Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

L’imagerie par résonance magnétique (IRM) est un outil de choix pour la caractérisation tissulaire in vivo. Il est démontré que la mesure d’un temps caractéristique en IRM, appelé « T1 », est corrélée à la composition du tissu. Justesse et reproductibilité sont requises dans la mesure du T1 pour : i) discriminer les valeurs de T1 des tissus sains et fibrosés dont la gamme de valeurs est assez restreinte, ii) permettre la mesure avant et après injection d’agent de contraste et iii) comparer les valeurs de T1 entre sites et constructeurs. A ce jour, aucune des techniques publiées n’est en mesure de fournir une mesure de T1 « idéale ». L’objectif principal de cette thèse est d’optimiser et de valider une technique de mesure du T1 sur le myocarde, qui se propose d’allier ces deux qualités. Pour atteindre cet objectif, nous avons travaillé la séquence appelée « SMART1Map » basée sur le principe d’échantillonnage d’une courbe de saturation-récupération. Des essais sur objets tests et sur volontaires à 1,5T et 3T ont d’abord été réalisés. Bien que les valeurs moyennes de T1 mesurées chez 7 sujets étaient justes et correspondaient à la littérature (1150 ± 84 ms à 1,5T), les résultats ont montré une faible reproductibilité imputable en partie à un manque de robustesse de la séquence vis-à-vis des inhomogénéités de champ magnétique particulièrement importantes à 3T. L’optimisation (simulation, implémentation et tests) de l’impulsion radiofréquence de saturation constitutive de la séquence a été mise en œuvre à 3T, sur objets fantômes, puis sur volontaires sains. Ces travaux ouvrent la voie à la mise en place de mesure de biomarqueur IRM de la fibrose / Cardiac Magnetic Resonance Imaging (MRI) has experienced growing interest due to its great potential in myocardial tissue characterization. Myocardium T1 values can be considered a useful imaging biomarker. Although many different T1 mapping techniques already exist, accurate and precise myocardial T1 quantification remains a desired yet challenging goal. Cardiac T1 mapping necessitates high precision to: i) discriminate values within the relatively short range of T1 values in healthy and diseased tissues, ii) allow both pre and post contrast agent injection T1 assessment, which is mandatory to compute the ECV and iii) allow comparison across platforms and hospitals. It should also provide a T1 value independent of heart rate. Among published methods, not any of them offer an “ideal” T1 quantification method. The main aim of this work is to optimize and to validate a precise and accurate quantitative T1 mapping technique. In order to achieve this goal, the sequence called « SMART1Map » based on the saturation recovery curve sampling was used. The first step consisted in performing T1 measurements on phantoms and healthy volunteers at 1,5T and 3T. Although this study allowed to assess accurate myocardium T1 values close to literature ones (1150 ± 84 ms), the sequence showed a poor precision likely due to a lack of robustness to magnetic field inhomogeneties and frequency offsets. Optimization (including simulation, implementation and tests) of the saturation RF pulse used in the sequence was carried out in phantoms then on healthy subjects at 3T. From this development, fibrosis detection through T1 measurements in clinical studies can now be started at 1.5T and 3T

L’Imagerie par résonance magnétique (IRM) est un outil fondamental pour l’exploration in vivo du développement du cerveau chez le fœtus, le bébé et l’enfant. Elle fournit plusieurs paramètres quantitatifs qui reflètent les changements des propriétés tissulaires au cours du développement en fonction de différents processus de maturation. Cependant, l’évaluation fiable de la maturation de la substance blanche est encore une question ouverte: d'une part, aucun de ces paramètres ne peut décrire toute la complexité des changements sous-jacents; d'autre part, aucun d'eux n’est spécifique d’un processus de développement ou d’une propriété tissulaire particulière. L’implémentation d’approches multiparamétriques combinant les informations complémentaires issues des différents paramètres IRM devrait permettre d’améliorer notre compréhension du développement du cerveau. Dans ce travail de thèse, je présente deux exemples de telles approches et montre leur pertinence pour l'étude de la maturation des faisceaux de substance blanche. La première approche fournit une mesure globale de la maturation basée sur la distance de Mahalanobis calculée à partir des différents paramètres IRM (temps de relaxation T1 et T2, diffusivités longitudinale et transverse du tenseur de diffusion DTI) chez des nourrissons (âgés de 3 à 21 semaines) et des adultes. Cette approche offre une meilleure description de l’asynchronisme de maturation à travers les différents faisceaux que les approches uniparamétriques. De plus, elle permet d'estimer les délais relatifs de maturation entre faisceaux. La seconde approche vise à quantifier la myélinisation des tissus cérébraux, en calculant la fraction de molécules d’eau liées à la myéline (MWF) en chaque voxel des images. Cette approche est basée sur un modèle tissulaire avec trois composantes ayant des caractéristiques de relaxation spécifiques, lesquelles ont été pré-calibrées sur trois jeunes adultes sains. Elle permet le calcul rapide des cartes MWF chez les nourrissons et semble bien révéler la progression de la myélinisation à l’échelle cérébrale. La robustesse de cette approche a également été étudiée en simulations. Une autre question cruciale pour l'étude du développement de la substance blanche est l'identification des faisceaux dans le cerveau des enfants. Dans ce travail de thèse, je décris également la création d'un atlas préliminaire de connectivité structurelle chez des enfants âgés de 17 à 81 mois, permettant l'extraction automatique des faisceaux à partir des données de tractographie. Cette approche a démontré sa pertinence pour l'évaluation régionale de la maturation de la substance blanche normale chez l’enfant. Pour finir, j’envisage dans la dernière partie du manuscrit les applications potentielles des différentes méthodes précédemment décrites pour l’étude fine des réseaux de substance blanche dans le cadre de deux exemples spécifiques de pathologies : les épilepsies focales et la leucodystrophie métachromatique. / Magnetic Resonance Imaging (MRI) is a fundamental tool for in vivo investigation of brain development in newborns, infants and children. It provides several quantitative parameters that reflect changes in tissue properties during development depending on different undergoing maturational processes. However, reliable evaluation of the white matter maturation is still an open question: on one side, none of these parameters can describe the whole complexity of the undergoing changes; on the other side, neither of them is specific to any particular developmental process or tissue property. Developing multiparametric approaches combining complementary information from different MRI parameters is expected to improve our understanding of brain development. In this PhD work, I present two examples of such approaches and demonstrate their relevancy for investigation of maturation across different white matter bundles. The first approach provides a global measure of maturation based on the Mahalanobis distance calculated from different MRI parameters (relaxation times T1 and T2, longitudinal and transverse diffusivities from Diffusion Tensor Imaging, DTI) in infants (3-21 weeks) and adults. This approach provides a better description of the asynchronous maturation across the bundles than univariate approaches. Furthermore, it allows estimating the relative maturational delays between the bundles. The second approach aims at quantifying myelination of brain tissues by calculating Myelin Water Fraction (MWF) in each image voxel. This approach is based on a 3-component tissue model, with each model component having specific relaxation characteristics that were pre-calibrated in three healthy adult subjects. This approach allows fast computing of the MWF maps from infant data and could reveal progression of the brain myelination. The robustness of this approach was further investigated using computer simulations. Another important issue for studying white matter development in children is bundles identification. In the last part of this work I also describe creation of a preliminary atlas of white matter structural connectivity in children aged 17-81 months. This atlas allows automatic extraction of the bundles from tractography datasets. This approach demonstrated its relevance for evaluation of regional maturation of normal white matter in children. Finally, in the last part of the manuscript I describe potential future applications of the previously developed methods to investigation of the white matter in cases of two specific pathologies: focal epilepsy and metachromatic leukodystrophy.

The side-effects of chemotherapy treatment are an increasingly important research focus as more cancer patients are reaching survivorship. While treatment allows for survival, it can also lead to problems which can significantly affect quality of life. Cognitive impairments after chemotherapy treatment are one such factor. First presented as anecdotal patient reports, over the last decade empirical evidence for this cognitive concern has been obtained. Much attention has been focused on post-chemotherapy research, yet little attention has been granted to these same patients’ cognition before treatment commences. Breast cancer (BC) patients face many obstacles before chemotherapy treatment such as: surgery and side-effects of anesthesia, increased cytokine activity, stress of a new disease diagnosis and upcoming challenges, and emotional burdens such as depression and anxiety. Many of these factors have independently been shown to affect cognitive abilities in both healthy populations as well as other patient groups. Therefore, the pre-treatment (or baseline) BC patient status warrants systematic study. This would then reduce mistakenly attributing carried-over cognitive deficits to side effects of chemotherapy. As well, it is possible that certain confounding variables may have neural manifestations at baseline that could be exacerbated by chemotherapy agents. The following thesis first presents a review paper which critically describes the current literature examining chemotherapy-related cognitive impairments (CRCIs), as well as possible confound variables affecting this population. Subsequently, three original research papers present pre-chemotherapy data showing significant neuroanatomical and neurofunctional differences in BC patients compared to controls. In particular, these neural differences are present in brain regions that have been reported in post-chemotherapy papers. This, as well as the effects of variables such as the number of days since surgery, depression and anxiety scores and more, support the initiative that research attention should increase focus on these patients at baseline in order to better understand their post-chemotherapy results.

The side-effects of chemotherapy treatment are an increasingly important research focus as more cancer patients are reaching survivorship. While treatment allows for survival, it can also lead to problems which can significantly affect quality of life. Cognitive impairments after chemotherapy treatment are one such factor. First presented as anecdotal patient reports, over the last decade empirical evidence for this cognitive concern has been obtained. Much attention has been focused on post-chemotherapy research, yet little attention has been granted to these same patients’ cognition before treatment commences. Breast cancer (BC) patients face many obstacles before chemotherapy treatment such as: surgery and side-effects of anesthesia, increased cytokine activity, stress of a new disease diagnosis and upcoming challenges, and emotional burdens such as depression and anxiety. Many of these factors have independently been shown to affect cognitive abilities in both healthy populations as well as other patient groups. Therefore, the pre-treatment (or baseline) BC patient status warrants systematic study. This would then reduce mistakenly attributing carried-over cognitive deficits to side effects of chemotherapy. As well, it is possible that certain confounding variables may have neural manifestations at baseline that could be exacerbated by chemotherapy agents. The following thesis first presents a review paper which critically describes the current literature examining chemotherapy-related cognitive impairments (CRCIs), as well as possible confound variables affecting this population. Subsequently, three original research papers present pre-chemotherapy data showing significant neuroanatomical and neurofunctional differences in BC patients compared to controls. In particular, these neural differences are present in brain regions that have been reported in post-chemotherapy papers. This, as well as the effects of variables such as the number of days since surgery, depression and anxiety scores and more, support the initiative that research attention should increase focus on these patients at baseline in order to better understand their post-chemotherapy results.

L’Imagerie par résonance magnétique (IRM) est un outil fondamental pour l’exploration in vivo du développement du cerveau chez le fœtus, le bébé et l’enfant. Elle fournit plusieurs paramètres quantitatifs qui reflètent les changements des propriétés tissulaires au cours du développement en fonction de différents processus de maturation. Cependant, l’évaluation fiable de la maturation de la substance blanche est encore une question ouverte: d'une part, aucun de ces paramètres ne peut décrire toute la complexité des changements sous-jacents; d'autre part, aucun d'eux n’est spécifique d’un processus de développement ou d’une propriété tissulaire particulière. L’implémentation d’approches multiparamétriques combinant les informations complémentaires issues des différents paramètres IRM devrait permettre d’améliorer notre compréhension du développement du cerveau. Dans ce travail de thèse, je présente deux exemples de telles approches et montre leur pertinence pour l'étude de la maturation des faisceaux de substance blanche. La première approche fournit une mesure globale de la maturation basée sur la distance de Mahalanobis calculée à partir des différents paramètres IRM (temps de relaxation T1 et T2, diffusivités longitudinale et transverse du tenseur de diffusion DTI) chez des nourrissons (âgés de 3 à 21 semaines) et des adultes. Cette approche offre une meilleure description de l’asynchronisme de maturation à travers les différents faisceaux que les approches uniparamétriques. De plus, elle permet d'estimer les délais relatifs de maturation entre faisceaux. La seconde approche vise à quantifier la myélinisation des tissus cérébraux, en calculant la fraction de molécules d’eau liées à la myéline (MWF) en chaque voxel des images. Cette approche est basée sur un modèle tissulaire avec trois composantes ayant des caractéristiques de relaxation spécifiques, lesquelles ont été pré-calibrées sur trois jeunes adultes sains. Elle permet le calcul rapide des cartes MWF chez les nourrissons et semble bien révéler la progression de la myélinisation à l’échelle cérébrale. La robustesse de cette approche a également été étudiée en simulations. Une autre question cruciale pour l'étude du développement de la substance blanche est l'identification des faisceaux dans le cerveau des enfants. Dans ce travail de thèse, je décris également la création d'un atlas préliminaire de connectivité structurelle chez des enfants âgés de 17 à 81 mois, permettant l'extraction automatique des faisceaux à partir des données de tractographie. Cette approche a démontré sa pertinence pour l'évaluation régionale de la maturation de la substance blanche normale chez l’enfant. Pour finir, j’envisage dans la dernière partie du manuscrit les applications potentielles des différentes méthodes précédemment décrites pour l’étude fine des réseaux de substance blanche dans le cadre de deux exemples spécifiques de pathologies : les épilepsies focales et la leucodystrophie métachromatique. / Magnetic Resonance Imaging (MRI) is a fundamental tool for in vivo investigation of brain development in newborns, infants and children. It provides several quantitative parameters that reflect changes in tissue properties during development depending on different undergoing maturational processes. However, reliable evaluation of the white matter maturation is still an open question: on one side, none of these parameters can describe the whole complexity of the undergoing changes; on the other side, neither of them is specific to any particular developmental process or tissue property. Developing multiparametric approaches combining complementary information from different MRI parameters is expected to improve our understanding of brain development. In this PhD work, I present two examples of such approaches and demonstrate their relevancy for investigation of maturation across different white matter bundles. The first approach provides a global measure of maturation based on the Mahalanobis distance calculated from different MRI parameters (relaxation times T1 and T2, longitudinal and transverse diffusivities from Diffusion Tensor Imaging, DTI) in infants (3-21 weeks) and adults. This approach provides a better description of the asynchronous maturation across the bundles than univariate approaches. Furthermore, it allows estimating the relative maturational delays between the bundles. The second approach aims at quantifying myelination of brain tissues by calculating Myelin Water Fraction (MWF) in each image voxel. This approach is based on a 3-component tissue model, with each model component having specific relaxation characteristics that were pre-calibrated in three healthy adult subjects. This approach allows fast computing of the MWF maps from infant data and could reveal progression of the brain myelination. The robustness of this approach was further investigated using computer simulations. Another important issue for studying white matter development in children is bundles identification. In the last part of this work I also describe creation of a preliminary atlas of white matter structural connectivity in children aged 17-81 months. This atlas allows automatic extraction of the bundles from tractography datasets. This approach demonstrated its relevance for evaluation of regional maturation of normal white matter in children. Finally, in the last part of the manuscript I describe potential future applications of the previously developed methods to investigation of the white matter in cases of two specific pathologies: focal epilepsy and metachromatic leukodystrophy.

Μαγνητικά νανοσωματίδια οξειδίων του σιδήρου παρασκευάσθηκαν μέσω της αλκαλικής συμπύκνωσης και ελεγχόμενης καταβύθισης συμπλόκων ιόντων FeII, υπό την παρουσία τυχαίου συμπολυμερούς PAA-co-MA. Οι παράμετροι της σύνθεσης μεταβλήθηκαν με σκοπό την απομόνωση προϊόντων που να εμφανίζουν τις καλύτερες μαγνητικές ιδιότητες. Όλα τα προϊόντα εμφάνισαν υψηλή κολλοειδή σταθερότητα σε υδατικά μέσα χαμηλής ιοντικής ισχύος, ενώ ο σιδηρομαγνητικός τους χαρακτήρας έδειξε να ποικίλει από ασθενής μέχρι αρκετά ισχυρός, όπως προέκυψε μετά τον χαρακτηρισμό τους με μαγνητοφόρηση και μαγνητική υπερθερμία με εναλλασόμενο μαγνητικό πεδίο. Το μέσο μέγεθος των νανοκρυσταλλιτών ήταν διαφορετικό σε κάθε προϊόν κυμαινόμενο από περίπου 3 έως 14 nm, όπως προσδιορίστηκε μέσω XRD. Η ανάλυση με ΤΕΜ έδειξε ότι στο προϊόν που εμφανίζει τις καλύτερες μαγνητικές ιδιότητες σχηματίζονται πλειάδες νανοσωματιδίων πυκνής διάταξης, και στις οποίες αποδίδεται η βελτιωμένη απόκριση σε μαγνητικά πεδία. Τα άλλα προϊόντα εμφάνισαν μικρότερα μεγέθη κρυσταλλιτών και διαφορετικά δομικά χαρακτηριστικά. Τα κολλοειδή καταβυθίζονταν κατόπιν αύξησης της ιοντικής ισχύος του διαλύτη. Για τον λόγο αυτό αποφασίστηκε η μελέτη της αντίδρασης σύζευξης των εξωτερικών καρβοξυλικών ομάδων του πολυμερικού φλοιού με mPEG-NH2, δεδομένου ότι η PEG αυξάνει σημαντικά τη σταθερότητα των κολλοειδών. Παρά το γεγονός ότι χρησιμοποιήθηκαν κοινά αντιδραστήρια σύζευξης, μόνο υπό πολύ ειδικές συνθήκες η απόδοση της αντίδρασης ήταν ικανοποιητική, οπότε και προέκυψαν σταθερά κολλοειδή σε συνθήκες υψηλής ιοντικής ισχύος. Τέλος, τα προϊόντα αξιολογήθηκαν για την ικανότητά τους να επάγουν υπερθερμία και μελετήθηκε ο χρόνος χαλάρωσης Τ2, ο οποίος σχετίζεται άμεσα με την ενίσχυση της αντίθεσης στην απεικόνιση μέσω μαγνητικού συντονισμού. Τέλος, ένα από τα προϊόντα, μελετήθηκε in vitro και in νίνο, προκειμένου να αξιολογηθεί η βιοσυμβατότητα του. Τα συστήματα αυτά παρουσιάζουν πολύ ενδιαφέρουσες ιδιότητες ώστε να τροποποιηθούν και να μελετηθούν περεταίρω ως θεραπευτικά ή/και διαγνωστικά νανοϋλικά. / Μagnetic nanoparticles of iron oxides were synthesized through condensation and controlled precipitation of a FeII complex, in alkaline environment, in the presence of a random copolymer PAA-co-MA, as polymeric corona. The synthetic parameters were varied with the aim of isolating products exhibiting the best magnetic properties. All products displayed high colloidal stability in low ionic strength aqueous media, while their ferromagnetic properties varied from weak to quite strong, as deduced after the characterization with magnetophoresis and magnetic hyperthermia with alternating magnetic field. The average crystallite size, as determined through XRD, varied from 8 to 14 nm depending on the product. TEM analysis showed that the product displaying the best magnetic properties formed clusters of densely packed nanocrystallites, leading to interesting superstructural motifs. All the other products displayed smaller crystallite sizes and different structural characteristics. The colloids precipitated upon increase of the ionic strength of the solvent (H2O) with NaCl. Therefore, it was decided to study the conjugation of the outer carboxyl groups of the polymeric corona with mPEG-NH2, since PEG is known to increase significantly the stability of colloids. Despite the fact that common conjugation reagents were used, only under specific conditions the yied of the reaction was appropriately high in order the resultant colloids to be stable in a high ionic strength (isotonic) medium. Finally the products were evaluated for their performance in magnetic hyperthermia and for contrast enhancement in magnetic resonance imaging, by studying the T2 relaxation time. One of the products was furthermore studied by in vitro and in vivo systems, in order to evaluate its biocompatibility. These colloidal systems exhibit very interesting properties in order to be further modified and studied as therapeutic and / or diagnostic (theragnostic) nanomaterials.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

The side-effects of chemotherapy treatment are an increasingly important research focus as more cancer patients are reaching survivorship. While treatment allows for survival, it can also lead to problems which can significantly affect quality of life. Cognitive impairments after chemotherapy treatment are one such factor. First presented as anecdotal patient reports, over the last decade empirical evidence for this cognitive concern has been obtained. Much attention has been focused on post-chemotherapy research, yet little attention has been granted to these same patients’ cognition before treatment commences. Breast cancer (BC) patients face many obstacles before chemotherapy treatment such as: surgery and side-effects of anesthesia, increased cytokine activity, stress of a new disease diagnosis and upcoming challenges, and emotional burdens such as depression and anxiety. Many of these factors have independently been shown to affect cognitive abilities in both healthy populations as well as other patient groups. Therefore, the pre-treatment (or baseline) BC patient status warrants systematic study. This would then reduce mistakenly attributing carried-over cognitive deficits to side effects of chemotherapy. As well, it is possible that certain confounding variables may have neural manifestations at baseline that could be exacerbated by chemotherapy agents. The following thesis first presents a review paper which critically describes the current literature examining chemotherapy-related cognitive impairments (CRCIs), as well as possible confound variables affecting this population. Subsequently, three original research papers present pre-chemotherapy data showing significant neuroanatomical and neurofunctional differences in BC patients compared to controls. In particular, these neural differences are present in brain regions that have been reported in post-chemotherapy papers. This, as well as the effects of variables such as the number of days since surgery, depression and anxiety scores and more, support the initiative that research attention should increase focus on these patients at baseline in order to better understand their post-chemotherapy results.

Biomedical optical imaging is capable of providing functional information of the soft bi-ological tissues, whose applications include imaging large tissues, such breastand brain in-vivo. Biomedical optical imaging uses near infrared light (600nm-900nm) as the probing media, givin ganaddedadvantageofbeingnon-ionizingimagingmodality. The tomographic technologies for imaging large tissues encompasses diffuse optical tomogra-phyandphotoacoustictomography. Traditional image reconstruction methods indiffuse optical tomographyemploysa �2-norm based regularization, which is known to remove high frequency no is either econstructed images and make the mappearsmooth. Hence as parsity based image reconstruction has been deployed for diffuse optical tomography, these sparserecov-ery methods utilize the �p-norm based regularization in the estimation problem with 0≤ p<1. These sparse recovery methods, along with an approximation to utilizethe �0-norm, have been used forther econstruction of diffus eopticaltomographic images.The comparison of these methods was performed by increasing the sparsityinthesolu-tion. Further a model resolution matrix based framework was proposed and shown to in-duceblurinthe�2-norm based regularization framework for diffuse optical tomography. This model-resolution matrix framework was utilized in the optical imaged econvolution framework. A basis pursuitdeconvolution based on Split AugmentedLagrangianShrink-ageAlgorithm(SALSA)algorithm was used along with the Tikhonovregularization step making the image reconstruction into a two-step procedure. This new two-step approach was found to be robust with no iseandwasabletobetterdelineatethestructureswhichwasevaluatedusingnumericalandgelatinphantom experiments. Modern diffuse optical imaging systems are multi-modalin nature, where diffuse optical imaging is combined with traditional imaging modalitiessuc has Magnetic Res-onanceImaging(MRI),or Computed Tomography(CT). Image-guided diffuse optical tomography has the advantage of reducingthetota lnumber of optical parameters beingreconstructedtothenumber of distinct tissue types identified by the traditional imaging modality, converting the optical image-reconstruction problem fromunder-determined innaturetoover-determined. In such cases, the minimum required measurements might be farless compared to those of the traditional diffuse optical imaging. An approach to choose these measurements optimally based on a data-resolution matrix is proposed, and it is shown that it drastically reduces the minimum required measurements (typicalcaseof240to6) without compromising the image reconstruction performance. In the last part of the work , a model-based image reconstruction approaches in pho-toacoustic tomography (which combines light and ultra sound) arestudied as it is know that these methods have a distinct advantage compared to traditionalanalytical methods in limited datacase. These model-based methods deployTikhonovbasedregularizationschemetoreconstruct the initial pressure from the boundary acoustic data. Again a model-resolution for these cases tend to represent the blurinduced by the regularization scheme. A method that utilizes this blurringmodelandper forms the basis pursuit econ-volution to improve the quantitative accuracy of the reconstructed photoacoustic image is proposed and shown to be superior compared to other traditional methods. Moreover, this deconvolution including the building of model-resolution matrixis achievedvia the Lanczosbidiagonalization (least-squares QR) making this approach computationally ef-ficient and deployable inreal-time. Keywords Medical imaging, biomedical optical imaging, diffuse optical tomography, photoacous-tictomography, multi-modalimaging, inverse problems,sparse recovery,computational methods inbiomedical optical imaging.