Diagnosing diffuse liver disease first involves measurement of blood enzymes followed by biopsy. However, blood markers lack spatial and diagnostic specificity and biopsy is highly risky and variable. Although structural changes have been evaluated using diffusion weighted imaging (DWI), the technique is minimally quantitative. Quantitative MR diffusion approaches, such as intra-voxel incoherent motion (IVIM) and diffusion tensor imaging (DTI) have been proposed to better characterize diseased liver. However, the so called pseudo-hepatic artefact due to cardiac motion, drastically affects DWI results. The overall goals of this thesis were thus to evaluate the pseudo-hepatic anisotropy artefact on the quality of diffusion tensor (DT) and IVIM metrics, and to identify potential solutions. Intra- and intersession DTI repeatability was evaluated in healthy human livers when varying the number of diffusion encoding gradients (NGD) and number of signal averages (NSA). Although no further advantage was observed with increasing NGD beyond 6 directions, increased NSA improved intra- and inter-session repeatability. The pseudo-hepatic artefact resulted in increased fractional anisotropy (FA) and tensor eigenvalues (λ1, λ2, λ3), most prominent in the left liver lobe during systole of the cardiac cycle. Without taking advantage of tensor directional information, increasing the acquired NGD slightly improved IVIM fit quality thus helping to minimize the pseudo-hepatic artefact. Combining IVIM and DTI resulted in FA values closer to the hypothesized value of 0.0, which, based on liver microstructure is most logical. Although both IVIM-DTI and DTI-IVIM exhibited similar fit R2 values, the latter failed more often, especially near major blood vessels. Thus, IVIM-DTI was concluded to be more robust and thus the better approach. / Thesis / Doctor of Philosophy (PhD)

No description available.

Diffusion of water molecules in biological tissues depends on several microstructural properties. Therefore, diffusion Magnetic Resonance Imaging (dMRI) is a useful tool to infer and study microstructural brain changes in the context of human development, ageing and neuropathology. In this thesis, the state-of-the-art of advanced dMRI techniques is explored and strategies to overcome or reduce its pitfalls are developed and validated. Firstly, it is shown that PCA denoising and Gibbs artefact suppression algorithms provide an optimal compromise between increased precision of diffusion measures and the loss of tissue's diffusion non-Gaussian information. Secondly, the spatial information provided by the diffusion kurtosis imaging (DKI) technique is explored and used to resolve crossing fibres and generalize diffusion measures to cases not limited to well-aligned white matter fibres. Thirdly, as an alternative to diffusion microstructural modelling techniques such as the neurite orientation dispersion and density imaging (NODDI), it is shown that spherical deconvolution techniques can be used to characterize fibre crossing and dispersion simultaneously. Fourthly, free water volume fraction estimates provided by the free water diffusion tensor imaging (fwDTI) are shown to be useful to detect and remove voxels corrupted by cerebrospinal fluid (CSF) partial volume effects. Finally, dMRI techniques are applied to the diffusion data from the large collaborative Cambridge Centre for Ageing and Neuroscience (CamCAN) study. From these data, the inference provided by diffusion anisotropy measures on maturation and degeneration processes is shown to be biased by age-related changes of fibre organization. Inconsistencies of previous NODDI ageing studies are also revealed to be associated with the different age ranges covered. The CamCAN data is also processed using a novel non-Gaussian diffusion characterization technique which is invariant to different fibre configurations. Results show that this technique can provide indices specific to axonal water fraction which can be linked to age-related fibre density changes.

Bipolar disorder is a heritable psychiatric disorder, and several of the genes associated with bipolar disorder and related psychotic disorders are involved in the development and maintenance of white matter in the brain. Patients with bipolar disorder have an increased incidence of white matter hyper-intensities, and quantitative brain imaging studies collectively indicate subtle decreases in white matter density and integrity in bipolar patients. This suggests that genetic vulnerability to psychosis may manifest itself as reduced white matter integrity, and that white matter integrity is an endophenotype of bipolar disorder. This thesis comprises a series of studies designed to test the role of white matter in genetic risk to bipolar disorder by analysis of diffusion tensor imaging (DTI) data in the Bipolar Family Study. Various established analysis methods for DTI, including whole-brain voxel-based statistics, tract-based spatial statistics (TBSS) and probabilistic neighbourhood tractography, were applied with fractional anisotropy (FA) as the outcome measure. Widespread but subtle white matter integrity reductions were found in unaffected relatives of patients with bipolar disorder, whilst more localised reductions were associated with cyclothymic temperament. Next, the relation of white matter to four of the most prominent psychosis candidate genes, NRG1, ErbB4, DISC1 and ZNF804A, was investigated. A core haplotype in NRG1, and three of the four key single nucleotide polymorphisms (SNPs) within it, showed an association with FA in the anterior thalamic radiations and the uncinate fasciculi. For the three SNPs considered in ErbB4, results were inconclusive, but this was consistent with the background literature. Most notable however, was a clear association of a non-synonymous DISC1 SNP, Ser704Cys, with FA extending over most of the white matter in the TBSS and voxel-based analyses. Finally, FA was not associated with a genome-wide supported risk SNP in ZNF804A, a finding which could not be attributed to a lack of statistical power, and which contradicts a strong, but previously untested hypothesis. Whilst the above results need corroboration from independent studies, other studies are needed to address the cellular and molecular basis of these findings. Overall, this work provides strong support for the role of white matter integrity in genetic vulnerability to bipolar disorder and the wider psychosis spectrum and encourages its future use as an endophenotype.

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

published_or_final_version / Orthopaedics and Traumatology / Master / Master of Philosophy

La conception classique de l'organisation des réseaux cérébraux participant au langage décrit deux zones corticales, l'une frontale (Broca), l'autre temporale intervenant respectivement dans la production et la compréhension du langage, unies par un faisceau de substance blanche: le faisceau longitudinal supérieur. L'imagerie par résonance magnétique d'activation (IRMf) a rendu possible la visualisation de zones d'activation corticales, et l'imagerie en tenseur de diffusion avec la tractographie celle des faisceaux de substance blanche. Ces données nouvelles permettent de repenser l'organisation corticale et sous-corticale du langage. L'ensemble des travaux en imagerie d'activation étaye l'hypothèse d'une dissociation dorso-ventrale du traitement du langage. Les zones de traitement de l'information phonétique étant dorsales, et les centres impliqués dans le traitement sémantique plus ventraux. Imagerie d'activation, imagerie du tenseur de diffusion, stimulations corticales et sous-corticales ont permis d'aboutir à un modèle de réseau du langage impliquant une voie dorsale, essentiellement phonologique et une voie ventrale, sémantique présentant deux composantes. La première est directe, par le faisceau fronto-occipital inférieur connectant les aires temporales postérieures à la région orbito-frontale. La seconde est une voie indirecte qui connecte successivement la région occipito-temporale au pôle temporal par l'intermédiaire du faisceau longitudinal inférieur puis le pôle temporal aux aires basifrontales par le faisceau unciné. Cette dernière voie est compensée après résection ou lors des stimulations per-opératoires, suggérant la possibilité de réseaux de suppléance parallèles et bilatéraux. Dans cette vision d'une voie ventrale sémantique bilatérale, notre travail a pour objet par l'utilisation de l'imagerie fonctionnelle d'activation, d'une part, et de l'imagerie en tenseur de diffusion d'autre part, 1) de vérifier le nombre de faisceaux qui sous-tendent cette voie et en particulier de la part attribuable au faisceau longitudinal moyen; 2) de caractériser les réorganisations de la connectivité fonctionnelle du réseau du langage après une chirurgie de tumeur gliale hémisphérique gauche. Dans la première partie de ce travail, après avoir rappelé la filiation phylogénétique de l'homme et du primate non-humain, en insistant sur les dissemblances qui existent dans leur anatomie corticale et sous-corticale, nous exposons comment ces données ont permis d'aboutir à la découverte du faisceau longitudinal moyen chez l'homme. Nous confirmons la visibilité en imagerie du tenseur de diffusion de ce faisceau et nous précisons ses rapports avec les différents faisceaux de substance blanche constitutifs des voies ventrales et dorsales du langage. Enfin nous discutons ces données tractographiques à la lumière de la dissection et discutons du rôle présumé du faisceau dans le langage. Dans un deuxième temps, nous présentons les concepts de connectivité anatomique, fonctionnelle et effective. Puis nous appliquons un outil d'analyse de la connectivité fonctionnelle à des données périopératoires en tâches de fluence afin de réaliser une cartographie de la plasticité périopératoire de la composante sémantique du langage. Les résultats de cette deuxième étude suggèrent un recrutement de l'hémisphère ipsilatéral à la lésion au décours de la chirurgie. Enfin, nous évoquons la possibilité d'induire une désynchronisation (i.e. une altération de la connectivité) du réseau du mode par défaut par une stimulation peropératoire de la partie postérieure du faisceau cingulaire, induisant une sensation de dépersonnalisation, ces résultats suggérant qu'une des fonctions du noeud le plus postérieur du réseau soit de maintenir un état de conscience du monde extérieur. / According to classical conception of the anatomo-functional organization of language, there are two main cortical areas: a frontal area (Broca) and a temporal one (Wernicke) respectively involved in language production and comprehension. Functional magnetic resonance Imaging (fMRI) reveals cortical areas of activation and diffusion tensor imaging-based tractography (DTI) makes feasible the visualization of white-matter tracts in the human brain. On the basis of these techniques, a new conception of language cortical and sub-cortical organization arose, supporting the hypothesis that language processing network is dissociated in an dorso-ventral way. Dorsal areas of the brain being devoted to phonologic processing and its ventral areas to semantic processing of speech. Different techniques such as fMRI, DTI, intraoperative cortical and subcortical mapping made possible to describe two pathways involved in the language network: a dorsal stream and a ventral stream respectively involved in phonologic and semantic processing. As the dorsal route is composed of a unique pathway, the superior longitudinal fasciculus, the ventral stream appears to be composed of two different pathways. First a direct pathway, the inferior occipitofrontal fasciculus, connecting the posterior temporal areas to the orbitofrontal region. The second one, an indirect pathway, the inferior longitudinal fasciculus links the posterior occipitotemporal to the temporal pole, then relayed by the uncinate fasciculus connecting the temporal pole to the basifrontal areas. According to these observations the aim of our work is In the present work, we aim (1) to confirm that the MdLF is constantly found in control subjects and that it can be delineated from the other fiber tracts that constitute language pathways, (2) to characterize the reorganization of language network's functional connectivity follmowing surgical removal of left hemisphere low grade gliomas. In this study, we confirmed that the MdLF is constantly found in healthy volunteers and we clearly delineate the MdLF from the other fascicles that constitute language pathways, especially the ventral pathway. Considering language plasticity, our findings suggest that in the postoperative period, brain plasticity occurs with an ipsilateral recrutment and increased fonctional connectivity in the left hemisphere. Finally, we report a collaborative work observing that intraoperative electrostimulations of the white matter underlying the left posterior cingulate, while performing a naming task, systematically induced an unresponsive state for few seconds in relationship with a dream-like state. This result provides direct evidence that connectivity underlying the posterior node of the default mode network permits maintained consciousness of the external world.

Mild traumatic brain injuries (MTBI) are the leading type of head injuries with appreciable risque of sequelae leading to functional and psychological deficits. Although mild traumatic brain injuries are frequently underdiagnosed by conventional imaging modalities, rapidly evolving techniques such as diffusion tensor imaging (DTI) reveal subtle changes in white matter integrity as a result of head trauma and play an important role in refining diagnosis, therapeutic interventions and management of MTBI. In this dissertation we use diffusion tensor imaging to detect the microstructural changes induced by axonal injuries and to monitor their evolution during the recovery process. DTI data were previously acquired from 11 subjects, football players of age 19-23 years (median age 20 years). Three players had suffered a mild traumatic brain injury during the season and underwent scanning within 24 hours after the injury with follow-ups after one and two weeks. A set of diffusion indices, such as fractional anisotropy, axial, radial and mean diffusivity were derived from the diffusion tensor. Changes in diffusion indices in concussed subjects were analyzed based on two different approaches: whole brain analysis, using tract-based spatial statistics (TBSS) and region of interest analysis (ROI). In both approaches we use a voxelwise analysis to examine group differences in diffusion indices between five controls and three concussed subjects for all DTI scans. Additional statistical analysis was performed between control groups consisting of five and three non-injured players. Both analyses demonstrated that the MTBI group reveals increase in fractional anisotropy and decreases in transversal and mean diffusivity in cortical and subcortical areas within 24 hours after the injury. / No changes were detected in TBSS analysis for the follow-up data sets. Furthermore, our ROI approach revealed multiples regions with significantly different voxels, non-uniformly distributed throughout the brain, for all diffusion indices in all three scans. Three of the diffusion indices fractional anisotropy, mean and transversal diffusivity showed higher vulnerability to head trauma in subcortical and cortical areas than in regions in the lower brain. Recovery of white matter pathways occured at different locations in the brain at one and two weeks after head trauma. Strong recovery was observed in mean and transversal diffusivity in subcortical areas that correspond to the corticospinal tract. No recovery was found for fractional anisotropy and axial diffusivity in the same region. Also, decreases in fractional anisotropy and increases in transversal and axial diffusivity were observed in the spleninum of the corpus callosum. As voxelwise analysis performed on DTI data revealed white matter regions, which exhibit changes in diffusion parameters in the concussed group for all three scans, we conclude that diffusion tensor imaging is a powerful technique for early detection of axonal injuries and may serve as an important tool for monitoring microstructural changes during the recovery process. / by Angelica Hotiu. / Thesis (Ph.D.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Esclerose Múltipla (MS) é uma doença neurodegenerativa que tem ganhado grande atenção nas últimas décadas, sendo o diagnóstico por imagens de ressonância magnética (MRI) um grande aliado para a avaliação da doença.Porém, um dos principais desafios é garantir uma maior sensibilidade e especificidade para detecção de diferentes lesões no sistema nervoso central (CNS) e assim classificar as diferentes variantes da MS, auxiliando na tomada de decisão para o tratamento farmacológico. Nas últimas décadas, a técnica de imagens ponderadas por difusão (DWI), em especial a técnica de imagem por tensor de difusão (DTI), têm sido evidenciada com grande potencial para o estudo da MS, apresentando uma melhora significativa para a detecção de lesões sutis, ainda em estágios iniciais da MS. Desta forma, as técnicas de processamento de imagens estão em constante aprimoramento para que sejam adaptados às novas modalidades de aquisição de imagens. Neste estudo focamos o desenvolvimento de uma técnica de processamento digital de imagens multimodais a fim de proporcionar uma solução viável para a rotina de diagnóstico por imagem em MS. Um conjunto de 25 pacientes de uma variante de MS foi selecionado aleatoriamente do banco de imagens do HCFMRP. Três modalidades de imagens foram coletadas para a avaliação da segmentação automatica (T1, T2-FLAIR e DTI), assim como a segmentação manual do especialista para cada paciente. Três métodos de segmentação multimodal automática de lesões foram analisados (Bayesiano, Frequentista e Agrupamento) afim de analisar a sensibilidade e especificidade de detecção de lesões na substância branca aparentemente normal (NAWM). Os resultados sugerem que o método de segmentação Bayesiano apresenta maior robustes e precisão na definição tanto de lesões visivelmente contrastantes em T1 e T2-FLAIR (i.e. lesões hipo e hiperintensas) assim como lesões da NAWM evidentes nos mapas quantitativos de DTI (FA e ADC). O erro associado à técninca automática de segmentação ficou em torno de 1.51 +- 0.51 % do volume total de lesões marcadas pelo especialista. Concluímos que o uso de ferramentas multimodais de segmentação de imagens MRI alcançou patamares razoáveis de detecção de lesões de MS, tornando assim uma ferramenta computacional hábil para uso no diagnóstico clínico. / Multiple sclerosis (MS) is a neurodegenerative disease that has gained great attention in the last decades, which magnetic resonance imaging (MRI) have shown as an important tool for the disease evaluation. However, one of the main challenges is guaranteeing greater lesion detection sensitivity and specificity in the whole central nervous system (CNS) and thus classify the different variants of MS, which aids in decision making for pharmacological treatment. In the last decades, the diffusion-weighted imaging (DWI) technique, especially the diffusion tensor imaging approach (DTI), has been evidenced with great potential for the study of MS, presenting a significant improvement for the detection of lesions even in early stages of MS. Hence, the techniques of image processing are constantly improving in order to be adapted on a multimodal image evaluation. In this study, the development of a multimodal digital image processing technique to provide a viable solution to the MS imaging routine was focused. A set of 25 patients from a MS variant was randomly selected from the HCFMRP imaging database. Three MR imaging modalities were collected for the evaluation of our automatic segmentation (T1, T2-FLAIR and DTI), as well as manual segmentation of the specialist for each patient. Three methods of automatic multimodal segmentation of MS lesions were analyzed (Bayesian, Frequentist and Clustering) in order to analyze the sensitivity and specificity of lesion detection in the apparently normal white matter (NAWM). The results suggest that the Bayesian segmentation method presented greater robustness and precision in the definition of visibly contrasting lesions in T1 and T2-FLAIR (i.e. hypo and hyperintense lesions) as well as NAWM lesions that are evident in quantitative DTI (FA and ADC). The error associated with the automatic segmentation technique was around 1.51 +- 0.51 % of the total lesion volume being evaluated by the a specialist. We conclude that the use of multimodal MRI images can be used in an automatic segmentation tools, reaching reasonable levels of MS lesion detection, thus making it a useful tool for clinical diagnosis.

Magnetic resonance imaging (MRI) has transformed the world of non-invasive imaging for diagnostic purposes. Modern techniques such as diffusion weighted imaging (DWI), diffusion tensor imaging (DTI), and diffusion spectrum imaging (DSI) have been used to reconstruct fiber pathways of the brain - providing a graphical picture of the so-called "connectome." However, there exists controversy in the literature as to the accuracy of the diffusion tractography reconstruction. Although various attempts at histological validation been attempted, there is still no 3D histological pathway validation of the fiber bundle trajectories seen in diffusion MRI. Such a validation is necessary in order to show the viability of current DSI tractography techniques in the ultimate goal for clinical diagnostic application. This project developed methods to provide this 3D histological validation using the rhesus monkey motor pathway as a model system. By injecting biotinylated dextran amine (BDA) tract tracer into the hand area of primary motor cortex, brain section images were reconstructed to create 3D fiber pathways labeled at the axonal level. Using serial coronal brain sections, the BDA label was digitized with a high resolution digital camera to create image montages of the fiber pathway with individual sections spaced at 1200 micron intervals through the brain. An MRI analysis system, OSIRX, was then used to reconstruct these sections into a 3D volume. This is an important technical step toward merging the BDA fiber tract histology with diffusion MRI tractography of the same brain, enabling identification of the valid and inaccurate aspects of diffusion fiber reconstruction. This will ultimately facilitate the use of diffusion MRI to quantify tractography, non-invasively and in vivo, in the human brain.