Représentations continue et discrète de la connectivité structurelle des fibres en U du sillon central

International audienceU-shape fibers are superficial white matter fibers connecting adjacent gyri. In this paper, we present a method to characterize the connectivity of U-shape fibers coursing around the central sulcus. Pre-and post-central gyral crests are semi-automatically drawn and used to build a connectivity space that is identical between subjects. This group space provides a dense representation of the short-range connectivity between the two gyri, as well as a structured representation after clustering

Study of the structural connectivity of short association fibres of the white matter of the human brain in diffusion MRI

Les fibres d’association courtes (fibres en U) de la substance blanche connectent des territoires corticaux situés dans des gyri adjacents. L’estimation in vivo de l’extension spatiale de ces fibres requiert des données IRM pondérées en diffusion (IRMd) à résolution spatiale et angulaire élevée afin de limiter l’effet du volume partiel à l’interface cortex/substance blanche et de capturer la complexité des configurations de fibres de la matière blanche superficielle. De telles données nécessitent des méthodes de prétraitement adaptées. De plus, l’étude quantitative de la connectivité de ces fibres nécessite la mise en place de stratégies avancées de tractographie et de filtrage des tractogrammes obtenus. Dans ce cadre, nous avons développé Diffuse (https://github.com/MecaLab/Brainvisa-Diffuse), une boîte à outil dédiée au traitement des données IRMd qui interface les méthodes de l’état de l’art de prétraitement, modélisation locale et d’estimation de la trajectoires des fibres par tractographie. En nous appuyant sur Diffuse, nous avons quantifié l’impact de six chaînes de correction des artéfacts classiquement utilisées en traitement des données IRMd sur les étapes ultérieures de modélisation locale et de tractographie (Brun et al. 2019). La deuxième contribution de ce thèse propose de décrire la connectivité des fibres en U d’un sillon en définissant un nouvel espace de représentation continu (Pron et al. 2018). Cet espace a été utilisé pour caractériser la connectivité anatomique des fibres d’association courtes du sillon central de 100 sujets droitiers issus de la base de données IRM de haute qualité du Human Connectome Project.Short association fibres (U-shaped fibres) of the white matter connect cortical territories located in adjacent gyri. In vivo estimation of the spatial extent of these fibres requires diffusion-weighted MRI data (dMRI) with high spatial and angular resolution to limit the effect of partial volume at the cortex/white substance interface and to capture the complexity of the fibre patterns. Such data require appropriate pre-processing methods. In addition, the quantitative study of the connectivity of these fibres requires the implementation of advanced tractography and filtering strategies for the tractograms obtained. In this context, we have developed Diffuse (https://github.com/MecaLab/Brainvisa-Diffuse), a toolbox dedicated to dMRI data processing that interfaces state-of-the-art methods for pre-treatment, local modelling and estimation of fibre trajectories by tractography. Using Diffuse, we quantified the impact of six artefact correction chains typically used in dMRI data processing on subsequent local modelling and tractography steps (Brun et al. 2019). The second contribution to this thesis proposes to describe the connectivity of the U-shaped fibres of a sulcus by defining a new continuous representation space (Pron et al. 2018). This space was used to characterize the anatomical connectivity of the short association fibers of the central sulcus of 100 right-handed subjects from the Human Connectome Project's high-quality MRI database

U-shape short-range extrinsic connectivity organisation around the human central sulcus

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Représentations continue et discrète de la connectivité structurelle des fibres en U du sillon central

International audienceU-shape fibers are superficial white matter fibers connecting adjacent gyri. In this paper, we present a method to characterize the connectivity of U-shape fibers coursing around the central sulcus. Pre-and post-central gyral crests are semi-automatically drawn and used to build a connectivity space that is identical between subjects. This group space provides a dense representation of the short-range connectivity between the two gyri, as well as a structured representation after clustering

Diffusion MRI: Assessment of the Impact of Acquisition and Preprocessing Methods Using the BrainVISA-Diffuse Toolbox

International audienceDiffusion MR images are prone to severe geometric distortions induced by head movement, eddy-current and inhomogeneity of magnetic susceptibility. Various correction methods have been proposed that depend on the choice of the acquisition settings and potentially provide highly different data quality. However, the impact of this choice has not been evaluated in terms of the ratio between scan time and preprocessed data quality. This study aims at investigating the impact of six well-known preprocessing methods, each associated to specific acquisition settings, on the outcome of diffusion analyses. For this purpose, we developed a comprehensive toolbox called Diffuse which automatically guides the user to the best preprocessing pipeline according to the input data. Using MR images of 20 subjects from the HCP dataset, we compared the six pre-processing pipelines regarding the following criteria: the ability to recover brain’s true geometry, the tensor model estimation and derived indices in the white matter, and finally the spatial dispersion of six well known connectivity pathways. As expected the pipeline associated to the longer acquisition fully repeated with reversed phase-encoding (RPE) yielded the higher data quality and was used as a reference to evaluate the other pipelines. In this way, we highlighted several significant aspects of other pre-processing pipelines. Our results first established that eddy-current correction improves the tensor-fitting performance with a localized impact especially in the corpus callosum. Concerning susceptibility distortions, we showed that the use of a field map is not sufficient and involves additional smoothing, yielding to an artificial decrease of tensor-fitting error. Of most importance, our findings demonstrate that, for an equivalent scan time, the acquisition of a b0 volume with RPE ensures a better brain’s geometry reconstruction and local improvement of tensor quality, without any smoothing of the image. This was found to be the best scan time/data quality compromise. To conclude, this study highlights and attempts to quantify the strong dependence of diffusion metrics on acquisition settings and preprocessing methods

Retrospective motion estimation for fetal brain MRI

International audienceMagnetic Resonance Imaging (MRI) is performed on fetus, to study cerebral development. However, the image is affected by child's and mother's motion. Ultra-fast MRI sequences allow to reduce artefact in slices, but motion still occurs between them. We propose a method based on orthogonal slices intersection to correct motion as well as a new solution for outliers removal

Estimation de mouvement rétrospective pour l'IRM cérébrale foetale

International audienceL'imagerie par résonance magnétique (IRM) foetale permet d'étudier le développement cérébral. Cependant, les mouvements de l'enfant et de la mère pendant l'acquisition entraînent des artefacts sur les images. Des séquences IRM utltra-rapides, permettent de réduire les artefacts mais du mouvement persiste entre les coupes. Nous proposons une méthode permettant de corriger le mouvement entre les coupes, basée sur l'intersection entre les coupes orthogonales, ainsi qu'une nouvelle méthode pour la détection des coupes mal recalées

Estimation de mouvement rétrospective pour l'IRM cérébrale foetale

International audienceL'imagerie par résonance magnétique (IRM) foetale permet d'étudier le développement cérébral. Cependant, les mouvements de l'enfant et de la mère pendant l'acquisition entraînent des artefacts sur les images. Des séquences IRM utltra-rapides, permettent de réduire les artefacts mais du mouvement persiste entre les coupes. Nous proposons une méthode permettant de corriger le mouvement entre les coupes, basée sur l'intersection entre les coupes orthogonales, ainsi qu'une nouvelle méthode pour la détection des coupes mal recalées

Retrospective motion estimation for fetal brain MRI

International audienceMagnetic Resonance Imaging (MRI) is performed on fetus, to study cerebral development. However, the image is affected by child's and mother's motion. Ultra-fast MRI sequences allow to reduce artefact in slices, but motion still occurs between them. We propose a method based on orthogonal slices intersection to correct motion as well as a new solution for outliers removal