Computerized Analysis of Magnetic Resonance Images to Study Cerebral Anatomy in Developing Neonates

The study of cerebral anatomy in developing neonates is of great importance for the understanding of brain development during the early period of life. This dissertation therefore focuses on three challenges in the modelling of cerebral anatomy in neonates during brain development. The methods that have been developed all use Magnetic Resonance Images (MRI) as source data. To facilitate study of vascular development in the neonatal period, a set of image analysis algorithms are developed to automatically extract and model cerebral vessel trees. The whole process consists of cerebral vessel tracking from automatically placed seed points, vessel tree generation, and vasculature registration and matching. These algorithms have been tested on clinical Time-of- Flight (TOF) MR angiographic datasets. To facilitate study of the neonatal cortex a complete cerebral cortex segmentation and reconstruction pipeline has been developed. Segmentation of the neonatal cortex is not effectively done by existing algorithms designed for the adult brain because the contrast between grey and white matter is reversed. This causes pixels containing tissue mixtures to be incorrectly labelled by conventional methods. The neonatal cortical segmentation method that has been developed is based on a novel expectation-maximization (EM) method with explicit correction for mislabelled partial volume voxels. Based on the resulting cortical segmentation, an implicit surface evolution technique is adopted for the reconstruction of the cortex in neonates. The performance of the method is investigated by performing a detailed landmark study. To facilitate study of cortical development, a cortical surface registration algorithm for aligning the cortical surface is developed. The method first inflates extracted cortical surfaces and then performs a non-rigid surface registration using free-form deformations (FFDs) to remove residual alignment. Validation experiments using data labelled by an expert observer demonstrate that the method can capture local changes and follow the growth of specific sulcus

Automatic segmentation of MR brain images with a convolutional neural network

Automatic segmentation in MR brain images is important for quantitative analysis in large-scale studies with images acquired at all ages. This paper presents a method for the automatic segmentation of MR brain images into a number of tissue classes using a convolutional neural network. To ensure that the method obtains accurate segmentation details as well as spatial consistency, the network uses multiple patch sizes and multiple convolution kernel sizes to acquire multi-scale information about each voxel. The method is not dependent on explicit features, but learns to recognise the information that is important for the classification based on training data. The method requires a single anatomical MR image only. The segmentation method is applied to five different data sets: coronal T2-weighted images of preterm infants acquired at 30 weeks postmenstrual age (PMA) and 40 weeks PMA, axial T2- weighted images of preterm infants acquired at 40 weeks PMA, axial T1-weighted images of ageing adults acquired at an average age of 70 years, and T1-weighted images of young adults acquired at an average age of 23 years. The method obtained the following average Dice coefficients over all segmented tissue classes for each data set, respectively: 0.87, 0.82, 0.84, 0.86 and 0.91. The results demonstrate that the method obtains accurate segmentations in all five sets, and hence demonstrates its robustness to differences in age and acquisition protocol

Three dimensional optical imaging of blood volume and oxygenation in the neonatal brain

Optical methods provide a means of monitoring cerebral oxygenation in newborn infants at risk of brain injury. A 32-channel optical imaging system has been developed with the aim of reconstructing three-dimensional images of regional blood volume and oxygenation. Full image data sets were acquired from 14 out of 24 infants studied; successful images have been reconstructed in 8 of these infants. Regional variations in cerebral blood volume and tissue oxygen saturation are present in healthy preterm infants. In an infant with a large unilateral intraventricular haemorrhage, a corresponding region of low oxygen saturation was detected. These results suggest that optical tomography may provide an appropriate technique for investigating regional cerebral haemodynamics and oxygenation at the cotside. (c) 2006 Elsevier Inc. All rights reserved

Early changes in brain structure correlate with language outcomes in children with neonatal encephalopathy.

Global patterns of brain injury correlate with motor, cognitive, and language outcomes in survivors of neonatal encephalopathy (NE). However, it is still unclear whether local changes in brain structure predict specific deficits. We therefore examined whether differences in brain structure at 6 months of age are associated with neurodevelopmental outcomes in this population. We enrolled 32 children with NE, performed structural brain MR imaging at 6 months, and assessed neurodevelopmental outcomes at 30 months. All subjects underwent T1-weighted imaging at 3 T using a 3D IR-SPGR sequence. Images were normalized in intensity and nonlinearly registered to a template constructed specifically for this population, creating a deformation field map. We then used deformation based morphometry (DBM) to correlate variation in the local volume of gray and white matter with composite scores on the Bayley Scales of Infant and Toddler Development (Bayley-III) at 30 months. Our general linear model included gestational age, sex, birth weight, and treatment with hypothermia as covariates. Regional brain volume was significantly associated with language scores, particularly in perisylvian cortical regions including the left supramarginal gyrus, posterior superior and middle temporal gyri, and right insula, as well as inferior frontoparietal subcortical white matter. We did not find significant correlations between regional brain volume and motor or cognitive scale scores. We conclude that, in children with a history of NE, local changes in the volume of perisylvian gray and white matter at 6 months are correlated with language outcome at 30 months. Quantitative measures of brain volume on early MRI may help identify infants at risk for poor language outcomes

Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI.

Preterm birth is a major public health concern, with the severity and occurrence of adverse outcome increasing with earlier delivery. Being born preterm disrupts a time of rapid brain development: in addition to volumetric growth, the cortex folds, myelination is occurring and there are changes on the cellular level. These neurological events have been imaged non-invasively using diffusion-weighted (DW) MRI. In this population, there has been a focus on examining diffusion in the white matter, but the grey matter is also critically important for neurological health. We acquired multi-shell high-resolution diffusion data on 12 infants born at ≤28weeks of gestational age at two time-points: once when stable after birth, and again at term-equivalent age. We used the Neurite Orientation Dispersion and Density Imaging model (NODDI) (Zhang et al., 2012) to analyse the changes in the cerebral cortex and the thalamus, both grey matter regions. We showed region-dependent changes in NODDI parameters over the preterm period, highlighting underlying changes specific to the microstructure. This work is the first time that NODDI parameters have been evaluated in both the cortical and the thalamic grey matter as a function of age in preterm infants, offering a unique insight into neuro-development in this at-risk population

Born too early and too small: higher order cognitive function and brain at risk at ages 8–16

Prematurity presents a risk for higher order cognitive functions. Some of these deficits manifest later in development, when these functions are expected to mature. However, the causes and consequences of prematurity are still unclear. We conducted a longitudinal study to first identify clinical predictors of ultrasound brain abnormalities in 196 children born very preterm (VP; gestational age 32 weeks) and with very low birth weight (VLBW; birth weight 1500 g). At ages 8–16, the subset of VP-VLBW children without neurological findings (124) were invited for a neuropsychological assessment and an MRI scan (41 accepted). Of these, 29 met a rigorous criterion for MRI quality and an age, and gender-matched control group (n = 14) was included in this study. The key findings in the VP-VLBW neonates were: (a) 37% of the VP-VLBW neonates had ultrasound brain abnormalities; (b) gestational age and birth weight collectively with hospital course (i.e., days in hospital, neonatal intensive care, mechanical ventilation and with oxygen therapy, surgeries, and retinopathy of prematurity) predicted ultrasound brain abnormalities. At ages 8–16, VP-VLBW children showed: a) lower intelligent quotient (IQ) and executive function; b) decreased gray and white matter (WM) integrity; (c) IQ correlated negatively with cortical thickness in higher order processing cortical areas. In conclusion, our data indicate that facets of executive function and IQ are the most affected in VP-VLBW children likely due to altered higher order cortical areas and underlying WMThis study was supported by the Spanish Government Institute Carlos III (FIS Pl11/02860), Spanish Ministry of Health to MM-L, and the University of Castilla-La Mancha mobility Grant VA1381500149

Sequelae of premature birth in young adults

Background and Purpose Qualitative studies about the abnormalities appreciated on routine magnetic resonance imaging (MRI) sequences in prematurely born adults are lacking. This article aimed at filling this knowledge gap by (1) qualitatively describing routine imaging findings in prematurely born adults, (2) evaluating measures for routine image interpretation and (3) investigating the impact of perinatal variables related to premature birth. Methods In this study two board-certified radiologists assessed T1-weighted and FLAIR-weighted images of 100 prematurely born adults born very preterm (VP <32 weeks) and/or at very low birth weight (VLBW <1500 g) and 106 controls born at full term (FT) (mean age 26.8 ± 0.7 years). The number of white matter lesions (WML) was counted according to localization. Lateral ventricle volume (LVV) was evaluated subjectively and by measurements of Evans’ index (EI) and frontal-occipital-horn ratio (FOHR). Freesurfer-based volumetry served as reference standard. Miscellaneous incidental findings were noted as free text. Results The LVV was increased in 24.7% of VP/VLBW individuals and significantly larger than in FT controls. This was best identified by measurement of FOHR (AUC = 0.928). Ventricular enlargement was predicted by low gestational age (odds ratio: 0.71, 95% CI 0.51–0.98) and presence of neonatal intracranial hemorrhage (odds ratio: 0.26, 95% CI 0.07–0.92). The numbers of deep and periventricular WML were increased while subcortical WMLs were not. Conclusion Enlargement of the LVV and deep and periventricular WMLs are typical sequelae of premature birth that can be appreciated on routine brain MRI. To increase sensitivity of abnormal LVV detection, measurement of FOHR seems feasible in clinical practice

MR diffusion changes in the perimeter of the lateral ventricles demonstrate periventricular injury in post-hemorrhagic hydrocephalus of prematurity

OBJECTIVES: Injury to the preterm lateral ventricular perimeter (LVP), which contains the neural stem cells responsible for brain development, may contribute to the neurological sequelae of intraventricular hemorrhage (IVH) and post-hemorrhagic hydrocephalus of prematurity (PHH). This study utilizes diffusion MRI (dMRI) to characterize the microstructural effects of IVH/PHH on the LVP and segmented frontal-occipital horn perimeters (FOHP). STUDY DESIGN: Prospective study of 56 full-term infants, 72 very preterm infants without brain injury (VPT), 17 VPT infants with high-grade IVH without hydrocephalus (HG-IVH), and 13 VPT infants with PHH who underwent dMRI at term equivalent. LVP and FOHP dMRI measures and ventricular size-dMRI correlations were assessed. RESULTS: In the LVP, PHH had consistently lower FA and higher MD and RD than FT and VPT (p\u3c.050). However, while PHH FA was lower, and PHH RD was higher than their respective HG-IVH measures (p\u3c.050), the MD and AD values did not differ. In the FOHP, PHH infants had lower FA and higher RD than FT and VPT (p\u3c.010), and a lower FA than the HG-IVH group (p\u3c.001). While the magnitude of AD in both the LVP and FOHP were consistently less in the PHH group on pairwise comparisons to the other groups, the differences were not significant (p\u3e.050). Ventricular size correlated negatively with FA, and positively with MD and RD (p\u3c.001) in both the LVP and FOHP. In the PHH group, FA was lower in the FOHP than in the LVP, which was contrary to the observed findings in the healthy infants (p\u3c.001). Nevertheless, there were no regional differences in AD, MD, and RD in the PHH group. CONCLUSION: HG-IVH and PHH results in aberrant LVP/FOHP microstructure, with prominent abnormalities among the PHH group, most notably in the FOHP. Larger ventricular size was associated with greater magnitude of abnormality. LVP/FOHP dMRI measures may provide valuable biomarkers for future studies directed at improving the management and neurological outcomes of IVH/PHH