James P. Boardman

Abnormal Cortical Development after Premature Birth Shown by Altered Allometric Scaling of Brain Growth

Background We postulated that during ontogenesis cortical surface area and cerebral volume are related by a scaling law whose exponent gives a quantitative measure of cortical development. We used this approach to investigate the hypothesis that premature termination of the intrauterine environment by preterm birth reduces cortical development in a dose-dependent manner, providing a neural substrate for functional impairment. Methods and Findings We analyzed 274 magnetic resonance images that recorded brain growth from 23 to 48 wk of gestation in 113 extremely preterm infants born at 22 to 29 wk of gestation, 63 of whom underwent neurodevelopmental assessment at a median age of 2 y. Cortical surface area was related to cerebral volume by a scaling law with an exponent of 1.29 (95% confidence interval, 1.25–1.33), which was proportional to later neurodevelopmental impairment. Increasing prematurity and male gender were associated with a lower scaling exponent (p < 0.0001) independent of intrauterine or postnatal somatic growth. Conclusions Human brain growth obeys an allometric scaling relation that is disrupted by preterm birth in a dose-dependent, sexually dimorphic fashion that directly parallels the incidence of neurodevelopmental impairments in preterm infants. This result focuses attention on brain growth and cortical development during the weeks following preterm delivery as a neural substrate for neurodevelopmental impairment after premature delivery.

Specific relations between neurodevelopmental abilities and white matter microstructure in children born preterm

Survivors of preterm birth have a high incidence of neurodevelopmental impairment which is not explained by currently understood brain abnormalities. The aim of this study was to test the hypothesis that the neurodevelopmental abilities of 2-year-old children who were born preterm and who had no evidence of focal abnormality on conventional MR imaging were consistently linearly related to specific local changes in white matter microstructure. We studied 33 children, born at a median (range) gestational age of 28(+5) (24(+4)-32(+1)) weeks. The children were recruited as infants from the Neonatal Intensive Care Unit at Queen Charlottes and Hammersmith Hospital in the early neonatal period and imaged at a median corrected age of 25.5 (24-27) months. The children underwent diffusion tensor imaging to measure fractional anisotropy (FA) as a measure of tissue microstructure, and neurodevelopmental assessment using the Griffiths Mental Development Scales [giving an overall developmental quotient (DQ) and sub-quotients scores for motor, personal-social, hearing-language, eye-hand coordination and performance scales] at 2 years corrected age. Tract-based spatial statistics with linear regression analysis of voxel-wise cross-subject statistics were used to assess the relationship between FA and DQ/sub-quotient scores and results confirmed by reduced major axis regression of regions with significant correlations. We found that DQ was linearly related to FA values in parts of the corpus callosum; performance sub-scores to FA values in the corpus callosum and right cingulum; and eye-hand coordination sub-scores to FA values in the cingulum, fornix, anterior commissure, corpus callosum and right uncinate fasciculus. This study shows that specific neurodevelopmental impairments in infants born preterm are precisely related to microstructural abnormalities in particular regions of cerebral white matter which are consistent between individuals. FA may aid prognostication and provide a biomarker for therapeutic or mechanistic studies of preterm brain injury.

Automatic segmentation of brain MRIs of 2-year-olds into 83 regions of interest.

Three-dimensional atlases and databases of the brain at different ages facilitate the description of neuroanatomy and the monitoring of cerebral growth and development. Brain segmentation is challenging in young children due to structural differences compared to adults. We have developed a method, based on established algorithms, for automatic segmentation of young childrens brains into 83 regions of interest (ROIs), and applied this to an exemplar group of 33 2-year-old subjects who had been born prematurely. The algorithm uses prior information from 30 normal adult brain magnetic resonance (MR) images, which had been manually segmented to create 30 atlases, each labeling 83 anatomical structures. Each of these adult atlases was registered to each 2-year-old target MR image using non-rigid registration based on free-form deformations. Label propagation from each adult atlas yielded a segmentation of each 2-year-old brain into 83 ROIs. The final segmentation was obtained by combination of the 30 propagated adult atlases using decision fusion, improving accuracy over individual propagations. We validated this algorithm by comparing the automatic approach with three representative manually segmented volumetric regions (the subcortical caudate nucleus, the neocortical pre-central gyrus and the archicortical hippocampus) using similarity indices (SI), a measure of spatial overlap (intersection over average). SI results for automatic versus manual segmentations for these three structures were 0.90+/-0.01, 0.90+/-0.01 and 0.88+/-0.03 respectively. This registration approach allows the rapid construction of automatically labelled age-specific brain atlases for children at the age of 2 years.

Abnormal deep grey matter development following preterm birth detected using deformation-based morphometry.

Preterm birth is a leading risk factor for neurodevelopmental and cognitive impairment in childhood and adolescence. The most common known cerebral abnormality among preterm infants at term equivalent age is a diffuse white matter abnormality seen on magnetic resonance (MR) images. It occurs with a similar prevalence to subsequent impairment, but its effect on developing neural systems is unknown. MR images were obtained at term equivalent age from 62 infants born at 24-33 completed weeks gestation and 12 term born controls. Tissue damage was quantified using diffusion-weighted imaging, and deformation-based morphometry was used to make a non-subjective survey of the whole brain to identify significant cerebral morphological alterations associated with preterm birth and with diffuse white matter injury. Preterm infants at term equivalent age had reduced thalamic and lentiform volumes without evidence of acute injury in these regions (t = 5.81, P < 0.05), and these alterations were more marked with increasing prematurity (t = 7.13, P < 0.05 for infants born at less than 28 weeks) and in infants with diffuse white matter injury (t = 6.43, P < 0.05). The identification of deep grey matter growth failure in association with diffuse white matter injury suggests that white matter injury is not an isolated phenomenon, but rather, it is associated with the maldevelopment of remote structures. This could be mediated by a disturbance to corticothalamic connectivity during a critical period in cerebral development. Deformation-based morphometry is a powerful tool for modelling the developing brain in health and disease, and can be used to test putative aetiological factors for injury.

A dynamic 4D probabilistic atlas of the developing brain

Probabilistic atlases are widely used in the neuroscience community as a tool for providing a standard space for comparison of subjects and as tissue priors used to enhance the intensity-based classification of brain MRI. Most efforts so far have focused on static brain atlases either for adult or pediatric cohorts. In contrast to the adult brain the rapid growth of the neonatal brain requires an age-specific spatial probabilistic atlas to provide suitable anatomical and structural information. In this paper we describe a 4D probabilistic atlas that allows dynamic generation of prior tissue probability maps for any chosen stage of neonatal brain development between 29 and 44 gestational weeks. The atlas is created from the segmentations of 142 neonatal subjects at different ages using a kernel-based regression method and provides prior tissue probability maps for six structures - cortex, white matter, subcortical grey matter, brainstem, cerebellum and cerebro-spinal fluid. The atlas is publicly available at www.brain-development.org.

The Effect of Preterm Birth on Thalamic and Cortical Development

Preterm birth is a leading cause of cognitive impairment in childhood and is associated with cerebral gray and white matter abnormalities. Using multimodal image analysis, we tested the hypothesis that altered thalamic development is an important component of preterm brain injury and is associated with other macro- and microstructural alterations. T1- and T2-weighted magnetic resonance images and 15-direction diffusion tensor images were acquired from 71 preterm infants at term-equivalent age. Deformation-based morphometry, Tract-Based Spatial Statistics, and tissue segmentation were combined for a nonsubjective whole-brain survey of the effect of prematurity on regional tissue volume and microstructure. Increasing prematurity was related to volume reduction in the thalamus, hippocampus, orbitofrontal lobe, posterior cingulate cortex, and centrum semiovale. After controlling for prematurity, reduced thalamic volume predicted: lower cortical volume; decreased volume in frontal and temporal lobes, including hippocampus, and to a lesser extent, parietal and occipital lobes; and reduced fractional anisotropy in the corticospinal tracts and corpus callosum. In the thalamus, reduced volume was associated with increased diffusivity. This demonstrates a significant effect of prematurity on thalamic development that is related to abnormalities in allied brain structures. This suggests that preterm delivery disrupts specific aspects of cerebral development, such as the thalamocortical system.

Construction of a consistent high-definition spatio-temporal atlas of the developing brain using adaptive kernel regression

Medical imaging has shown that, during early development, the brain undergoes more changes in size, shape and appearance than at any other time in life. A better understanding of brain development requires a spatio-temporal atlas that characterizes the dynamic changes during this period. In this paper we present an approach for constructing a 4D atlas of the developing brain, between 28 and 44 weeks post-menstrual age at time of scan, using T1 and T2 weighted MR images from 204 premature neonates. The method used for the creation of the average 4D atlas utilizes non-rigid registration between all pairs of images to eliminate bias in the atlas toward any of the original images. In addition, kernel regression is used to produce age-dependent anatomical templates. A novelty in our approach is the use of a time-varying kernel width, to overcome the variations in the distribution of subjects at different ages. This leads to an atlas that retains a consistent level of detail at every time-point. Comparisons between the resulting atlas and atlases constructed using affine and non-rigid registration are presented. The resulting 4D atlas has greater anatomic definition than currently available 4D atlases created using various affine and non-rigid registration approaches, an important factor in improving registrations between the atlas and individual subjects. Also, the resulting 4D atlas can serve as a good representative of the population of interest as it reflects both global and local changes. The atlas is publicly available at www.brain-development.org.

An optimised tract-based spatial statistics protocol for neonates: applications to prematurity and chronic lung disease

Preterm birth is associated with altered white matter microstructure, defined by metrics derived from diffusion tensor imaging (DTI). Tract-based spatial statistics (TBSS) is a useful tool for investigating developing white matter using DTI, but standard TBSS protocols have limitations for neonatal studies. We describe an optimised TBSS protocol for neonatal DTI data, in which registration errors are reduced. As chronic lung disease (CLD) is an independent risk factor for abnormal white matter development, we investigate the effect of this condition on white matter anisotropy and diffusivity using the optimised protocol in a proof of principle experiment. DTI data were acquired from 93 preterm infants (48 male) with a median gestational age at birth of 28(+5) (23(+4)-35(+2))weeks at a median postmenstrual age at scan of 41(+4) (38(+1)-46(+6))weeks. Nineteen infants developed CLD, defined as requiring supplemental oxygen at 36weeks postmenstrual age. TBSS was modified to include an initial low degrees-of-freedom linear registration step and a second registration to a population-average FA map. The additional registration steps reduced global misalignment between neonatal fractional anisotropy (FA) maps. Infants with CLD had significantly increased radial diffusivity (RD) and significantly reduced FA within the centrum semiovale, corpus callosum and inferior longitudinal fasciculus (p<0.05) compared to their peers, controlling for degree of prematurity and age at scan. The optimised TBSS protocol improved reliability for neonatal DTI analysis. These data suggest that potentially modifiable respiratory morbidity is associated with widespread altered white matter microstructure in preterm infants at term-equivalent age.

A common neonatal image phenotype predicts adverse neurodevelopmental outcome in children born preterm

Diffuse white matter injury is common in preterm infants and is a candidate substrate for later cognitive impairment. This injury pattern is associated with morphological changes in deep grey nuclei, the localization of which is uncertain. We test the hypotheses that diffuse white matter injury is associated with discrete focal tissue loss, and that this image phenotype is associated with impairment at 2years. We acquired magnetic resonance images from 80 preterm infants at term equivalent (mean gestational age 29(+6)weeks) and 20 control infants (mean GA 39(+2)weeks). Diffuse white matter injury was defined by abnormal apparent diffusion coefficient values in one or more white matter region (frontal, central or posterior white matter at the level of the centrum semiovale), and morphological difference between groups was calculated from 3D images using deformation based morphometry. Neurodevelopmental assessments were obtained from preterm infants at a mean chronological age of 27.5months, and from controls at a mean age of 31.1months. We identified a common image phenotype in 66 of 80 preterm infants at term equivalent comprising: diffuse white matter injury; and tissue volume reduction in the dorsomedial nucleus of the thalamus, the globus pallidus, periventricular white matter, the corona radiata and within the central region of the centrum semiovale (t=4.42 p<0.001 false discovery rate corrected). The abnormal image phenotype is associated with reduced median developmental quotient (DQ) at 2years (DQ=92) compared with control infants (DQ=112), p<0.001. These findings indicate that specific neural systems are susceptible to maldevelopment after preterm birth, and suggest that neonatal image phenotype may serve as a useful biomarker for studying mechanisms of injury and the effect of putative therapeutic interventions.

Early Growth in Brain Volume Is Preserved in the Majority of Preterm Infants

Preterm infants have reduced cerebral tissue volumes in adolescence. This study addresses the question: Is reduced global brain growth in the neonatal period inevitable after premature birth, or is it associated with specific medical risk factors?