Neste trabalho apresentamos uma nova abordagem para a exploração de fibras neurais a partir de imagens de tensores de difusão. A estratégia combina técnicas de visualização de informação e visualização científica para obter uma rápida e precisa interpretação das fibras. Para isto fazemos uma transformação das fibras para vetores, e utilizamos uma nova técnica de projeção multi-dimensional (P-LSP), para trabalhar com conjuntos grandes de dados. A exploração do espaço das fibras é feita através desta projeção. Além disso, é apresentada a extensão das técnicas LSP e P-LSP para criar projeções em 3D, assim como estratégias que permitem interagir com pontos em 3D. Outra contribuição deste trabalho é a modificação de um método apresentado para criar superfícies de densidade fechadas sobre pontos esparsos. Esta modificação torna possível criar superfícies sobre conjuntos de pontos maiores com uma qualidade aceitável, o que é utilizado para representar conjunto de fibras como uma superfície. Esta nova abordagem é comparada com trabalhos similares mostrando nossas vantagens em termos de tempo de processamento, qualidade e funcionalidades para analisar esta categoria de dados / This work presents a novel approach for the exploration of neural fibers extracted from Diffusion Tensor Images. The developed strategy combines techniques from information and scientific visualization in order to attain a fast and precise interpretation of fiber sets. The approach transforms fibers into vectors from which a new multidimensional projection technique (PLSP) capable of handling large data sets. The fiber space is explored through the projection. Additionally this work extends P-LSP and LSP projections to 3D, and defines strategies to interact with 3D sparse points. Another contribution of this work is the extension of a method to create close density surfaces over the sparse space generated by the projections. The visualization approach is compared with other similar work showing advantages in processing time, quality and exploration capability to analyze this type of data sets

Neste trabalho apresentamos uma nova abordagem para a exploração de fibras neurais a partir de imagens de tensores de difusão. A estratégia combina técnicas de visualização de informação e visualização científica para obter uma rápida e precisa interpretação das fibras. Para isto fazemos uma transformação das fibras para vetores, e utilizamos uma nova técnica de projeção multi-dimensional (P-LSP), para trabalhar com conjuntos grandes de dados. A exploração do espaço das fibras é feita através desta projeção. Além disso, é apresentada a extensão das técnicas LSP e P-LSP para criar projeções em 3D, assim como estratégias que permitem interagir com pontos em 3D. Outra contribuição deste trabalho é a modificação de um método apresentado para criar superfícies de densidade fechadas sobre pontos esparsos. Esta modificação torna possível criar superfícies sobre conjuntos de pontos maiores com uma qualidade aceitável, o que é utilizado para representar conjunto de fibras como uma superfície. Esta nova abordagem é comparada com trabalhos similares mostrando nossas vantagens em termos de tempo de processamento, qualidade e funcionalidades para analisar esta categoria de dados / This work presents a novel approach for the exploration of neural fibers extracted from Diffusion Tensor Images. The developed strategy combines techniques from information and scientific visualization in order to attain a fast and precise interpretation of fiber sets. The approach transforms fibers into vectors from which a new multidimensional projection technique (PLSP) capable of handling large data sets. The fiber space is explored through the projection. Additionally this work extends P-LSP and LSP projections to 3D, and defines strategies to interact with 3D sparse points. Another contribution of this work is the extension of a method to create close density surfaces over the sparse space generated by the projections. The visualization approach is compared with other similar work showing advantages in processing time, quality and exploration capability to analyze this type of data sets

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第17572号 / 工博第3731号 / 新制||工||1569(附属図書館) / 30338 / 京都大学大学院工学研究科電気工学専攻 / (主査)教授 小林 哲生, 教授 土居 伸二, 教授 山川 宏 / 学位規則第4条第1項該当

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The knowledge of the behavior of non-spherical particles suspended in turbulent flows covers a wide range of applications in engineering and science. Dispersed two-phase flows and turbulence are the most challenging subjects in engineering, and when combined it gives rise to more complexities as the result of the inherent stochastic nature of the turbulence of the carrier-phase together with the random distribution of the dispersed phase. Moreover, for anisotropic particles the coupling between the translation and rotation of particle increases the complication. Because of the practical importance of prolate particleladen turbulent flows, the plenty of numerical and experimental works have been conducted to study such suspensions. Numerical approaches have given valuable insight of turbulent suspension flows, although the computation has been only carried out at the macro scale and models, not including flow distortion around the particle, comprise the detail of the flow in the order of a particle size. In addition, the model of the forces imposed on the particle by the fluid and mass point treatment are strictly valid for infinitely small particle having size less than all scales of the fluid turbulence. Fully resolved solution at the scale of the dispersed phase in turbulent flows for high Reynolds number has been recently performed but is still a challenge. On the other hand, the presence of particle as the dispersed phase makes experimental measurements much more complicated than those with single phase as a result of particles interference. The area of considerable difficulty with this type of experiments is the measurement of the fluid-phase velocity remarkably close to the particle surface. Generally, experimental researches have been concentrated on measuring the mean velocity and Reynolds stresses of the carrier-phase, and the mean velocity, fluctuations, orientation and accumulation of the non-spherical particles. Higher-order quantities, including Lagrangian particle velocity correlations, the carrier-phase turbulence modulation, and two-particle and particlefluid velocity correlations are also of interest. It has been found that the rotational and translational movements of the fibershaped particle depend on the nature of carrier-phase field and fiber characteristics such as aspect ratio, fiber Stokes number, fiber Reynolds number, and the ratio of fiber to flow length scale. With the development of PIV (Particle Image Velocimetry) and PTV (Particle Tracking Velocimetry) techniques, it has been appeared that combined PIV/PTV will be the best available choice for the experimental study of dispersed two-phase flows. The purpose of combined PIV/PTV measurement of two-phase systems is simultaneous measurements of fluid and suspended objects, where the PIV measurement of the fluid phase are combined with PTV measurement of the dispersed phase. The objective of this doctoral thesis is to study the behavior of rod-like particles suspended in wall-bounded turbulent flow through simultaneous PIV/PTV measurements of the velocity of the flow field and particle motion. As a representative of rod-like particles, I have employed cellulose acetate fibers with the length to diameter ratio (aspect ratio) larger than one. Here, It has been considered only dilute suspensions with no flocculation; thus fiber-fiber interaction is negligible. The measurements have been conducted within the parallel planes (2D view) illuminated by laser in the streamwise direction in thin film suspension flowing on the water table setup at Linné FLOW Centre, KTH Mechanics Lab. It is shown that this setup is a well-behaved experimental model of half channel flows often used in Direct Numerical Simulation (DNS) investigations. Therefore, the experimental results are comparable to their DNS counterpart where it is convenient. A single camera PIV technique has been used to measure flowing suspension. Therefore, it has been needed to preprocess images using a spatial median filter to separate images of two phases, tracer particles as representative of fluid and fibers suspended. The well-known PIV processing algorithms have been applied to the phase of fluid. I have also introduced a novel algorithm to recognize and match fibers in consecutive images to track fibers and estimate their velocity. It is not feasible to study all relevant aspects of particle-laden turbulent flows in a single study. In this study, I present the statistics of the rotational and translational motion of fiber-like particles and the surrounding fluid velocity. To the author’s knowledge, remarkably little experimental work has been published to date on simultaneous measurement of fiber motion and turbulence field in a turbulent fiber suspension flow to reveal dynamics of fibers in this regime. Therefore, the results of this work will be profitable in better understanding of such multiphase flows. The statistical analysis of the translational motion of fibers shows that the size of fiber is a significant factor for the dynamical behavior of the fiber near the wall. It has been observed that, in the region near the wall, the probability of presence of the long fibers is high in both the high-speed and low-speed streaks of flow, and the mean velocity of fibers almost conforms to the mean velocity of flow; whereas the short fibers are mostly present in the low-speed areas, and the fiber mean velocity obey the dominant flow velocity in these areas. In the far-wall regions, the translation of fibers is practically unaffected by the aspect ratio, whereas it depends crucially on the wall-normal distance. Moreover, it was found that in the case of long fibers near the wall, the low speed fibers mostly are orientated in streamwise direction. On the other hand, there is no preferential orientation for fast long fibers. Although wall-normal velocities were not measured in this study, it is hypothesized that this behavior is a result of fibers being affected by the sweep and ejection events known to occur in wall-bounded turbulent flow. The fast fibers are in sweep environment and comes from the upper layer. The low speed fibers are into ejection areas in the vicinity of the wall, and the wall has a stabilizing effect on them. The short fibers are still oriented mostly in streamwise direction for a certain range of low velocity. Furthermore, since a considerable change of the fiber behavior is observed in a certain ratio of the fiber length to the fiber distance from the solid wall, it is supposed that this ratio is also a prominent parameter for the behavior of fiber near the wall. The results presented are in terms of viscous wall units wherever are denoted by superscript “+”.

L’objectif de cette thèse est de développer des méthodes IRM permettant d’étudier l’impact d’une ischémie focale transitoire sur le cerveau de rat nouveau-né. Les techniques utilisées sont l’imagerie à contraste renforcé par le manganèse (MEMRI), l’imagerie du tenseur de diffusion (DTI) ainsi que de façon préliminaire l’imagerie Q-ball (QBI). Le MEMRI après injection intra cérébrale a été utilisé afin d’étudier de manière dynamique le tractus cortico-thalamique, en parallèle le DTI a servi de marqueur de la structuration cérébrale. Les résultats ont montré une atteinte du tractus cortico-thalamique ipsi-latéral, sept et quatorze jours après ischémie. De manière générale le DTI a montré une structuration ralentie à la suite de l’ischémie. A partir de ces résultats la faisabilité d’une méthode d’acquisition rapide et de traitement de données Q-ball a été établie puis testée sur un animal immature. Les méthodes mises en place se sont révélées efficaces dans le suivi de la maturation cérébrale dans des conditions normales ainsi que pathologiques, ouvrant des perspectives d’études liées au développement cérébral. / The thesis aim is to develop MRI methods to study the impact of focal transient ischemia in neonatal rat brain. The principal techniques used are MEMRI (Manganese Enhanced MRI), DTI (Diffusion Tensor Imaging) and QBI (Q-Ball Imaging). MEMRI was used to observe in a dynamic way the cortico-thalamic manganese transport combined with the structural informations extracted from the DTI experiments. Results have shown a cortico-thalamic pathway disturbance, at seven and fourteen days after ischemia. Globally DTI results have shown a slowed brain structuration. From these results, the feasibility of a fast acquisition method and the post processing steps of Q-ball protocol was established and applied in an immature rat. The different MRI protocols developed during this thesis have shown good efficiency to follow the rat brain maturation, in healthy and pathological conditions, thus opening new perspectives for brain development studies.

A complete understanding of the functional and structural impairments driving persistent post-concussive symptom (PCS) expression in approximately one-third of those who suffer from mild traumatic brain injury (mTBI) is essential for the development of effective treatment strategies and improving quality of life. While traditional outcome measures, such as neuropsychological testing and structural magnetic resonance imaging, are sensitive to the severe functional impairments and widespread tissue damage frequently seen after moderate-to-severe injuries, more advanced measures that are sensitive to the subtle changes in cognitive function and tissue microstructure that may underlie persistent PCS are necessary for the assessment of recovery from mTBI. Toward this end, the current study investigates the utility of eye-tracking analysis and high-definition fiber tractography (HDFT) as advanced measures of functional and microstructural outcome in 11 adults with chronic mTBI and varying levels of PCS (ages 20-60; mean time post-injury = 9.53 ± 6.74 years) in comparison to 10 healthy adults (ages 20-54). Performance on neuropsychological and eye-tracking tasks of processing speed, attention, and working memory, and HDFT-derived quantitative measures of the microstructural integrity of the forceps major, inferior fronto-occipital fasciculus, middle longitudinal fasciculus, and superior longitudinal fasciculus were compared between groups, and the results were used to define discriminatory functions for mTBI classification. The relationships between neuropsychological and eye-tracking measures of cognitive function and HDFT-derived measures of tract integrity were explored, as was the utility of these functional and structural measures for predicting persistent PCS in chronic mTBI. The results suggest that eye-tracking analysis may be more specific to cognitive impairments resulting from mTBI than neuropsychological testing, and HDFT is highly sensitive and specific to the subtle microstructural changes that persist chronically in this population. Furthermore, white matter integrity assessed using HDFT is more strongly associated with impairments in processing speed, attention, and memory indicated through eye-tracking analysis relative to performance on neuropsychological tests. Finally, although the predictive utility of eye-tracking and HDFT for the experience of persistent PCS was not demonstrated in the present sample, the possibility that these data are confounded by symptom exaggeration, comorbid mental health impairment, or lack of self-awareness for functional deficits cannot be ruled out, and future research using large, homogenous sample of mTBI is necessary to validate the present findings.

L'imagerie en tenseur de diffusion (DTI) permet de fournir un complément d'informations quantitatives au niveau tissulaire et sur le suivi des fibres de substance blanche. Elle nous a permis d'explorer chez des patients atteints d'épilepsie du lobe temporal (TLE) des anomalies cérébrales non détectables par les techniques d'imagerie conventionnelles. Dans ce travail de thèse nous avons combiné deux méthodes computationnelles s'appuyant l'une sur l'extraction d'informations dans des régions d'intérêts localisées et l'autre sur des mesures effectuées (moyennées) le long des fibres de substance blanche. L'identification de paramètres, à partir du tenseur de diffusion, a permis de mettre en évidence des modifications structurales de la substance blanche et de la substance grise, notamment au niveau des régions du système limbique (hippocampe, fornix, régions cingulaires, thalamus, amygdala). Trois groupes de sujets ont participé à cette étude : un groupe de patients atteints d'épilepsie du lobe temporal avec sclérose hippocampique (TLE+HS), un groupe de patients sans lésion visible sur l'IRM conventionnelle (TLE-HS) et un groupe de sujets volontaires. Les résultats obtenus ont montré des anomalies significatives dans les régions analysées chez les patients TLE-HS, différentes des celles retrouvées chez les patients TLE+HS. Les indices de tenseur de diffusion retenus ont permis de mettre en évidence une désorganisation structurale des régions du système limbique chez les patients TLE, spécialement dans le groupe sans lésion visible sur l'IRM conventionnelle / Diffusion tensor imaging (DTI) can provide quantitative information of brain abnormalities in patients with temporal lobe epilepsy (TLE). This technique allowed us to explore brain abnormalities that are not detectable with conventional magnetic resonance imaging (MRI).In this thesis we combined two computational methods: the first is based on information extraction from regions of interest and the second is based on measurements (averaged) along the white matter fibers. The identification of parameters from diffusion tensor has highlighted structural changes in the white matter and gray matter, particularly in the limbic system regions (hippocampus, fornix, cingulate regions, thalamus, amygdala). Three subject groups participated on this study: a patients group with temporal lobe epilepsy and a hippocampal sclerosis (TLE+HS), a patients group with TLE and normal conventional MRI (TLE-HS) and a healthy controls group. The results showed significant abnormalities in the analysed regions in patients with TLE-HS, different from those found in patients with TLE + HS. The selected diffusion tensor indices allowed us to highlight the structural disorganization of limbic system regions in patients with TLE, especially in patients with normal conventional MRI

Ce travail vise au développement d’une méthode d’inférence des fibres de la substance blanche cérébrale fondée sur l’utilisation d’une approche globale de type « verres de spins » sous contraintes anatomiques. Contrairement aux méthodes classiques reconstituant les fibres indépendamment les unes des autres, cette approche markovienne reconstruit l’ensemble des fibres dans un unique processus de minimisation d’une énergie globale dépendant de la configuration des spins (position, orientation, longueur et connexion(s)) et de leur adéquation avec le modèle local du processus de diffusion, afin d'améliorer la robustesse et la réalité anatomique des fibres reconstruites. Le travail mené dans le cadre de cette thèse a donc consisté, en plus du développement de l’algorithme de tractographie, à étudier la possibilité de le contraindre à l’aide d’a priori anatomiques provenant de l’imagerie anatomique pondérée en T1 et des nouvelles approches de microscopie par IRM de diffusion fournissant des informations de nature micro-structurelle sur le tissu. En particulier, l’algorithme a été conçu pour autoriser une forte courbure des fibres à l’approche du ruban cortical et permettre leur connexion au sommet des gyri, mais également sur leurs flancs. Le modèle NODDI (Neurite Orientation Dispersion and Density Imaging) a gagné en popularité au cours des dernières années grâce à sa compatibilité avec une utilisation en routine clinique et permet de quantifier la densité neuritique et la dispersion angulaire des axones. Une forte dispersion traduit l’existence de populations de fibres d’orientations différentes ou une forte courbure d’un même faisceau de fibres au sein d'un voxel. Elle est donc exploitée pour relâcher la contrainte de faible courbure à proximité du cortex cérébral dans notre approche de tractographie globale lorsque cette dispersion angulaire est forte, permettant aux fibres de s'orienter par rapport à la normale locale au cortex. Cette contrainte est en revanche supprimée si la dispersion angulaire reste faible, indiquant une trajectoire à plus faible courbure, à l’instar des fibres se projetant dans le fond du gyrus ou des fibres en U. Les performances de cette nouvelle approche de tractographie sous contraintes anatomiques ont été évaluées à partir de données simulées, et ont été testées sur des données IRM post-mortem de très haute résolution et sur des données IRM in vivo de résolution millimétrique. En parallèle de ce développement méthodologique, une étude des corrélats locaux-régionaux de la densité neuritique et de l’activation cérébrale à la surface du cortex a été réalisée. L'étude a été menée sur la cohorte de sujets sains scannés dans le cadre du projet européen CONNECT dotée de données anatomiques, de diffusion et fonctionnelles reposant sur l’utilisation de paradigmes explorant en particulier les réseaux de la motricité, du langage et de la vision. Les données anatomiques ont permis d’extraire la surface piale et une parcellisation surfacique du cortex de chaque individu, les données de diffusion ont permis l’évaluation des cartographies individuelles de la densité neuritique au sein du ruban cortical et les données fonctionnelles du phénomène BOLD (Blood Oxygen Level Dependent) ont permis le calcul des cartographies individuelles des z-scores du modèle linéaire général pour différents contrastes. Une colocalisation des maxima de la densité neuritique et des pics d'activation a été observée, pouvant être interprétée comme une augmentation de la densité neuritique au sein des réseaux fonctionnels afin d'en améliorer l'efficacité. L’étude a également corroboré la latéralisation du réseau fonctionnel du langage et de la motricité, en accord avec la latéralisation de la population scannée tandis qu'une augmentation de la densité neuritique dans le cortex visuel droit a été observée pouvant être corrélée à des résultats d’étude de l’attention visuo-spatiale reportée dans la littérature chez le primate non-humain. / This work aims at developing a method inferring white matter fibers reconstructed using a global spin-glass approach constrained by anatomical prior knowledge. Unlike usual methods building fibers independently from one another, our markovian approach reconstructs the whole tractogram in an unique process by minimizing the global energy depending on the spin glass configuration (position, orientation, length and connection(s)) and the match with the local diffusion process in order to increase the robustness and the accuracy of the algorithm and the anatomical reliability of the reconstructed fibers. Thus, the work done during this PhD, along with the development of the global tractography algorithm, consisted in studying the feasibility of the anatomical prior knowledge integration stemming from the T1 weighted MRI and from new diffusion MRI microstructure approaches providing microstructural information of the surrounding tissue. In particular, the algorithm was built to allow a high fiber curvature when getting closer to the cortical ribbon and thus enabling the connection not only at the end of the gyri but also on their sides. The NODDI (Neurite Orientation Dispersion and Density Imaging) model has become more and more popular during the past years thanks to its capability to be used in clinical routine and allows to quantify neurite density and axons angular dispersion. A high dispersion means the existence of different fibers population or a high curvature of a fascicle within a voxel. Thus, the orientation dispersion has been used in our global tractography framework to release the curvature constraint near the cerebral cortex when the angular dispersion is high, allowing fibers to orientate collinear to the local normal to the cortical surface. However, this constraint is removed if the angular dispersion stays low, meaning a low curvature fiber trajectory following the example of the fibers projecting to the end of a gyrus or the U-fibers. The performances of this new tractography approach constrained by anatomical prior knowledge have been evaluated on simulated data, and tested on high resolution post-mortem MRI acquisitions and millimetric resolution in vivo MRI acquisitions. In parallel of this methodological development, a study about local-regional correlations between neurite density and cerebral activation on the cortical surface has been made. This study has been conducted on the healthy volunteers cohort scanned in the frame of the European CONNECT project including anatomical, diffusion and functional data. The anatomical data has been used to extract the pial surface and an individual parcellation on the cortical surface for each volunteer, the diffusion data has been used to evaluate the individual maps of neurite density within the cortical ribbon and the functional data from the BOLD (Blood Oxygen Level Dependent) effect has been used to calculate the individual z-scores of the general linear model for specific contrasts investigating the motor, language and visual networks. A co-localization of neurite density and activation peaks has been observed, which might indicate an increase of the neurite density within functional networks in order to increase its efficiency. This study also corroborates the lateralization of the language functional network and the motor one, in good agreement with the population lateralization, while an increase of the neurite density in the visual cortex has been observed which might be correlated to the results of visuo-spatial attention studies described in the literature on the non-human primate.

Diffusion Tensor Imaging (DTI) is a well-established magnetic resonance technique that can non-invasively interpret tissue geometry and track neural pathways by sampling the diffusion of water molecules in the brain tissue. However, it is currently limited to tracking large nerve fiber bundles and fails to faithfully resolve thinner fibers. Conventional DTI studies use a diffusion time, t[subscript diff] of 30 ms - 55 ms for diffusion measurements. This work proposes the use of DTI at long t[subscript diff] to enhance the sensitivity of the method towards regions of low diffusion anisotropy and improve tracking of smaller fibers. The Stimulated Echo Acquisition Mode (STEAM) sequence was modified to allow DTI measurements at long t[subscript diff] (approximately 200 ms), while avoiding T2 signal loss. For comparison, DTI data was acquired using STEAM at the shorter value of t[subscript diff] and with the standard Double Spin Echo sequence with matched signal-to-noise ratio. This approach was tested on phantoms and fixed monkey brains and then translated to in vivo studies in rhesus macaques. Qualitative and quantitative comparison of the techniques was based on fractional anisotropy, diffusivity, three-phase plots and directional entropy. Tensor-field maps and probabilistic connectivity fronts were evaluated for all three acquisitions. Comparison of the tracked nerve pathways showed that fibers obtained at long t[subscript diff] were much longer. Further, the optic tract was tracked in ex vivo fixed rhesus brains for cross validation. The optic tract, traced at long t[subscript diff], conformed to the well documented anatomical description, thus confirming the accuracy of tract tracing at long t[subscript diff]. The benefits of DTI at long t[subscript diff] indeed help to realize the potential of tensor based tractography towards studying neural development and diagnosing neuro-pathologies, albeit the improvement is more significant ex vivo than in vivo.