1ère Etude (Fatigue et ATP dans la SEP): La fatigue dans la SEP est un symptôme fréquent et retentit sur la qualité de vie. L’évaluation clinique est réalisée par le score FSS (fatigue scale score). Cependant, il est nécessaire d’avoir des biomarqueurs fiables et objectifs, notamment si une perspective thérapeutique est envisagée. L’ATP (adénosine tri-phosphate) est un marqueur du métabolisme énergétique et peut être mesuré in vivo à l’étage cérébral par spectroscopie du phosphore (31P-MRS). L’objectif de cette étude est d’évaluer s’il existe une corrélation du β-ATP (spécifique de l’ATP) avec la fatigue évaluée par le FSS. 30 patients présentant une SEP progressives ont été explorés en IRM 3T avec une antenne spécifique du phosphore par une séquence 31P-MRS multivoxel centrée sur les centres semi-ovales. 2 régions ont été segmentées: (a) les hémisphères fronto-pariétaux et (b) substance blanche normale repérée à partir d’une séquence FLAIR. Les ratios des métabolites énergétiques évalués étaient le PCr% et le β-ATP%. Les corrélations statistiques entre les métabolites énergétiques avec le FSS ont été calculées par les tests de Spearman. Les résultats ont montré que le β-ATP% était corrélé avec le FSS (r=0.46; p=0,01) dans les hémisphères fronto-pariétaux.2ème Etude (Cortex moteur et faisceau cortico-spinal évalués par IRM et excitabilité corticale dans la SEP): Les lésions corticales, notamment de l’aire motrice, sont source de handicap. Les séquences de double (DIR) et phase sensitive inversion récupération (PSIR) permettent d’évaluer les lésions corticales et la séquence en imagerie en tenseur de diffusion (DTI) permet quant à elle d’évaluer le faisceau cortico-spinal (CS). L’excitabilité corticale permet aussi d’évaluer ces régions anatomiques par SMT (stimulation magnétique transcrânienne). L’objectif de cette étude a été de rechercher une corrélation entre les données IRM et d’excitabilité corticale. 25 SEP progressives ont eu une SMT pour évaluer l’excitabilité corticale du cortex moteur pour obtenir les paramètres de FICmoy, FICmax, IICmoy, IICmax (facilitation et inhibition intra-corticale). Ces patients ont aussi eu une IRM avec les séquences: 3D DIR (0,7x0,7x0,8mm), axiales PSIR (0,6x0,6x3mm) pour compter le nombre de lésion du cortex moteur du côté ipsilatéral, et une séquence DTI 12 directions pour extraire les paramètres de fraction d’anisotropie (FA), coefficient apparent de diffusion (ADC), diffusivité radiale et axiale du CS ipsilatéral. Les corrélations entre les données IRM avec les données d’excitabilité sont calculées par tests de Spearman. Les résultats ne montrent pas de corrélation entre le nombre de lésions corticales avec les données d’excitabilité corticale. Il existe en revanche une corrélation entre FICmoy et FICmax avec la diffusivité radiale (r=0.56 ; p=0.004 et r=-0.59 ; p=0.002, respectivement) et avec l’ADC (r=-0.44; p=0.03 et r=-0.45 ; p=0.02, respectivement) suggérant un épuisement de compensation de la FIC par les lésions de démyélinisation. / 1st Study (Fatigue and ATP in MS): Fatigue in MS is a common symptom and impact on quality of life. Clinical examination relies on FSS (fatigue scale score). However, it is important to have reliable and objective biomarkers. ATP (adenosin tri-phosphate) is an energetic metabolite which can be measured by brain phosphorous magnetic spectroscopy (31P-MRS) in vivo. We aimed to assess correlation between β-ATP (specific of ATP) with FSS. 30 progressive MS were assessed by 3T MRI with a phosphorous coil and a multivoxel 31P-MRS sequence. 2 areas were segmented in: (a) fronto-parietal hemispheres and (b) normal appearing white matter (NAWM) defined by FLAIR sequence. The energetic metabolites ratios assessed were: PCr% and β-ATP%. Correlations between energetic metabolites with FSS were computed by Spearman tests. Results showed β-ATP% correlated with FSS (r=0.46; p=0,01) in fronto-parietal hemispheres.2nd Study (Motor cortex and cortico-spinal tract assessed by MRI et cortical excitability in MS): Cortical lesions, especially from motor cortex, result in disability. Double and phase sensitive inversion recovery sequences can assess cortical lesions while diffusion tractography imaging (DTI) can assess cortico-spinal tract (CST). Cortical excitability can also assess these anatomical areas by transcranial magnetic stimulation (TMS). We aimed to assess correlation between MRI data with cortical excitability. 25 progressive MS had cortical excitability from motor cortex assessed by TMS: ICFmean, ICFmax, ICImean, ICImax (intra-cortical facilitation and inhibition). These patients also had a MRI with the following sequences: 3D DIR (0,7x0,7x0,8mm), axial PSIR (0,6x0,6x3mm) to count ipsitaleral motor cortical lesions, and a 12-directions DTI sequence to obtain fractional anisotropy (FA), apparent diffusion coefficient (ADC), radial and axial diffusivity parameters of ipsilateral CST. Correlations between MRI data with cortical excitability data were computed by Spearman tests. The results did not show correlation between cortical lesions count and cortical excitability data. There was a correlation between ICFmean and ICFmax with radial diffusivity (r=0.56; p=0.004 et r=-0.59; p=0.002, respectively) and with ADC (r=-0.44; p=0.03 et r=-0.45; p=0.02, respectively) which suggests a defective ICF by demyelinated lesions.

Tensors occur in many areas of science and engineering. Especially, they are used to describe charge, mass and energy transport (i.e. electrical conductivity tensor, diffusion tensor, thermal conduction tensor resp.) If the locale transport pattern is complicated, usual second order tensor representation is not sufficient. So far, there are no appropriate visualization methods for this case. We point out similarities of symmetric higher order tensors and spherical harmonics. A spherical harmonic representation is used to improve tensor glyphs. This paper unites the definition of streamlines and tensor lines and generalizes tensor lines to those applications where second order tensors representations fail. The algorithm is tested on the tractography problem in diffusion tensor magnetic resonance imaging (DT-MRI) and improved for this special application.

Objective: Reductions of gray matter volume and cortical thickness in anorexia nervosa (AN) are well documented. However, findings regarding the integrity of white matter (WM) as studied via diffusion weighted imaging (DWI) are remarkably heterogeneous, and WM connectivity has been examined only in small samples using a limited number of regions of interest. The present study investigated whole-brain WM connectivity for the first time in a large sample of acutely underweight patients with AN. Method: DWI data from predominantly adolescent patients with acute AN (n ¼ 96, mean age ¼ 16.3 years) and age-matched healthy control participants (n ¼ 96, mean age ¼ 17.2 years) were analyzed. WM connectivity networks were generated from fiber-tractography-derived streamlines connecting 233 cortical/subcortical regions. To identify group differences, network-based statistic was used while taking head motion, WM, and ventricular volume into account. Results: Patients with AN were characterized by 6 WM subnetworks with abnormal architecture, as indicated by increased fractional anisotropy located primarily in parietal-occipital regions and accompanied by reduced radial diffusivity. Group differences based on number of streamlines reached only nominal significance. Conclusion: Our study reveals pronounced alterations in the WM connectome in young patients with AN. In contrast to known reductions in gray matter in the acutely underweight state of AN, this pattern does not necessarily indicate a deterioration of the WM network. Future studies using advanced MRI sequences will have to clarify interrelations with axonal packing or

Diffusion Magnetic Resonance Imaging (dMRI) is a method for measuring molecular diffusion in biological tissue microstructure. This information can be used to predict the location and orientation of white matter fibers in the brain, a process known as tractography. Analysis of the map of neural connections can provide meaningful information about the severity or progression of neurodegenerative diseases such as Alzheimer's, and allow for early intervention to prevent progression. However, tractography has its pitfalls; current fiber-tracking algorithms suffer from generating false-positive connections and affect the reliability of structural connectivity maps. To counter this downside, tractogram filtering methods have been created to remove inaccurately predicted connections. This study aims at evaluating the impact of the novel semi-supervised filtering method FINTA on the brain networks of people with Mild Cognitive Impairment (MCI), which precedes diseases like Alzheimer's. The proposed experiments use the Nipype Neuroimaging Python library for the automation of the entire process. Registration, parcellation, and tracking were performed using MRtrix and FSL. Furthermore, DIPY and NiBabel were used for tractogram processing. Finally, filtering was performed based on code provided by the authors of FINTA, and graph measures were computed using the NetworkX Python library. Experiments were performed on both raw and weighted structural connectivity matrices. Results suggest that filtering has an effect on graph measures such as the clustering coefficient and betweenness centrality for different nodes corresponding to brain regions. / Diffusion magnetisk resonanstomografi (diffusions MRT) är en metod för att mäta den molekylära diffusionen i mikrostrukturen i biologisk vävnad. Denna information kan användas för att förutsäga var fibrerna i den vita substansen i hjärnan befinner sig och hur de är orienterade i den process som kallas traktografi. Analys av kartan över nervförbindelser kan ge meningsfull information om svårighetsgraden eller utvecklingen av neurodegenerativa sjukdomar som Alzheimers och möjliggöra tidiga insatser för att förhindra utvecklingen. Traktografi har dock sina fallgropar och nuvarande algoritmer för fiberspårning lider av att generera falska positiva anslutningar och påverkar de strukturella konnektivitetskartorna som förhindrar tillförlitliga förutsägelser. För att motverka denna nackdel har filtreringsmetoder för traktogram skapats för att ta bort de felaktigt förutsagda anslutningarna.  Denna studie syftar till att utvärdera effekterna av den nya semi-övervakade filtreringsmetoden FINTA på hjärnnätverk hos personer med lindrig kognitiv störning (eng. mild cognitive impairment, MCI) som föregår sjukdomar som Alzheimers. I de föreslagna experimenten används Python-biblioteket Nipype Neuroimaging för automatisering av hela processen. Registrering, parcellering och spårning gjordes med hjälp av MRtrix och FSL, dessutom användes DIPY och NiBabel för traktogrambehandling. Slutligen utfördes filtrering baserat på kod från författarna till FINTA och grafmått beräknades med hjälp av NetworkX Python-bibliotek. Experimenten utfördes på råa och viktade strukturella konnektivitetsmatriser. Resultaten tyder på att filtrering har en effekt på grafmått som klustringskoefficient och betweenness centrality för olika noder som motsvarar hjärnregioner.

Odorous sensations are based on trigeminal and olfactory perceptions. Both trigeminal and olfactory stimuli generate overlapping as well as distinctive activations in the olfactory cortex including the piriform cortex. Orbitofrontal cortex (OFC), an integrative center for all senses, is directly activated in the presence of olfactory stimulations. In contrast, the thalamus, a very important midbrain structure, is not directly activated in the presence of odors, but rather acts as a relay for portions of olfactory information between primary olfactory cortex and higher-order processing centers. The aims of the study were (1) to examine the number of streamlines between the piriform cortex and the OFC and also between the piriform cortex and the thalamus and (2) to explore potential correlations between these streamlines and trigeminal and olfactory chemosensory perceptions. Thirty-eight healthy subjects were recruited for the study and underwent diffusion MRI using a 3T MRI scanner with 67 diffusion directions. ROIs were adapted from two studies looking into olfaction in terms of functional and structural properties of the olfactory system. The “waytotal number” was used which corresponds to number of streamlines between two regions of interests. We found the number of streamlines between the piriform cortex and the thalamus to be higher in the left hemisphere, whereas the number of streamlines between the piriform cortex and the OFC were higher in the right hemisphere. We also found streamlines between the piriform cortex and the thalamus to be positively correlated with the intensity of irritating (trigeminal) odors. On the other hand, streamlines between the piriform cortex and the OFC were correlated with the threshold scores for these trigeminal odors. This is the first studying the correlations between streamlines and olfactory scores using tractography. Results suggest that different chemosensory stimuli are processed through different networks in the chemosensory system involving the thalamus.

Magnetic Resonance Imaging (MRI) is a cornerstone in neuroimaging for studying brain anatomy and functions. Anatomical MRI images, such as T1-weighted (T1-w) scans, allow the non-invasive visualization of the brain tissues, enabling the investigation of the brain morphology and facilitating the diagnosis of both acquired (e.g., tumors, stroke lesions, infections) and congenital (e.g., malformations) brain disorders. T1-w images provide a detailed representation of brain anatomy and accurate differentiation between the main brain structures, such as white matter (WM) and gray matter (GM), therefor they are frequently used in combination with advanced sequences such as diffusion MRI (dMRI) for the computation of the structural connectivity of the brain. In particular, from the processing of dMRI data, it is possible to investigate the structures of WM through tractography techniques, obtaining a virtual representation of the WM pathways called tractogram. Since the tractogram is a collection of digital fibers representing the neuronal axons connecting the brain's cortical areas, it is the fundamental element for studying the brain's structural connectivity. A critical step for processing the tractography data is the accurate labeling of the brain tissues, usually performed through brain tissue segmentation of T1-w images. Even though the gold standard is manual segmentation, it is time-consuming and prone to intra/inter-operator variability. Automated model-based methods produce more consistent and reliable results, however, they struggle with accuracy in the case of pathological brains due to reliance on priors based on normal anatomy. Recently, deep learning (DL) has shown the potential of supervised data-driven approaches for brain tissue segmentation by leveraging the information encoded in the signal intensity of T1-w images. As a first contribution of this thesis, we reported empirical evidence that a data-driven approach is effective for brain tissue segmentation in pathological brains. By implementing a DL network trained on a large dataset of only healthy subjects, we demonstrated improvements in segmenting the brain tissues compared to models based on healthy anatomical priors, especially on severely distorted brains. Additionally, we published a benchmark for enabling an open investigation into improving tissue segmentation of distorted brains, providing a training dataset of about one thousand healthy individuals with T1-w MR images and corresponding brain tissue labels, and a test dataset includes several tens of individuals with severe brain distortions. Another crucial aspect of processing tractography data for brain connectivity analysis is the correct alignment of the WM structures across different subjects or their normalization into a common reference space, usually performed as tractography alignment. The best practice is to perform the registration using T1-w images and then apply the resulting transformation to align the tractography, despite T1-w images lacking fiber orientation information. In light of this, various methods have been proposed to leverage the information of the WM from dMRI data, ranging from scalar diffusion maps to more complex models encoding fiber orientation in the voxels. As a second contribution to the thesis, we provide a comprehensive survey of methods for conducting tractogram alignment. Additionally, we include an empirical study with the results of a quantitative comparison among the main methods for which an implementation is available. From our findings, the use of increasingly complex diffusion models does not significantly improve the alignment of tractograms. Conversely, correspondence methods that use the fibers directly to compute the alignment outperform voxel-based methods, albeit with some limitations: not producing a deformation field, operating in an unsupervised manner, and avoiding using anatomical information. Recently, geometric deep learning (GDL) models have shown promising results in handling non-grid data like tractograms, offering new possibilities for WM structure alignment. The third main contribution of this thesis is implementing a GDL model for tractogram alignment through a supervised approach guided by fiber correspondence. The alignment is predicted as the displacement of fiber points, based on a GDL registration framework that combines graph convolutional networks and differentiable loopy belief propagation, incorporating the definition of fiber structure into the encoding of the graph. Our empirical analysis demonstrates the advantages of utilizing the proposed GDL framework over traditional volumetric registration, showcasing high alignment accuracy, low inference time, and good generalization capabilities. Overall, this thesis advances the methodology for processing MRI data for brain structural connectivity, addressing the challenges of tissue segmentation and tractography alignment, proving the potential of DL approaches also in the case of pathological brains.

L'objectif de cette thèse est de fournir une chaine de traitement complète pour la reconstruction des faisceaux de la matière blanche à partir d'images pondérées en diffusion caractérisées par une faible résolution angulaire. Cela implique (i) d'inférer en chaque voxel un modèle de diffusion à partir des images de diffusion et (ii) d'accomplir une ''tractographie", i.e., la reconstruction des faisceaux à partir de ces modèles locaux. Notre contribution en modélisation de la diffusion est une nouvelle distribution statistique dont les propriétés sont étudiées en détail. Nous modélisons le phénomène de diffusion par un mélange de telles distributions incluant un outil de sélection de modèle destiné à estimer le nombre de composantes du mélange. Nous montrons que le modèle peut être correctement estimé à partir d'images de diffusion ''single-shell" à faible résolution angulaire et qu'il fournit des biomarqueurs spécifiques pour l'étude des tumeurs. Notre contribution en tractographie est un algorithme qui approxime la distribution des faisceaux émanant d'un voxel donné. Pour cela, nous élaborons un filtre particulaire mieux adapté aux distributions multi-modales que les filtres traditionnels. Pour démontrer l'applicabilité de nos outils en usage clinique, nous avons participé aux trois éditions du MICCAI DTI Tractography challenge visant à reconstruire le faisceau cortico-spinal à partir d'images de diffusion ''single-shell" à faibles résolutions angulaire et spatiale. Les résultats montrent que nos outils permettent de reconstruire toute l'étendue de ce faisceau. / The objective of this thesis is to provide a complete pipeline that achieves an accurate reconstruction of the white matter fascicles using clinical diffusion images characterized by a low angular resolution. This involves (i) a diffusion model inferred in each voxel from the diffusion images and (ii) a tractography algorithm fed with these local models to perform the actual reconstruction of fascicles. Our contribution in diffusion modeling is a new statistical distribution, the properties of which are extensively studied. We model the diffusion as a mixture of such distributions, for which we design a model selection tool that estimates the number of mixture components. We show that the model can be accurately estimated from single shell low angular resolution diffusion images and that it provides specific biomarkers for studying tumors. Our contribution in tractography is an algorithm that approximates the distribution of fascicles emanating from a seed voxel. We achieve that by means of a particle filter better adapted to multi-modal distributions than the traditional filters. To demonstrate the clinical applicability of our tools, we participated to all three editions of the MICCAI DTI Tractography challenge aiming at reconstructing the cortico-spinal tract from single-shell low angular and low spatial resolution diffusion images. Results show that our pipeline provides a reconstruction of the full extent of the CST.

A esquizofrenia é um transtorno mental de alta complexidade e até o presente momento nenhuma teoria conseguiu explicar completamente sua etiologia. Uma dessas teorias acredita que a transferência de informações entre os hemisférios de pacientes com esquizofrenia, que ocorre através do corpo caloso, comissura anterior e posterior, pode estar comprometida. Os objetivos do nosso estudo foram avaliar se existem alterações de conectividade inter-hemisférica (IH) e se essas alterações sofrem influência do gênero, em pacientes portadores de esquizofrenia quando comparados com seus parentes em primeiro grau e controles saudáveis, utilizando-se da imagem de ressonância magnética por tensor de difusão (IRMTD). Participaram do estudo 30 pacientes portadores de esquizofrenia, diagnosticados pelos critérios do Manual diagnóstico e estatístico das doenças mentais em sua quarta edição, os quais foram selecionados entre os pacientes do grupo de medicações atípicas do ambulatório de esquizofrenia e da enfermaria psiquiátrica do Hospital das Clínicas da Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo; 30 parentes em primeiro grau desses pacientes; e 30 voluntários saudáveis. Todos os sujeitos do estudo foram submetidos a um exame de ressonância magnética, realizado no Centro de Ciências das Imagens e Física Médica de nossa instituição, onde foram adquiridas as sequências volumétricas e difusionais utilizadas em nosso estudo. Em posse das imagens de ressonância magnética dos 90 sujeitos do estudo, realizamos o pós-processamento dessas imagens, utilizando o software BrainVoyager QX® versão 2.4, com o intuito de obtermos, por meio dos dados provenientes da IRMTD, os mapas de anisotropia fracional (AF) e difusibilidade média (DM). Com esses mapas em mãos, procedemos à análise estatística do estudo, denominada de análise de covariância voxel a voxel (VANCOVA), no cérebro todo. Nessa análise, utilizamos a idade como covariável e verificamos a influência do gênero nos resultados encontrados. Nossos resultados 6 evidenciaram que os pacientes portadores de esquizofrenia apresentaram valores de AF e DM alterados em estruturas homólogas ao corpo caloso e áreas frontais adjacentes. Assim, podemos afirmar que descobrimos perda de conectividade IH nesses mesmos pacientes. Por meio de nosso estudo, descobrimos também a influência do gênero nos valores de AF e DM encontrados e então, consequentemente, podemos dizer que a conectividade IH de pacientes portadores de esquizofrenia sofreu influência do sexo. A idade também mostrou influenciar a conectividade IH de nossos pacientes. Com o atual conceito de que alterações de AF e DM podem ser encaradas como indicativos de comprometimento da mielina, e sabendo que a mielina participa diretamente das reações neuroquímicas do sistema glutamatérgico cerebral, também podemos dizer que o sistema glutamatérgico que participa da conectividade IH desses pacientes encontrava-se comprometido. / Schizophrenia is a highly complex mental disorder and no theory to date was able to fully explain the etiology of this disorder. One of the existing theories advocates that interhemispheric communication, which occurs through the corpus callosum and the anterior and posterior commissures, might be impaired in schizophrenia. Our study was designed to investigate whether there are interhemispheric connectivity (IC) alterations in schizophrenia and whether these alterations are influenced by gender through the comparison of schizophrenia patients with their first-degree relatives and healthy controls using diffusion tensor imaging (DTI). We enrolled 30 schizophrenia patients diagnosed according to the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders and selected from the Group of Atypical Medications of the Schizophrenia Outpatient Clinic and the psychiatric ward of the Ribeirão Preto Medical School University Hospital, 30 first-degree relatives of these patients and 30 healthy volunteers. All subjects underwent magnetic resonance imaging (MRI) scans for the acquisition of volumetric and diffusion sequences. The images were post-processed using BrainVoyager QX® version 2.4 to create fractional anisotropy (FA) and mean diffusivity (MD) maps from DTI data. The resulting data were analyzed using voxel-to- voxel analysis of covariance (VANCOVA) for the whole brain. In this analysis, we used age as a co-variable and assessed the influence of gender. Our results showed that schizophrenia patients had altered FA and MD values in structures homologous to the corpus callosum and adjacent frontal areas, suggestive of IC loss in the patients. We also found that gender influenced FA and MD values and, therefore, that IC in schizophrenia patients is influenced by gender. Age was also found to influence IC in our patients. Based on the current conception that FA and MD alterations may indicate myelin impairment and knowing that myelin participates directly in neurochemical reactions of the glutamatergic system in the brain, we can infer that the glutamatergic system, which is implicated in IC, is affected in schizophrenia and is influenced by gender.

La plupart des constructeurs de systèmes d'imagerie par résonance magnétique (IRM) proposent un large choix d'applications de post-traitement sur les données IRM reconstruites a posteriori, mais très peu de ces applications peuvent être exécutées en temps réel pendant l'examen. Mises à part certaines solutions dédiées à l'IRM fonctionnelle permettant des expériences relativement simples ainsi que d'autres solutions pour l'IRM interventionnelle produisant des scans anatomiques pendant un acte de chirurgie, aucun outil n'a été développé pour l'IRM pondérée en diffusion (IRMd). Cependant, comme les examens d'IRMd sont extrêmement sensibles à des perturbations du système hardware ou à des perturbations provoquées par le sujet et qui induisent des données corrompues, il peut être intéressant d'investiguer la possibilité de reconstruire les données d'IRMd directement lors de l'examen. Cette thèse est dédiée à ce projet innovant. La contribution majeure de cette thèse a consisté en des solutions de débruitage des données d'IRMd en temps réel. En effet, le signal pondéré en diffusion peut être corrompu par un niveau élevé de bruit qui n'est plus gaussien, mais ricien ou chi non centré. Après avoir réalisé un état de l'art détaillé de la littérature sur le bruit en IRM, nous avons étendu l'estimateur linéaire qui minimise l'erreur quadratique moyenne (LMMSE) et nous l'avons adapté à notre cadre de temps réel réalisé avec un filtre de Kalman. Nous avons comparé les performances de cette solution à celles d'un filtrage gaussien standard, difficile à implémenter car il nécessite une modification de la chaîne de reconstruction pour y être inséré immédiatement après la démodulation du signal acquis dans l'espace de Fourier. Nous avons aussi développé un filtre de Kalman parallèle qui permet d'appréhender toute distribution de bruit et nous avons montré que ses performances étaient comparables à celles de notre méthode précédente utilisant un filtre de Kalman non parallèle. Enfin, nous avons investigué la faisabilité de réaliser une tractographie en temps-réel pour déterminer la connectivité structurelle en direct, pendant l'examen. Nous espérons que ce panel de développements méthodologiques permettra d'améliorer et d'accélérer le diagnostic en cas d'urgence pour vérifier l'état des faisceaux de fibres de la substance blanche. / Most magnetic resonance imaging (MRI) system manufacturers propose a huge set of software applications to post-process the reconstructed MRI data a posteriori, but few of them can run in real-time during the ongoing scan. To our knowledge, apart from solutions dedicated to functional MRI allowing relatively simple experiments or for interventional MRI to perform anatomical scans during surgery, no tool has been developed in the field of diffusion-weighted MRI (dMRI). However, because dMRI scans are extremely sensitive to lots of hardware or subject-based perturbations inducing corrupted data, it can be interesting to investigate the possibility of processing dMRI data directly during the ongoing scan and this thesis is dedicated to this challenging topic. The major contribution of this thesis aimed at providing solutions to denoise dMRI data in real-time. Indeed, the diffusion-weighted signal may be corrupted by a significant level of noise which is not Gaussian anymore, but Rician or noncentral chi. After making a detailed review of the literature, we extended the linear minimum mean square error (LMMSE) estimator and adapted it to our real-time framework with a Kalman filter. We compared its efficiency to the standard Gaussian filtering, difficult to implement, as it requires a modification of the reconstruction pipeline to insert the filter immediately after the demodulation of the acquired signal in the Fourier space. We also developed a parallel Kalman filter to deal with any noise distribution and we showed that its efficiency was quite comparable to the non parallel Kalman filter approach. Last, we addressed the feasibility of performing tractography in real-time in order to infer the structural connectivity online. We hope that this set of methodological developments will help improving and accelerating a diagnosis in case of emergency to check the integrity of white matter fiber bundles.

Il est de plus en plus reconnu que les connexions du cerveau jouent un rôle important sur la fonction cérébrale, en particulier les fonctions cognitives supérieures comme le langage. Cependant l’imperfection des techniques traitant les connexions macroscopiques humaines a empêché l’avancement de nos connaissances sur l'anatomie des faisceaux. Nous nous appuyons ainsi aujourd’hui essentiellement sur la littérature du XIXème siècle. Les définitions des trajets et des connexions anatomiques de nombreux faisceaux sont constamment débattues. En utilisant l'imagerie de diffusion, nous réévaluons les anatomies des faisceaux clés dans une grande cohorte saine. Nous utilisons une nouvelle approche de segmentation des faisceaux qui vise à reproduire la méthode introduite par les dissectionistes. Celle-ci définit un tract comme l’ensemble des fibres passant par une même tige, minimisant ainsi l’a priori sur leurs terminaisons. Nous nous concentrons sur les faisceaux d'association des capsules externe et extrême, notamment les faisceaux occipito-frontal inférieur (FOFI) et unciné (FU) impliqués dans le circuit du langage ventral. Nous passons en revue la littérature sur ces tracts, fournissons des descriptions détaillées de leurs connectivités anatomiques et donnons un nouvel éclairage sur leur asymétrie et organisation interne. Dans une première étude, nous confirmons que les deux faisceaux ont de plus vastes projections dans le cortex qu'on ne le pensait, et nous présentons de nouveaux résultats concernant les branches asymétriques des faisceaux. Dans une deuxième étude, nous étudions en profondeur le FU et ses sous composantes. Nous résolvons un débat d’un siècle en exhibant clairement sa frontière avec le FOFI et nous identifions pour chaque sous composante des caractéristiques anatomiques distinctives y compris des asymétries. Ces résultats apportent un éclairage nouveau sur le FOFI et le FU qui sera crucial pour démêler leurs rôles multifonctionnels. / The importance of the brain’s connections for cerebral function is increasingly emphasized especially for higher cognitive functions like language. But the imperfection of the techniques used to address the human macroscopic connections has prevented the advancement of our knowledge on the anatomy of fibre pathways. Thus we rely heavily on XIXth century literature. Controversy surrounding the anatomical course and connections of many fibre pathways persists. Using diffusion imaging, we reevaluate the anatomies of key pathways in a large healthy cohort. We use a novel tract segmentation approach that aims to reproduce the method introduced by dissectionists – defining a tract as all fibers passing through a stem, thus minimizing a priori on their terminations. We focus on the association pathways of the external and extreme capsules, namely the inferior fronto-occipital (IFOF) and uncinate fasciculi (UF), implicated in the ventral language circuitry. We review the literature on these tracts, provide detailed descriptions of their connectional anatomies and present new insights regarding their asymmetry and internal organization. In a first study, we confirm that both tracts have more extensive projections within the cortex than previously thought and present new results regarding asymmetrical tract branches. In a second study we further investigate the UF including its subcomponents. We resolve a century old debate by clarifying its elusive boundary with the IFOF and reveal the distinctive anatomical features including asymmetry patterns of each subcomponent. These results shed new light on the IFOF and UF and will be crucial for disentangling their multifunctional roles.