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

Longitudinal analysis of the preterm cortex using multi-modal spectral matching

Extremely preterm birth (less than 32 weeks completed gestation) overlaps with a period of rapid brain growth and development. Investigating longitudinal brain changes over the preterm period in these infants may allow the development of biomarkers for predicting neurological outcome. In this paper we investigate longitudinal changes in cortical thickness,cortical fractional anisotropy and cortical mean diffusivity in a groupwise space obtained using a novel multi-modal spectral matching technique. The novelty of this method consists in its ability to register surfaces with very little shape complexity,like in the case of the early developmental stages of preterm infants,by also taking into account their underlying biology. A multi-modal method also allows us to investigate interdependencies between the parameters. Such tools have great potential in investigating in depth the regions affected by preterm birth and how they relate to each other

Using compartment models of diffusion MRI to investigate the preterm brain

Preterm birth is the leading cause of neonatal mortality, with survivors experiencing motor, cognitive and other deficits at increased rates. In preterm infancy, the developing brain undergoes folding, myelination, and rapid cellular growth. Diffusion-Weighted Magnetic Resonance Imaging (DW MRI) is an imaging modality that allows noninvasive inference of cellular microstructure in living tissue, and its parameters reflect changes in brain tissue composition. In this thesis, we employ compartment models of DW MRI to investigate the microstructure in preterm-born subjects at different ages. Within infants, we have used the NODDI model to investigate longitudinal changes in neurite density and orientation dispersion within the white matter, cerebral cortex and thalamus, explaining known trends in diffusion tensor parameters with greater specificity. We then used a quantitative T2 sequence to develop and investigate a novel, multi-modal parameter known as the ‘g-ratio’. We have also investigated changing microstructural geometry within the cortex. Immediately after preterm birth, the highly-ordered underlying cellular structure makes diffusion in the cortex almost entirely radial. This undergoes a transition to a disordered and isotropic state over the first weeks of life, which we have used the DIAMOND model to quantify. This radiality decreases at a rate that depends on the cortical lobe. In a cohort of young adults born extremely preterm, we have quantified differences in brain microstructure compared to term-born controls. In preterm subjects, the brain structures are smaller than for controls, leading to increased partial volume in some regions of interest. We introduce a method to infer diffusion parameters in partial volume, even for regions which are smaller than the diffusion resolution. Overall, this thesis utilises and evaluates a variety of compartment models of DW MRI. By developing and applying principled and robust methodology, we present new insights into microstructure within the preterm-born brain

Longitudinal analysis of extreme prematurity: a neuroimage investigation of early brain development

Brain development is a complex process, and disruptions from its normal course may affect the later neurological outcome of an individual. Preterm infants are at higher risk of disability, since a substantial part of brain development happens outside the mother’s womb, making it vulnerable to a range of insults. Understanding the early brain development during the preterm period is of critical importance and magnetic resonance imaging (MRI) allows us to investigate this. Methodologically, this is a challenging task, as classical approaches of studying longitudinal development over this period do not cope with the large changes taking place. This thesis focuses on the development of tools to study the changes in cortical folding, shape of different brain structures and microstructural changes over the preterm period from longitudinal data of extremely preterm-born infants. It describes a tissue segmentation pipeline, optimised on a postmortem fetal dataset, and then focuses on finding longitudinal correspondences between the preterm and termequivalent brain regions and structures in extremely preterm-born infants using MRI. Three novel registration techniques are proposed for longitudinal registration of this challenging data. These are based on matching the spectral components associated with either the cortical surfaces, diffusion tensor images, or both. These allow us to quantify longitudinal changes in different brain regions and structures. We investigated changes in cortical folding of different lobes, microstructural changes and tracts in the white matter, cortical thickness and changes in cortical fractional anisotropy and mean diffusivity. We used cortical surface registration to look at shape differences between controls and extremely preterm-born young adults to gain an insight into the long-term impact of prematurity. This research may contribute to the development of early biomarkers for predicting the neurological outcome of preterm infants and illuminate our understanding of brain development during this crucial period

Recent advances in diffusion neuroimaging: applications in the developing preterm brain

Measures obtained from diffusion-weighted imaging provide objective indices of white matter development and injury in the developing preterm brain. To date, diffusion tensor imaging (DTI) has been used widely, highlighting differences in fractional anisotropy (FA) and mean diffusivity (MD) between preterm infants at term and healthy term controls; altered white matter development associated with a number of perinatal risk factors; and correlations between FA values in the white matter in the neonatal period and subsequent neurodevelopmental outcome. Recent developments, including neurite orientation dispersion and density imaging (NODDI) and fixel-based analysis (FBA), enable white matter microstructure to be assessed in detail. Constrained spherical deconvolution (CSD) enables multiple fibre populations in an imaging voxel to be resolved and allows delineation of fibres that traverse regions of fibre-crossings, such as the arcuate fasciculus and cerebellar-cortical pathways. This review summarises DTI findings in the preterm brain and discusses initial findings in this population using CSD, NODDI, and FBA

Studying neuroanatomy using MRI

The study of neuroanatomy using imaging enables key insights into how our brains function, are shaped by genes and environment, and change with development, aging, and disease. Developments in MRI acquisition, image processing, and data modelling have been key to these advances. However, MRI provides an indirect measurement of the biological signals we aim to investigate. Thus, artifacts and key questions of correct interpretation can confound the readouts provided by anatomical MRI. In this review we provide an overview of the methods for measuring macro- and mesoscopic structure and inferring microstructural properties; we also describe key artefacts and confounds that can lead to incorrect conclusions. Ultimately, we believe that, though methods need to improve and caution is required in its interpretation, structural MRI continues to have great promise in furthering our understanding of how the brain works

Cortical thickness of primary visual cortex correlates with motion deficits in periventricular leukomalacia

Abstract Impairments of visual motion perception and, in particular, of flow motion have been consistently observed in premature and very low birth weight subjects during infancy. Flow motion information is analyzed at various cortical levels along the dorsal pathways, with information mainly provided by primary and early visual cortex (V1, V2 and V3). We investigated the cortical stage of the visual processing that underlies these motion impairments, measuring Grey Matter Volume and Cortical Thickness in 13 children with Periventricular Leukomalacia (PVL). The cortical thickness, but not the grey matter volume of area V1, correlates negatively with motion coherence sensitivity, indicating that the thinner the cortex, the better the performance among the patients. However, we did not find any such association with either the thickness or volume of area MT, MST and areas of the IPS, suggesting damage at the level of primary visual cortex or along the optic radiation

Using neuro-cognitive modelling to link attention deficits to structural and functional brain changes

‘Visual attention’ is an emerging property of interconnected neural networks, in which the interconnections are biased to promote targets over distracting stimuli. It has been shown that efficiency of the attention system is lost after many kinds of brain damage, with each presumably effecting different aspects of basic visual attention functions. Yet, our understanding of these processes is limited by the methodological shortcomings of classical neuropsychological assessment. The overarching goal of the current thesis was to overcome these constrains and thereby extend the link between attention deficits and underlying brain changes. The here used approach incorporates parametric measurement of visual attention derived from the computational Theory of Visual Attention (TVA, Bundesen, 1990) and modern magnetic resonance imaging techniques. Project 1 of the current thesis applied a combined TVA–neuroimaging analysis in a neurodevelopmental model (preterm birth) to relate attention deficits with changes in functional connectivity networks. We found that pre- versus full-term born adults show a selective reduction of visual short-term memory capacity. The remarkable changes we observed in attention-related large-scale brain networks of the occipital and posterior parietal cortices were most pronounced in those preterm born individuals with the most preserved attention functions. This finding was interpreted as evidence for a compensatory reorganization of functional connectivity in order to ameliorate the advert consequences of preterm birth on visual short-term memory. Project 2 of this thesis applied a combined TVA-neuroimaging analysis in a neurodegenerative model (posterior cortical atrophy) to relate attention deficits with structural changes in grey and white matter morphometry. Compared to healthy control participants, patients with posterior cortical atrophy suffered from a selective disturbance of visual processing speed. The individual rate of processing speed slowing was a valid predictor for the severity of simultanagnosia, the core symptom in this clinical condition. We further found wide-spread atrophy in occipital as well as parietal and to a smaller degree in temporal brain areas. White matter degeneration in the superior parietal lobe, rather than atrophy of any grey matter cluster, was significantly associated with patients’ impaired processing speed. Based on these results we propose that disruption of white matter pathways especially within the superior parietal lobe leads to reduced processing speed which then results in the overt clinical symptoms of simultanagnosia. Altogether, projects of the current thesis expanded the link between specific attention deficits and underlying brain damage by using neuro-cognitive modelling. We demonstrated that parametric measurements of attention facilitate, in the role of intermediate cognitive constructs, the mapping between etiological factors and behavioral outcomes. Identifying predictable behavior-brain relationships in attention disorders may offer new perspectives for diagnosis and treatment. The clinical application of an integrated TVA-neuroimaging analysis could additionally compliment insights from healthy participants toward understanding the principles of normal visual attention as well as identifying their neuronal basis