeuroImage 44 (3), 884–892. Talos, D.M., Fishman, R.E., Park, H., Folkerth, R.D., Follett, P.L., Volpe, J.J., Jensen, F.E., 2006. Developmental regulation of alphaamino-3-hydroxy-5-methyl-4-isoxazole-propionic acid receptor subunit expression in forebrain and relationship to regional susceptibility to hypoxic/ischemic injury. I. Rodent cerebral white matter and cortex. J. Comp. Neurol. 497, 42–60. Thomas, B., Eyssen, M., Peeters, R., Molenaers, G., Van Hecke, P., De Cock, P., Sunaert, S., 2005. Quantitative diffusion tensor imaging in cerebral palsy due to periventricular white matter injury. Brain 128 (Pt 11), 2562–2577. Tournier, J.D., Calamante, F., Connelly, A., 2007. Robust determination of the fibre orientation distribution in diffusion MRI: non-

negativity constrained susper-resolved spherical deconvolution. Neuroimage 35 (4), 1459–1472. Trivedi, R., Gupta, R.K., Husain, N., Rathore, R.K., Saksena, S., Srivastava, S., Malik, G.K., Das, V., Pradhan, M., Sarma, M.K., Pandey, C.M., Narayana, P.A., 2009. Region-specific maturation of cerebral cortex in human fetal brain: diffusion tensor imaging and histology. Neuroradiology 51 (9), 567–576. Tusor, N., Wusthoff, C., Smee, N., Merchant, N., Arichi, T., Allsop, J.M., Cowan, F.M., Azzopardi, D., Edwards, A.D., Counsell, S.J., 2012. Prediction of neurodevelopmental outcome after hypoxic-ischemic encephalopathy treated with hypothermia by diffusion tensor imaging analysed using tract-based spatial statistics. Pediatr. Res. 72 (1), 63–69. Tymofiyeva, O., Hess, C.P., Ziv, E., Tian, N., Bonifacio, S.L., McQuillen, P.S., Ferriero, D.M., Barkovich, A.J., Xu, D., 2012. Towards the “baby connectome”: mapping the structural connectivity of the newborn brain. PLoS One 7 (2), e31029. van Kooij, B.J.M., de Vries, L.S., Ball, G., van Haaster, I.C., Benders, M.J.N.L., Groenendaal, F., Counsell, S.J., 2012. Neonatal tract-based spatial statistics findings and outcome in preterm infants. AJNR 33, 188–194. van de Looij, Y., Lodygensky, G.A., Dean, J., Lazeyras, F., Hagberg, H., Kjellmer, I., Mallard, C., Hu¨ppi, P.S., Sizonenko, S.V., 2012. Highfield diffusion tensor imaging characterization of cerebral white matter injury in LPS-exposed fetal sheep. Pediatr. Res. 72 (3), 285–292. van der Aa, N.E., Leemans, A., Northington, F.J., van Straaten, H.L., van Haastert, I.C., Groenendaal, F., Benders, M.J., de Vries, L.S., 2011. Does diffusion tensor imaging-based tractography at 3 months of age contribute to the prediction of motor outcome after perinatal arterial ischemic stroke? Stroke 42 (12), 3410–3414. Vermeulen, R.J., van Schie, P.E., Hendrikx, L., Barkhof, F., van Weissenbruch, M., Knol, D.L., Pouwels, P.J., 2008. Diffusionweighted and conventional MR imaging in neonatal hypoxic ischemia: two-year follow-up study. Radiology 249 (2), 631–639. Volpe, J.J., 2001. Neurobiology of periventricular leukomalacia in the premature infant. Pediatr. Res. 50, 553–562. Volpe, J.J., 2003. Cerebral white matter injury of the premature infantmore common than you think. Pediatrics 112 (1 Pt 1), 176–180. Volpe, J.J., 2009. The encephalopathy of prematurity-brain injury and impaired brain development inextricably intertwined. Semin. Pediatr. Neurol. 16, 167–178. Ward, P., Counsell, S., Allsop, J., Cowan, F., Shen, Y., Edwards, D., Rutherford, M., 2006. Reduced fractional anisotropy on diffusion tensor magnetic resonance imaging after hypoxic-ischemic encephalopathy. Pediatrics 117, e19–e30. Wimberger, D.M., Roberts, T.P., Barkovich, A.J., Prayer, L.M., Moseley, M.E., Kucharczyk, J., 1995. Identification of “premyelination” by diffusion-weighted MRI. J. Comp. Assist. Tomogr. 19, 28–33. Yap, P.T., Fan, Y., Chen, Y., Gilmore, J.H., Lin, W., Shen, D., 2011. Development trends of white matter connectivity in the first years of life. PLOS One 6 (9), e24678. Yakolev, P.I., Lecours, A.R., 1967. The myelogenic cycles of regional maturation of the brain. In: Minowski, A. (Ed.), Regional Development of the Brain in Early Life. Blackwell, Oxford, pp. 3–70. Yung, A., Poon, G., Qiu, D.Q., Chu, J., Lam, B., Leung, C., Goh, W., Khong, P.L., 2007. White matter volume and anisotropy in preterm children: a pilot study of neurocognitive correlates. Pediatr. Res. 61 (6), 732–736. Zalesky, A., Fornito, A., Bullmore, E., 2012. On the use of correlation as a measure of network connectivity. NeuroImage 60 (4), 2096–2106.

II. DIFFUSION MRI FOR QUANTITATIVE MEASUREMENT