Examining the development of brain structure in utero with fetal MRI, acquired as part of the Developing Human Connectome Project

The human brain is an incredibly complex organ, and the study of it traverses many scales across space and time. The development of the brain is a protracted process that begins embryonically but continues into adulthood. Although neural circuits have the capacity to adapt and are modulated throughout life, the major structural foundations are laid in utero during the fetal period, through a series of rapid but precisely timed, dynamic processes. These include neuronal proliferation, migration, differentiation, axonal pathfinding, and myelination, to name a few. The fetal origins of disease hypothesis proposed that a variety of non-communicable diseases emerging in childhood and adulthood could be traced back to a series of risk factors effecting neurodevelopment in utero (Barker 1995). Since this publication, many studies have shown that the structural scaffolding of the brain is vulnerable to external environmental influences and the perinatal developmental window is a crucial determinant of neurological health later in life. However, there remain many fundamental gaps in our understanding of it. The study of human brain development is riddled with biophysical, ethical, and technical challenges. The Developing Human Connectome Project (dHCP) was designed to tackle these specific challenges and produce high quality open-access perinatal MRI data, to enable researchers to investigate normal and abnormal neurodevelopment (Edwards et al., 2022). This thesis will focus on investigating the diffusion-weighted and anatomical (T2) imaging data acquired in the fetal period, between the second to third trimester (22 – 37 gestational weeks). The limitations of fetal MR data are ill-defined due to a lack of literature and therefore this thesis aims to explore the data through a series of critical and strategic analysis approaches that are mindful of the biophysical challenges associated with fetal imaging. A variety of analysis approaches are optimised to quantify structural brain development in utero, exploring avenues to relate the changes in MR signal to possible neurobiological correlates. In doing so, the work in this thesis aims to improve mechanistic understanding about how the human brain develops in utero, providing the clinical and medical imaging community with a normative reference point. To this aim, this thesis investigates fetal neurodevelopment with advanced in utero MRI methods, with a particular emphasis on diffusion MRI. Initially, the first chapter outlines a descriptive, average trajectory of diffusion metrics in different white matter fiber bundles across the second to third trimester. This work identified unique polynomial trajectories in diffusion metrics that characterise white matter development (Wilson et al., 2021). Guided by previous literature on the sensitivity of DWI to cellular processes, I formulated a hypothesis about the biophysical correlates of diffusion signal components that might underpin this trend in transitioning microstructure. This hypothesis accounted for the high sensitivity of the diffusion signal to a multitude of simultaneously occurring processes, such as the dissipating radial glial scaffold, commencement of pre-myelination and arborization of dendritic trees. In the next chapter, the methods were adapted to address this hypothesis by introducing another dimension, and charting changes in diffusion properties along developing fiber pathways. With this approach it was possible to identify compartment-specific microstructural maturation, refining the spatial and temporal specificity (Wilson et al., 2023). The results reveal that the dynamic fluctuations in the components of the diffusion signal correlate with observations from previous histological work. Overall, this work allowed me to consolidate my interpretation of the changing diffusion signal from the first chapter. It also serves to improve understanding about how diffusion signal properties are affected by processes in transient compartments of the fetal brain. The third chapter of this thesis addresses the hypothesis that cortical gyrification is influenced by both underlying fiber connectivity and cytoarchitecture. Using the same fetal imaging dataset, I analyse the tissue microstructural change underlying the formation of cortical folds. I investigate correlations between macrostructural surface features (curvature, sulcal depth) and tissue microstructural measures (diffusion tensor metrics, and multi-shell multi-tissue decomposition) in the subplate and cortical plate across gestational age, exploring this relationship both at the population level and within subjects. This study provides empirical evidence to support the hypotheses that microstructural properties in the subplate and cortical plate are altered with the development of sulci. The final chapter explores the data without anatomical priors, using a data-driven method to extract components that represent coordinated structural maturation. This analysis aims to examine if brain regions with coherent patterns of growth over the fetal period converge on neonatal functional networks. I extract spatially independent features from the anatomical imaging data and quantify the spatial overlap with pre-defined neonatal resting state networks. I hypothesised that coherent spatial patterns of anatomical development over the fetal period would map onto the functional networks observed in the neonatal period. Overall, this thesis provides new insight about the developmental contrast over the second to third trimester of human development, and the biophysical correlates affecting T2 and diffusion MR signal. The results highlight the utility of fetal MRI to research critical mechanisms of structural brain maturation in utero, including white matter development and cortical gyrification, bridging scales from neurobiological processes to whole brain macrostructure. their gendered constructions relating to women

Improving foetal and neonatal echo-planar imaging with image-based shimming

Tese de mestrado integrado em Engenharia Biomédica e Biofísica, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2015O Developing Human Connectome Project pretende realizar um progresso científico único através da criação do primeiro connectome 4D no início da vida do bebé. De forma a criar um mapa dinâmico da conectividade do cérebro do bebé, é fundamental obter imagens funcionais e com ponderação em difusão. A imagem eco-planar (EPI) é a principal sequência de ressonância magnética aplicada na aquisição dessa informação. Esta sequência permite uma aquisição rápida e repetida de imagens cerebrais permitindo mapear as flutuações da atividade cerebral (imagiologia funcional) bem como ter uma boa resolução nas imagens de difusão (movimento de moléculas de água no volume cerebral). No entanto, esta técnica está associada a artefactos de suscetibilidade. Estes artefactos surgem quando existem interfaces entre duas amostras com suscetibilidades magnéticas diferentes como sejam o tecido biológico e o ar. De forma a minimizar esses artefactos é necessário reduzir as heterogeneidades do campo magnético principal B0 através de shimming. O presente trabalho focou-se em shimming ativo, no qual o campo magnético é mapeado com base num modelo composto por funções harmónicas esféricas e são calculadas as correntes a aplicar às bobinas de shimming. Essas bobinas geram um campo magnético que compensa as heterogeneidades presentes anteriormente. Convencionalmente, as tentativas para superar este problema envolvem a utilização do método disponibilizado no sistema de ressonância magnética, nas quais o campo é mapeado com base em projecções (ex: FASTMAP). Este método é de execução rápida mas apresenta duas desvantagens principais: em primeiro lugar, o utilizador tem um controlo reduzido sobre o processo; em segundo, as regiões nas quais o campo é mapeado não são definidas com base na anatomia de interesse. No contexto deste trabalho, o controlo sobre o processo é importante no sentido de ser possível aplicar exatamente a mesma metodologia a um grupo elevado de sujeitos. Por seu lado, o mapeamento com base na anatomia permite obter uma optimização mais precisa. Com o surgimento de novas tecnologias passou a ser possível fazer um mapeamento mais detalhado do campo magnético com técnicas baseadas em imagem ao invés de projecções. Estas técnicas envolvem a definição de um volume relacionado com a anatomia, e que é incluído na totalidade na optimização do campo. O principal objetivo deste trabalho foi desenvolver uma ferramenta de shimming baseado em imagem a fim de otimizar o campo magnético no contexto de imagens de EPI do cérebro neonatal e fetal. O cérebro do bebé sofre alterações na sua dimensão e forma durante o seu desenvolvimento desde a idade fetal até neonatal. Em cada uma dessas fases o bebé encontra-se cercado por um ambiente diferente que requere uma abordagem específica ao mesmo. Neste sentido, o trabalho desenvolvido foi dividido em três partes principais: descrição da estrutura necessária para a correta aplicação do shimming, shimming neonatal e shimming fetal. Em primeiro lugar, as limitações do shimming baseado em imagem foram estudadas e o algoritmo básico para aplicar o método foi testado. Nesta parte do trabalho foi demonstrado que os campos gerados pelas bobinas de shim presentes no equipamento de ressonância magnética são consistentes com as funções harmónicas esféricas que compõem o modelo aplicado. O efeito do movimento da cama do equipamento sobre a eficiência do shimming foi também estudada. Foi possível corrigir a informação do sistema de coordenadas que descrevem o mapa de campo B0 de forma a incluir o movimento da cama necessário para a obtenção das imagens em sujeitos fetais. A segunda parte do trabalho focou-se no desenvolvimento do shimming para o caso neonatal. Foi desenvolvida uma ferramenta para definição de uma região de interesse, unwrapping da fase e cálculo das correntes de shim. Esta foi desenvolvida em ambiente MATLAB. Nos recém-nascidos o shimming deve ser aplicado numa região de interesse restrita ao cérebro devido à presença da interface ar/tecido no escalpe do bebé. Assim, a definição da região de interesse consistiu principalmente na aplicação de um limiar a fim de binarizar a imagem de magnitude, ajustada pelo utilizador. Em simultâneo foi implementada uma técnica de exclusão dos olhos com base na anatomia dos diferentes planos. No seu conjunto o método apresentou-se flexível de forma a ser ajustado ao sujeito em estudo. Quando aplicado com a mesma metodologia (limiar e exclusão de olhos) o volume incluído foi semelhante entre bebés. O método de shimming foi avaliado com base em três medidas de dispersão do mapa de campo residual: largura a meia altura, desvio padrão dos pixéis no interior da região de interesse e o intervalo de frequências no interior do qual 95 % dos pixéis se encontravam. A utilização de diferentes medidas permitiu a avaliação do m´etodo em relação a diferentes aspetos. Este método foi aplicado a 52 participantes recém-nascidos com idade gestacional média de 39.8 ± 1.7 semanas. O cálculo das correntes de shim permitiu gerar um campo magnético que melhorou a homogeneidade do campo B0 no volume adquirido, sendo consistente com o previsto. Uma imagem média do campo residual foi calculada mostrando que existem duas regiões (occipital e pequenas regiões laterais) nas quais o campo magnético B0 apresenta ainda heterogeneidades. Por fim, os resultados indicam que este método melhorou o campo perto da periferia do cérebro quando comparado com o método convencional disponibilizado no equipamento. O shimming neonatal (shimming ótimo ou OIBS) foi utilizado como alicerce para a implementação de um método ajustado às características das aquisições fetais. Existem duas características principais que devem ser tidas em conta. Em primeiro lugar, os fetos encontram-se envoltos em líquido amniótico e tecido materno pelo que o ambiente no qual estão inseridos permite que a região de interesse seja definida de forma menos restrita. Em segundo lugar, o facto de a cabeça do feto ser pequena pode levar à existência de valores de corrente das bobinas de shim elevados. Essas correntes, principalmente associadas às bobinas de segunda ordem geram campos de magnitude elevada na região do tecido adiposo, o que altera a sua frequência de ressonância. Desta forma, as técnicas de supressão de gordura específicas em frequência são menos efetivas e a imagem de EPI apresenta artefactos. Assim, a ferramenta para shimming fetal incluiu a definição de uma região de interesse cilíndrica e um método de shimming baseado em imagem com limites lineares (shimming limitado ou CIBS) impostos com base na frequência de ressonância do tecido adiposo. O CIBS consistiu na aplicação de limites superiores e inferiores ([-300 100] Hz) para a frequência dos pixéis pertencentes à gordura após a aplicação do shimming. Adicionalmente, o impulso de radiofrequência utilizado para a supressão de gordura foi estudado a fim o otimizar para a sua utilização no contexto do shimming fetal. Para o estudo dos parâmetros do impulso de radiofrequência, os rins de dois voluntários adultos saudáveis foram utilizados como simulação do ambiente fetal, devido as semelhanças entre a localização e interface entre tecidos. Os métodos OIBS e CIBS foram aplicados em 6 grávidas saudáveis com idades gestacional média de 28±6 semanas. Os mapas de campo residuais mostraram que as técnicas eram semelhantes em termos de homogeneidade no interior da região de interesse definida como cérebro, mas a segunda (CIBS) apresentou melhores resultados na supressão de gordura. Como estudo do impulso de radiofrequência foi demonstrado que o desvio do impulso em cerca de 100 Hz no sentido da frequência de ressonância da água melhoraria a supressão de gordura sem detrimento do sinal da água. A utilização do novo método CIBS em simultâneo com um impulso de radiofrequência otimizado mostrou ser a melhor solução para homogeneizar o campo e suprimir a gordura. Em conclusão, as ferramentas apresentadas permitiram melhorar a qualidade das imagens de EPI da cabeça do feto e do recém-nascido no contexto do Developing Human Connectome Project. O shimming neonatal mostrou ser um método consistente que pode facilmente ser utilizado por parte da equipa clínica. A nível fetal foi apresentado um método que demonstra a capacidade de superar as limitações demonstradas pelas técnicas convencionais.The Developing Human Connectome Project (dHCP) aims to make major scientific progress by creating the first 4-dimensional connectome of early life. Echo planar imaging (EPI) is the main acquisition technique applied in functional and diffusion imaging, which are central to map the human brain. This technique allows fast acquisition of spatial information enabling volumetric coverage of the whole brain, but it is associated with susceptibility artefacts. In order to minimize those artefacts it is necessary to reduce main magnetic field B0 in homogeneities through shimming. Conventionally, the attempts to overcome this problem use the manufacturer’s default method. Unfortunately, with those techniques the user has little control over the process, and the regions within which the field is corrected are not anatomically based. The main objective of this project was to develop an image-based shimming tool to optimize the magnetic field in the context of EPI images adjusted to the neonatal and foetal brains. The babies’ brain suffers changes in dimension and shape during its development from foetal to neonatal age. In each one of those stages the baby is surrounded by a different environment which requires a distinct shimming approach. As a result, the work was divided into three main parts: framework description, neonatal shimming and foetal shimming. First, the limitations of image-based shimming were investigated, and the framework to apply the method was described. It was demonstrated that fields generated by shim coils were consistent with the spherical harmonic model applied. In addition, the coordinate information of the B0 field map was corrected in order to include the table displacement needed for foetal imaging. Second, a tool was developed for neonatal shimming. The tool included region-of-interest (ROI) definition, phase unwrapping and shim calculation. The ROI definition implemented was flexible in order to adjust to each subject under study. When applying this approach while keeping the same threshold/eye exclusion methodology the volume included was similar between babies. The shim calculation allowed to generate shim values that improved homogeneity of the magnetic field within the volume imaged. This method slightly improved the field near the brain’s margins when compared with the manufacturer’s default techniques. Finally, for foetal shimming the groundwork of the neonatal tool was adjusted to this cohort characteristics. The tool for foetal shimming included additional cylindrical ROI definition and constrained image-based shimming. The constrained shimming allowed to account for the mother’s adipose tissue which in the presence of high shim values can lead to imperfect fat suppression. Along with the implementation of shimming tools, the radio frequency pulse used for fat suppression was studied. The new constrained image-based shimming showed similar results in terms of field homogeneity within the fetus’ brain when compared with the optimal image based shimming, with improvement of fat suppression that is enhanced when simultaneously used with the optimized fat suppression radiofrequency pulse

Collaborative patch-based super-resolution for diffusion-weighted images

In this paper, a new single image acquisition super-resolution method is proposed to increase image resolution of diffusion weighted (DW) images. Based on a nonlocal patch-based strategy, the proposed method uses a non-diffusion image (b0) to constrain the reconstruction of DW images. An extensive validation is presented with a gold standard built on averaging 10 high-resolution DW acquis itions. A comparison with classical interpo- lation methods such as trilinear and B-spline demonstrates the competitive results of our proposed approach in termsofimprovementsonimagereconstruction,fractiona lanisotropy(FA)estimation,generalizedFAandangular reconstruction for tensor and high angular resolut ion diffusion imaging (HARDI) models. Besides, fi rst results of reconstructed ultra high resolution DW images are presented at 0.6 × 0.6 × 0.6 mm 3 and0.4×0.4×0.4mm 3 using our gold standard based on the average of 10 acquisitions, and on a single acquisition. Finally, fi ber tracking results show the potential of the proposed super-resolution approach to accurately analyze white matter brain architecture.We thank the reviewers for their useful comments that helped improve the paper. We also want to thank the Pr Louis Collins for proofreading this paper and his fruitful comments. Finally, we want to thank Martine Bordessoules for her help during image acquisition of DWI used to build the phantom. This work has been supported by the French grant "HR-DTI" ANR-10-LABX-57 funded by the TRAIL from the French Agence Nationale de la Recherche within the context of the Investments for the Future program. This work has been also partially supported by the French National Agency for Research (Project MultImAD; ANR-09-MNPS-015-01) and by the Spanish grant TIN2011-26727 from the Ministerio de Ciencia e Innovacion. This work benefited from the use of FSL (http://fsl.fmrib.ox.ac.uk/fsl/fslwiki/), FiberNavigator (code.google.com/p/fibernavigator/), MRtrix software (http://www. brain.org.au/software/mrtrix/) and ITKsnap (www.itk.org).Coupé, P.; Manjón Herrera, JV.; Chamberland, M.; Descoteaux, M.; Hiba, B. (2013). Collaborative patch-based super-resolution for diffusion-weighted images. NeuroImage. 83:245-261. https://doi.org/10.1016/j.neuroimage.2013.06.030S2452618

A novel diffusion tensor imaging-based computer-aided diagnostic system for early diagnosis of autism.

Autism spectrum disorders (ASDs) denote a significant growing public health concern. Currently, one in 68 children has been diagnosed with ASDs in the United States, and most children are diagnosed after the age of four, despite the fact that ASDs can be identified as early as age two. The ultimate goal of this thesis is to develop a computer-aided diagnosis (CAD) system for the accurate and early diagnosis of ASDs using diffusion tensor imaging (DTI). This CAD system consists of three main steps. First, the brain tissues are segmented based on three image descriptors: a visual appearance model that has the ability to model a large dimensional feature space, a shape model that is adapted during the segmentation process using first- and second-order visual appearance features, and a spatially invariant second-order homogeneity descriptor. Secondly, discriminatory features are extracted from the segmented brains. Cortex shape variability is assessed using shape construction methods, and white matter integrity is further examined through connectivity analysis. Finally, the diagnostic capabilities of these extracted features are investigated. The accuracy of the presented CAD system has been tested on 25 infants with a high risk of developing ASDs. The preliminary diagnostic results are promising in identifying autistic from control patients

Relationship between large-scale structural and functional brain connectivity in the human lifespan

The relationship between the anatomical structure of the brain and its functional organization is not straightforward and has not been elucidated yet, despite the growing interest this topic has received in the last decade. In particular, a new area of research has been defined in these years, called \u2019connectomics\u2019: this is the study of the different kinds of \u2019connections\u2019 existing among micro- and macro-areas of the brain, from structural connectivity \u2014 described by white matter fibre tracts physically linking cortical areas \u2014 to functional connectivity \u2014 defined as temporal correlation between electrical activity of different brain regions \u2014 to effective connectivity\u2014defining causal relationships between functional activity of different brain areas. Cortical areas of the brain physically linked by tracts of white matter fibres are known to exhibit a more coherent functional synchronization than areas which are not anatomically linked, but the absence of physical links between two areas does not imply a similar absence of functional correspondence. Development and ageing, but also structural modifications brought on by malformations or pathology, can modify the relation between structure and function. The aim of my PhD work has been to further investigate the existing relationship between structural and functional connectivity in the human brain at different ages of the human lifespan, in particular in healthy adults and both healthy and pathological neonates and children. These two \u2019categories\u2019 of subjects are very different in terms of the analysis techniques which can be applied for their study, due to the different characteristics of the data obtainable from them: in particular, while healthy adult data can be studied with the most advanced state-of-the-art methods, paediatric and neonatal subjects pose hard constraints to the acquisition methods applicable, and thus to the quality of the data which can be analysed. During this PhD I have studied this relation in healthy adult subjects by comparing structural connectivity from DWI data with functional connectivity from stereo-EEG recordings of epileptic patients implanted with intra-cerebral electrodes. I have then focused on the paediatric age, and in particular on the challenges posed by the paediatric clinical environment to the analysis of structural connectivity. In collaboration with the Neuroradiology Unit of the Giannina Gaslini Hospital in Genova, I have adapted and tested advanced DWI analysis methods for neonatal and paediatric data, which is commonly studied with less effective methods. We applied the same methods to the study of the effects of a specific brain malformation on the structural connectivity in 5 paediatric patients. While diffusion weighted imaging (DWI) is recognised as the best method to compute structural connectivity in the human brain, the most common methods for estimating functional connectivity data \u2014 functional MRI (fMRI) and electroencephalography (EEG) \u2014 suffer from different limitations: fMRI has good spatial resolution but low temporal resolution, while EEG has a better temporal resolution but the localisation of each signal\u2019s originating area is difficult and not always precise. Stereo-EEG (SEEG) combines strong spatial and temporal resolution with a high signal-to-noise ratio and allows to identify the source of each signal with precision, but is not used for studies on healthy subjects because of its invasiveness. Functional connectivity in children can be computed with either fMRI, EEG or SEEG, as in adult subjects. On the other hand, the study of structural connectivity in the paediatric age is met with obstacles posed by the specificity of this data, especially for the application of the advanced DWI analysis techniques commonly used in the adult age. Moreover, the clinical environment introduces even more constraints on the quality of the available data, both in children and adults, further limiting the possibility of applying advanced analysis methods for the investigation of connectivity in the paediatric age. Our results on adult subjects showed a positive correlation between structural and functional connectivity at different granularity levels, from global networks to community structures to single nodes, suggesting a correspondence between structural and functional organization which is maintained at different aggregation levels of brain units. In neonatal and paediatric subjects, we successfully adapted and applied the same advanced DWI analysis method used for the investigation in adults, obtaining white matter reconstructions more precise and anatomically plausible than with methods commonly used in paediatric clinical environments, and we were able to study the effects of a specific type of brain malformation on structural connectivity, explaining the different physical and functional manifestation of this malformation with respect to similar pathologies. This work further elucidates the relationship between structural and functional connectivity in the adult subject, and poses the basis for a corresponding work in the neonatal and paediatric subject in the clinical environment, allowing to study structural connectivity in the healthy and pathological child with clinical data

Complex diffusion-weighted image estimation via matrix recovery under general noise models

We propose a patch-based singular value shrinkage method for diffusion magnetic resonance image estimation targeted at low signal to noise ratio and accelerated acquisitions. It operates on the complex data resulting from a sensitivity encoding reconstruction, where asymptotically optimal signal recovery guarantees can be attained by modeling the noise propagation in the reconstruction and subsequently simulating or calculating the limit singular value spectrum. Simple strategies are presented to deal with phase inconsistencies and optimize patch construction. The pertinence of our contributions is quantitatively validated on synthetic data, an in vivo adult example, and challenging neonatal and fetal cohorts. Our methodology is compared with related approaches, which generally operate on magnitude-only data and use data-based noise level estimation and singular value truncation. Visual examples are provided to illustrate effectiveness in generating denoised and debiased diffusion estimates with well preserved spatial and diffusion detail.Comment: 26 pages, 9 figure

Abnormal Microstructural Development of the Cerebral Cortex in Neonates With Congenital Heart Disease Is Associated With Impaired Cerebral Oxygen Delivery.

Background Abnormal macrostructural development of the cerebral cortex has been associated with hypoxia in infants with congenital heart disease ( CHD ). Animal studies have suggested that hypoxia results in cortical dysmaturation at the cellular level. New magnetic resonance imaging techniques offer the potential to investigate the relationship between cerebral oxygen delivery and cortical microstructural development in newborn infants with CHD . Methods and Results We measured cortical macrostructural and microstructural properties in 48 newborn infants with serious or critical CHD and 48 age-matched healthy controls. Cortical volume and gyrification index were calculated from high-resolution structural magnetic resonance imaging. Neurite density and orientation dispersion indices were modeled using high-angular-resolution diffusion magnetic resonance imaging. Cerebral oxygen delivery was estimated in infants with CHD using phase contrast magnetic resonance imaging and preductal pulse oximetry. We used gray matter-based spatial statistics to examine voxel-wise group differences in cortical microstructure. Microstructural development of the cortex was abnormal in 48 infants with CHD , with regions of increased fractional anisotropy and reduced orientation dispersion index compared with 48 healthy controls, correcting for gestational age at birth and scan (family-wise error corrected for multiple comparisons at P<0.05). Regions of reduced cortical orientation dispersion index in infants with CHD were related to impaired cerebral oxygen delivery ( R2=0.637; n=39). Cortical orientation dispersion index was associated with the gyrification index ( R2=0.589; P<0.001; n=48). Conclusions This study suggests that the primary component of cerebral cortex dysmaturation in CHD is impaired dendritic arborization, which may underlie abnormal macrostructural findings reported in this population, and that the degree of impairment is related to reduced cerebral oxygen delivery