Rozprawy doktorskie na temat „Biomedical labeling”

In eukaryotic cells, some mRNAs localize to distinct areas of the cell where RNA is translated and the encoded protein is specifically localized. Recent studies have suggested that even though prokaryotic cells lack internal compartmentalization, different RNAs can localize to distinct regions of the bacterial cell. Our lab is developing methods for labeling and detecting RNA with the goal of determining localization of endogenous RNAs within single cells. We currently employ an eIF4a protein-specific aptamer for RNA labeling using one of two methods. (1) Target RNA is tagged with the aptamer sequence at the 3' end and the aptamer triggers protein complementation of two fusion proteins, each containing split EGFP and split eIF4A proteins. (2) Two RNA probes, each containing a half of a split eIF4a-specific aptamer and an antisense sequence complementary to the target RNA, bind the unmodified transcript through complementary interactions. This binding brings the two fragments of the split aptamer in close proximity and allows proper folding of a split aptamer. A fluorescent signal is generated by the aptamer-driven reassociation of the fusion proteins. In this work, we investigate the sensitivity of the first method for detecting transcripts expressed from their natural chromosomal loci, and describe attempts to increase the sensitivity of the method by using multiple aptamer tagging. We also present results suggesting that the second method, combining protein complementation and split aptamer approach, provides high sensitivity enabling detection of endogenous bacterial RNAs expressed at low level.

The human cerebral cortex is a highly foliated structure that supports the complex cognitive abilities of humans. The cortex is divided by its cytoarchitectural characteristics that can be approximated by the folding pattern of the cortex. Psychiatric and neurological diseases, such as Huntington's disease or schizophrenias, are often related with structural changes in the cerebral cortex. Detecting structural changes in different regions of cerebral cortex can provide insight into disease biology, progression and response to treatment. The delineation of anatomical regions on the cerebral cortex is time intensive if performed manually, therefore automated methods are needed to perform this delineation. Magnetic Resonance Imaging (MRI) is commonly used to explore the structural change in patients with psychiatric and neurological diseases. This dissertation proposes a fast and reliable method to automatically parcellate the cortical surface generated from MR images. A fully automated pipeline has been built to process MR images and generate cortical surfaces associated with parcellation labels. First, genus zero cortical surfaces for each hemisphere of a subject are generated from MR images. The surface is generated at the parametric boundary between gray matter and white matter. Geometry features are calculated for each cortical surface to as scalar values to drive a multi-resolution spherical registration that can align two cortical surfaces together in the spherical domain. Then, the labels on a subject's cortical surface are evaluated by registering a subject's cortical surface with a population atlas and combining the information of prior probabilities on the atlas with the subject's geometry features. The automated parcellation has been tested on a group of subjects with various cerebral cortex structures. It shows that the proposed method is fast (takes about 3 hours to parcellate at one hemisphere) and accurate (with the weighted average Dice ~0.86). The framework of this dissertation will be as follows: the first chapter is about the introduction, including motivation, background, and significance of the study. The second chapter describes the whole pipeline of the automated surface parcellation and focuses on technical details of every method used in the pipeline. The third chapter presents results achieved in this study and the fourth chapter discusses the results and draws a conclusion.

The high prevalence and mortality of cerebrovascular disease has led to the development of several methods to measure cerebral blood flow (CBF) in vivo. One of these, arterial spin labeling (ASL), is a quantitative magnetic resonance imaging (MRI) technique with the advantage that it is completely non-invasive. The quantification of CBF using ASL requires correction for a tissue specific parameter called the brain-blood partition coefficient (BBPC). Despite regional and inter-subject variability in BBPC, the current recommended implementation of ASL uses a constant assumed value of 0.9 mL/g for all regions of the brain, all subjects, and even all species. The purpose of this dissertation is 1) to apply ASL to a novel population to answer an important clinical question in the setting of Down syndrome, 2) to demonstrate proof of concept of a rapid technique to measure BBPC in mice to improve CBF quantification, and 3) to translate the correction method by applying it to a population of healthy canines using equipment and parameters suitable for use with humans. Chapter 2 reports the results of an ASL study of adults with Down syndrome (DS). This population is unique for their extremely high prevalence of Alzheimer’s disease (AD) and very low prevalence of systemic cardiovascular risk factors like atherosclerosis and hypertension. This prompted the hypothesis that AD pathology would lead to the development of perfusion deficits in people with DS despite their healthy cardiovascular profile. The results demonstrate that perfusion is not compromised in DS participants until the middle of the 6th decade of life after which measured global CBF was reduced by 31% (p=0.029). There was also significantly higher prevalence of residual arterial signal in older participants with DS (60%) than younger DS participants (7%, p = 0.005) or non-DS controls (0%, p < 0.001). This delayed pattern of perfusion deficits in people with DS differs from observations in studies of sporadic AD suggesting that adults with DS benefit from an improved cardiovascular risk profile early in life. Chapter 3 introduces calibrated short TR recovery (CaSTRR) imaging as a rapid method to measure BBPC and its development in mice. This was prompted by the inability to account for potential changes in BBPC due to age, brain atrophy, or the accumulation of hydrophobic A-β plaques in the ASL study of people with DS in Chapter 2. The CaSTRR method reduces acquisition time of BBPC maps by 87% and measures a significantly higher BBPC in cortical gray matter (0.99±0.04 mL/g,) than white matter in the corpus callosum (0.93±0.05 mL/g, p=0.03). Furthermore, when CBF maps are corrected for BBPC, the contrast between gray and white matter regions of interest is improved by 14%. This demonstrates proof of concept for the CaSTRR technique. Chapter 4 describes the application of CaSTRR on healthy canines (age 5-8 years) using a 3T human MRI scanner. This represents a translation of the technique to a setting suitable for use with a human subject. Both CaSTRR and pCASL acquisitions were performed and further optimization brought the acquisition time of CaSTRR down to 4 minutes which is comparable to pCASL. Results again show higher BBPC in gray matter (0.83 ± 0.05 mL/g) than white matter (0.78 ± 0.04 mL/g, p = 0.007) with both values unaffected by age over the range studied. Also, gray matter CBF is negatively correlated with age (p = 0.003) and BBPC correction improved the contrast to noise ratio by 3.6% (95% confidence interval = 0.6 – 6.5%). In summary, the quantification of ASL can be improved using BBPC maps derived from the novel, rapid CaSTRR technique.

Ischaemic stroke is a major cause of death and disability worldwide. Cerebral autoregulation, which can be impaired during acute stroke, and collateral flow to brain tissue through the circle of Willis, both play a role in preventing tissue infarction. The configuration of the arterial circle varies between individuals. Thus, personalised modelling of the cerebral arterial network, to determine the potential for collateral flow, can be of significant value in the clinical context of stroke. The interaction between autoregulation and collateral flow remains poorly understood. In this study, steady-state physiological models of the cerebral arterial network, including several common variants of the circle of Willis, were coupled to a spatially variable mathematical representation of cerebral autoregulation. The resulting model was used to simulate various arterial occlusions, as well as bilateral and unilateral impairment of autoregulation, in each structural variant. The work identified few circle of Willis variants that present either particularly high-risk or particularly low-risk of cerebral ischaemia. Instead it was found that most variants are dependent upon the bilateral function of autoregulation to facilitate collateral flow and preserve cerebral blood flows. When autoregulation was impaired unilaterally, downstream of an occlusion, blood flows in the contralateral hemisphere were preserved at the expense of the ipsilateral tissue at risk. Arterial network models have in the past been personalised using structural, rather than functional, angiography measurements. This thesis presents a novel model-based method for absolute blood volume flow rate quantification in short arterial segments using dynamic magnetic resonance angiography data. The work also investigated the additional information that can be obtained from such functional angiography. The flow quantification technique was found to accurately estimate flows in shorter arterial segments than an existing technique. However, improvements to noise performance, and strategies for rejection of contaminating signals from overlapping vessels within the imaging plane, are required before the technique can be applied to personalised cerebral arterial network modelling.

Collateral blood flow is the compensatory flow of blood to the tissue through secondary channels when the primary channel is compromised. It is of vital importance in cerebrovascular disease where collateral flow can maintain large regions of brain tissue which would otherwise have suffered ischaemic damage. Traditional x-ray based techniques for visualising collateral flow are invasive and carry risks to the patient. In this thesis novel magnetic resonance imaging techniques for performing vessel-selective labelling of brain feeding arteries are explored and developed to reveal the source and extent of collateral flow in the brain non-invasively and without the use of contrast agents. Vessel-encoded pseudo-continuous arterial spin labelling (VEPCASL) allows the selective labelling of blood water in different combinations of brain feeding arteries that can be combined in post-processing to yield vascular territory maps. The mechanism of VEPCASL was elucidated and optimised through simulations of the Bloch equations and phantom experiments, including its sensitivity to sequence parameters, blood velocity and off-resonance effects. An implementation of the VEPCASL pulse sequence using an echo-planar imaging (EPI) readout was applied in healthy volunteers to enable optimisation of the post-labelling delay and choice of labelling plane position. Improvements to the signal-to-noise ratio (SNR) and motion-sensitivity were made through the addition of background suppression pulses and a partial-Fourier scheme. Experiments using a three-dimensional gradient and spin echo (3D-GRASE) readout were somewhat compromised by significant blurring in the slice direction, but showed potential for future work with a high SNR and reduced dropout artefacts. The VEPCASL preparation was also applied to a dynamic 2D angiographic readout, allowing direct visualisation of collateral blood flow in the brain as well as a morphological and functional assessment of the major cerebral arteries. The application of a balanced steady-state free precession (bSSFP) readout significantly increased the acquisition efficiency, allowing the generation of dynamic 3D vessel-selective angiograms. A theoretical model of the dynamic angiographic signal was also derived, allowing quantification of blood flow through specified vessels, providing a significant advantage over qualitative x-ray based methods. Finally, these methods were applied to a number of patient groups, including those with vertebro-basilar disease, carotid stenosis and arteriovenous malformation. These preliminary studies demonstrate that useful clinical information regarding collateral blood flow can be obtained with these techniques.

碩士
國立嘉義大學
應用化學系研究所
106
In recent years, hyperbranched polymers without classic chromophores, such as aromatic structure or conjugated main chain, have attracted increasing attention due to strong fluorescence emission in aqueous solution under appropriate conditions. Herein, we would adopt AB2 and A2 + B3 type one-pot strategies to synthesize nonconventional fluorescent hyperbranched polymers with different terminal functional groups as NH2 and COOH, respectively. In order to distinguish from our previous study (Polymer 2013, 54, 623.), we synthesized new AB2-type monomer with vinyl structure incorporation as AB2 II, that the A end point was an amino group, and the B end point was a carboxylic acid functional group in this study. Through the one-pot polymerization of AB2 II monomers, we could obtain internal rich amide bonds, tertiary amines and water-soluble hyperbranched polymers II (abbreviation as HBP II) with large number of carboxylic acids on the periphery. Moreover, the A2 + B3 strategy was used commercially available chemicals, ethylenediaminetetraacetic dianhydride (abbreviation as EDTAD) and jeffamine® T-403 polyetheramine (abbreviation as T403), as the starting material to synthesize hyperbranched poly(amic acid) (abbreviaiotn as HBPAA) with amine-terminal functional groups in one pot. Dendritic polymer have received extensive interest due to their unique properties such as globular three-dimensional structures, cavernous interior, and large number of peripheral functionalities. It is worth to note that our hyperbranched polymers HBP II and HBPAA had nonconventional fluorescence behavior, and its fluorescence intensity could be adjusted by the pH values of solution. The fluorescence intensity of HBP II in neutral and weakly alkaline aqueous solutions was higher than that of acidic solutions; whereas for HBPAA, the fluorescence intensity in acidic aqueous solutions was higher than that of neutral and alkaline solution. Their quantum yields could reach 13.5% (Em: 460 nm, HBP II) and 18.3% (Em: 430 nm, HBPAA), respectively. The nonconventional fluorescent hyperbranched polymers in this study had the characteristics of facile preparation, high water solubility, and a large number of peripheral functional groups that can be further modified. Combining with its strong fluorescence behavior, it will have considerable potential in bioimaging and drug labeling carriers.

We live in a world where data surround us in every aspect of our lives. The key challenge for humans and machines is how we can make better use of such data. Imagine what would happen if you were to have intelligent machines that could give you insight into the data. Insight that will enable you to better 1) reason about, 2) learn, and 3) understand the underlying phenomena that produced the data. The possibilities of combined human-machine intelligence are endless and will impact our lives in ways we can not even imagine today. Synergistic human-machine intelligence aims to facilitate the analytical reasoning and inference process of humans by creating machines that maximize a human's ability to 1) reason about, 2) learn, and 3) understand large, complex, and heterogeneous data. Combined human-machine intelligence is a powerful symbiosis of mutual benefit, in which we depend on the computational capabilities of the machine for the tasks we are not good at, and the machine requires human intervention for the tasks it performs poorly on. This relationship provides a compelling alternative to either approach in isolation for solving today's and tomorrow's arising data challenges. In his regard, this dissertation proposes a diverse analytical framework that leverages synergistic human-machine intelligence to maximize a human's ability to better 1) reason about, 2) learn, and 3) understand different biomedical imaging and healthcare data present in the patient's electronic health record (EHR). Correspondingly, we approach the data analyses problem from the 1) visualization, 2) labeling, and 3) mining perspective and demonstrate the efficacy of our analytics on specific application scenarios and various data domains. In the first part of this dissertation we explore the question how we can build intelligent imaging analytics that are commensurate with human capabilities and constraints, specifically for optimizing data visualization and automated labeling workflows. Our journey starts with heuristic rule-based analytical models that are derived from task-specific human knowledge. From this experience, we move on to data-driven analytics, where we adapt and combine the intelligence of the model based on prior information provided by the human and synthetic knowledge learned from partial data observations. Within this realm, we propose a novel Bayesian transductive Markov random field model that requires minimal human intervention and is able to cope with scarce label information to learn and infer object shapes in complex spatial, multimodal, spatio-temporal, and longitudinal data. We then study the question how machines can learn discriminative object representations from dense human provided label information by investigating learning and inference mechanisms that make use of deep learning architectures. The developed analytics can aid visualization and labeling tasks, which enables the interpretation and quantification of clinically relevant image information. The second part explores the question how we can build data-driven analytics for exploratory analysis in longitudinal event data that are commensurate with human capabilities and constraints. We propose human-intuitive analytics that enable the representation and discovery of interpretable event patterns to ease knowledge absorption and comprehension of the employed analytics model and the underlying data. We propose a novel doubly-constrained convolutional sparse-coding framework that learns interpretable and shift-invariant latent temporal event patterns. We apply the model to mine complex event data in EHRs. By mapping the event space to heterogeneous patient encounters in the EHR we explore the linkage between healthcare resource utilization (HRU) in relation to disease severity. This linkage may help to better understand how disease specific co-morbidities and their clinical attributes incur different HRU patterns. Such insight helps to characterize the patient's care history, which then enables the comparison against clinical practice guidelines, the discovery of prevailing practices based on common HRU group patterns, and the identification of outliers that might indicate poor patient management.

abstract: Modern medical conditions, including cancer, traumatic brain injury, and cardiovascular disease, have elicited the need for cell therapies. The ability to non-invasively track cells in vivo in order to evaluate these therapies and explore cell dynamics is necessary. Magnetic Resonance Imaging provides a platform to track cells as a non-invasive modality with superior resolution and soft tissue contrast. A new methodology for cellular labeling and imaging uses Nile Red doped hexamethyldisiloxane (HMDSO) nanoemulsions as dual modality (Magnetic Resonance Imaging/Fluorescence), dual-functional (oximetry/ detection) nanoprobes. While Gadolinium chelates and super paramagnetic iron oxide-based particles have historically provided contrast enhancement in MRI, newer agents offer additional advantages. A technique using 1H MRI in conjunction with an oxygen reporter molecule is one tool capable of providing these benefits, and can be used in neural progenitor cell and cancer cell studies. Proton Imaging of Siloxanes to Map Tissue Oxygenation Levels (PISTOL) provides the ability to track the polydimethylsiloxane (PDMS) labeled cells utilizing the duality of the nanoemulsions. 1H MRI based labeling of neural stem cells and cancer cells was successfully demonstrated. Additionally, fluorescence labeling of the nanoprobes provided validation of the MRI data and could prove useful for quick in vivo verification and ex vivo validation for future studies.
Dissertation/Thesis
Masters Thesis Bioengineering 2014

Current techniques for nucleic acid analysis often involve extensive sample preparation that requires skilled personnel and multiple purification steps. In this dissertation, we introduce an on-chip, isothermal, post-hybridization labeling and signal amplification technique that can directly interrogate unmodified DNA and RNA samples on a microarray format, eliminating the need for microarray sample pre-processing.

We name this technique Surface Initiated Enzymatic Polymerization (SIEP), where we exploit the ability of a template independent DNA polymerase called Terminal Deoxynucleotidyl Transferase (TdT) to catalyze the formation of long single-stranded DNA (ssDNA) chain from the 3'-end of a short DNA primer, which is tethered on the surface, and TdT's ability to incorporate unnatural reporter nucleotides, such as fluorescent nucleotides. We hypothesize that polymerization of a long ssDNA chain while incorporating multiple fluorescent nucleotides on target DNA or RNA hybridized to probe printed on a surface will provide a simple and powerful, isothermal method for on-chip labeling and signal amplification.

We developed the SIEP methodology by first characterizing TdT biochemical reaction to polymerize long homopolymer ssDNA (> 1000 bases) starting from the 3'-OH of ten bases oligonucleotides. We found that the preferred monomers (deoxynucleotide, dNTP) are dATP and dTTP, and that the length of the ssDNA extension is determined by the ratio of input monomer (dNTP) to initiator (short oligonucleotides). We also investigated TdT's ability to incorporate fluorescent dNTPs into a ssDNA chain by examining the effect of the molar ratios of fluorescent dNTP to natural dNTP on the initiation efficiency, the degree of fluorophore incorporation, the length and the polydispersity of the polymerized DNA strand. These experiments allowed us to incorporate up to ~50 fluorescent Cy3-labeled dNTPs per kilobase into a ssDNA chain. With the goal of using SIEP as an on-chip labeling method, we also quantified TdT mediated signal amplification on the surface by immobilizing ssDNA oligonucleotide initiators on a glass surface followed by SIEP of DNA. The incorporation of multiple fluorophores into the extended DNA chain by SIEP translated to a up to ~45 fold increase in signal amplification compared to the incorporation of a single fluorophore.

SIEP was then employed to detect hybridization of DNA (25 bases), short miRNA (21 bases) and long mRNA (1400 bases) by the post-hybridization, on-chip polymerization of fluorescently labeled ssDNA that was grown from the 3'-OH of hybridized target strands. A dose-response curve for detection of DNA hybridization by SIEP was generated, with a ~1 pM limit of detection (LOD) and a 2-log linear dynamic range while the detection of short miRNA and fragmented mRNA targets resulted in ~2 pM and ~10 pM LOD, respectively with a 3-log linear dynamic range.

We further developed SIEP for colorimetric detection by exploiting the presence of negatively charged phosphate backbone on the surface as target DNA or RNA hybridizes on the immobilized probe. The net negative charge on the surface is further increased by TdT catalyzed polymerization of long ssDNA. We then used positively charged gold nanoparticles as reporters, which can be further amplified through electroless metallization, creating DNA spots that are visible by eye. We observed an increase of 100 fold in LOD due to SIEP amplification.

Overall, we demonstrated the use of SIEP methodology to label unmodified target DNA and RNA on chip, which can be detected through fluorescence signal or colorimetric signal of metallized DNA spots. This methodology is straightforward and versatile, is compatible with current microarray technology, and can be implemented using commercially available reagents.

Dissertation

Le dioxyde de carbone (CO2) est un résidu naturel du métabolisme cellulaire, la troisième substance la plus abondante du sang, et un important agent vasoactif. À la moindre variation de la teneur en CO2 du sang, la résistance du système vasculaire cérébral et la perfusion tissulaire cérébrale subissent des changements globaux. Bien que les mécanismes exacts qui sous-tendent cet effet restent à être élucidés, le phénomène a été largement exploité dans les études de réactivité vasculaire cérébrale (RVC). Une voie prometteuse pour l’évaluation de la fonction vasculaire cérébrale est la cartographie de la RVC de manière non-invasive grâce à l’utilisation de l’Imagerie par Résonance Magnétique fonctionnelle (IRMf). Des mesures quantitatives et non-invasives de de la RVC peuvent être obtenus avec l’utilisation de différentes techniques telles que la manipu- lation du contenu artériel en CO2 (PaCO2) combinée à la technique de marquage de spin artériel (Arterial Spin Labeling, ASL), qui permet de mesurer les changements de la perfusion cérébrale provoqués par les stimuli vasculaires. Toutefois, les préoccupations liées à la sensibilité et la fiabilité des mesures de la RVC limitent de nos jours l’adoption plus large de ces méthodes modernes de IRMf. J’ai considéré qu’une analyse approfondie ainsi que l’amélioration des méthodes disponibles pourraient apporter une contribution précieuse dans le domaine du génie biomédical, de même qu’aider à faire progresser le développement de nouveaux outils d’imagerie de diagnostique. Dans cette thèse je présente une série d’études où j’examine l’impact des méthodes alternatives de stimulation/imagerie vasculaire sur les mesures de la RVC et les moyens d’améliorer la sensibilité et la fiabilité de telles méthodes. J’ai aussi inclus dans cette thèse un manuscrit théorique où j’examine la possible contribution d’un facteur méconnu dans le phénomène de la RVC : les variations de la pression osmotique du sang induites par les produits de la dissolution du CO2. Outre l’introduction générale (Chapitre 1) et les conclusions (Chapitre 6), cette thèse comporte 4 autres chapitres, au long des quels cinq différentes études sont présentées sous forme d’articles scientifiques qui ont été acceptés à des fins de publication dans différentes revues scientifiques. Chaque chapitre débute par sa propre introduction, qui consiste en une description plus détaillée du contexte motivant le(s) manuscrit(s) associé(s) et un bref résumé des résultats transmis. Un compte rendu détaillé des méthodes et des résultats peut être trouvé dans le(s) dit(s) manuscrit(s). Dans l’étude qui compose le Chapitre 2, je compare la sensibilité des deux techniques ASL de pointe et je démontre que la dernière implémentation de l’ASL continue, la pCASL, offre des mesures plus robustes de la RVC en comparaison à d’autres méthodes pulsés plus âgées. Dans le Chapitre 3, je compare les mesures de la RVC obtenues par pCASL avec l’utilisation de quatre méthodes respiratoires différentes pour manipuler le CO2 artérielle (PaCO2) et je démontre que les résultats peuvent varier de manière significative lorsque les manipulations ne sont pas conçues pour fonctionner dans l’intervalle linéaire de la courbe dose-réponse du CO2. Le Chapitre 4 comprend deux études complémentaires visant à déterminer le niveau de reproductibilité qui peut être obtenu en utilisant des méthodes plus récentes pour la mesure de la RVC. La première étude a abouti à la mise au point technique d’un appareil qui permet des manipulations respiratoires du CO2 de manière simple, sécuritaire et robuste. La méthode respiratoire améliorée a été utilisée dans la seconde étude – de neuro-imagerie – où la sensibilité et la reproductibilité de la RVC, mesurée par pCASL, ont été examinées. La technique d’imagerie pCASL a pu détecter des réponses de perfusion induites par la variation du CO2 dans environ 90% du cortex cérébral humain et la reproductibilité de ces mesures était comparable à celle d’autres mesures hémodynamiques déjà adoptées dans la pratique clinique. Enfin, dans le Chapitre 5, je présente un modèle mathématique qui décrit la RVC en termes de changements du PaCO2 liés à l’osmolarité du sang. Les réponses prédites par ce modèle correspondent étroitement aux changements hémodynamiques mesurés avec pCASL ; suggérant une contribution supplémentaire à la réactivité du système vasculaire cérébral en lien avec le CO2.
Carbon dioxide (CO2) is a natural byproduct of cellular metabolism, the third most abundant substance of blood, and a potent vasoactive agent. The resistance of cerebral vasculature and perfusion of the brain tissue respond to the slightest change in blood CO2 content. The physiology of such an effect remains elusive, yet the phenomenon has been widely exploited in studies of the cerebral vascular function. A promising avenue for the assessment of brain’s vascular function is to measure the cerebrovascular reactivity to CO2 (CVR) non-invasively using functional MRI. Quantitative and non-invasive mapping of CVR can be obtained using respiratory manipulations in arterial CO2 and Arterial Spin Labeling (ASL) to measure the perfusion changes associated with the vascular stimulus. However, concerns related to the sensitivity and reliability of CVR mea- sures by ASL still limit their broader adoption. I considered that a thorough analysis and amelioration of available methods could bring a valuable contribution in the domain of biomedical engineering, helping to advance new diagnostic imaging tools. In this thesis I present a series of studies where I exam the impact of alternative manipulation/ASL methods on CVR measures, and ways to improve the sensitivity and reliability of these measures. I have also included in this thesis a theoretical paper, where I exam the possible contribution of an unappreciated factor in the CVR phenomenon: the changes in blood osmotic pressure induced by the products of CO2 dissolution. Apart from a general introduction (Chapter 1) and conclusion (Chapter 6), this thesis comprises 4 other chapters, in which five different research studies are presented in the form of articles accepted for publication in scientific journals. Each of these chapters begins with its own specific introduction, which consists of a description of the background motivating the study and a brief summary of conveyed findings. A detailed account of methods and results can be found in the accompanying manuscript(s). The study composing Chapter 2 compares the sensitivity of two state-of-the-art ASL techniques and show that a recent implementation of continuous ASL, pCASL, affords more robust measures of CVR than older pulsed methods. The study described in Chapter 3 compares pCASL CVR measures obtained using 4 different respiratory methods to manipulate arterial CO2 (PaCO2) and shows that results can differ significantly when manipulations are not designed to operate at the linear range of the CO2 dose-response curve. Chapter 4 encompasses two complementary studies seeking to determine the degree of reproducibility that can be attained measuring CVR using the most recent methods. The first study resulted in the technical development of a breathing apparatus allowing simple, safe and robust respiratory CO2 manipulations. The improved respiratory method was used in the second – neuroimaging – study, in which I and co-authors investigate the sensitivity and reproducibility of pCASL measuring CVR. The pCASL imaging technique was able to detect CO2-induced perfusion responses in about 90% of the human brain cortex and the reproducibility of its measures was comparable to other hemodynamic measures already adopted in the clinical practice. Finally, in Chapter 5 I present a mathematical model that describes CVR in terms of PaCO2-related changes in blood osmolarity. The responses predicted by this model correspond closely to the hemodynamic changes measured with pCASL, suggesting an additional contribution to the reactivity of cerebral vasculature to CO2.

There is no current cure for food allergy; therefore consumers with food allergy rely on accurate and detailed information on food labels in order to prevent an adverse reaction. Manufacturers cannot guarantee that food products are free from allergens as cross contamination can occur in several situations including but not limited to raw materials, the actual premises, storage and distribution, manufacturing processes and cleaning procedures. In order to alert the allergic consumer to the possible presence of trace allergens, manufacturers have voluntarily added precautionary labelling to processed foods. There are several variations to these statements, for example: “may contain traces of”, “may be present “and “made on the same production line”. The main purpose of this thesis is to understand the role of precautionary labelling in the care of children with food allergies.

L’imagerie par résonance magnétique (IRM) est un outil important pour l’investigation qualitative et quantitative de la physiologie du cerveau. L’investigation de l’activité neuronale à l’aide de cette modalité est possible grâce à la détection de changements hémodynamiques qui surviennent de manière concomitante aux activités de signalisation des neurones, tels l’augmentation régionale du débit sanguin cérébral (CBF) ou encore la variation de la concentration de désoxyhémoglobine dans les vaisseaux veineux. Pour étudier la formation de contrastes fonctionnels qui découlent de ces phénomènes, deux séquences de pulses ont été développées en vue d’expériences en IRM fonctionnelle (IRMf) visant l’imagerie du signal oxygéno-dépendant BOLD ainsi que de la perfusion. Le premier objectif de cette thèse fut le développement d’une séquence de type écho-planar (EPI) permettant l’acquisition entrelacée d’images en mode échos de gradient (GRE-EPI) ainsi qu’en mode échos de spins (SE-EPI) pour l’évaluation de la performance de ces deux méthodes d’imagerie au cours d’une expérience en IRMf BOLD impliquant l’utilisation d’un stimulus visuel chez 4 sujets adultes sains. Le deuxième objectif principal de cette thèse fut le développement d’une séquence de marquage de spins artériels employant un module de marquage fonctionnant en mode pseudo-continu (pCASL) pour la quantification du CBF au repos. Cette séquence fut testée chez 3 sujets adultes en bonne santé et sa performance fut comparée à celle d’une séquence similaire développée par un groupe de recherche extérieur. Les résultats de l’expérience portant sur le contraste BOLD indiquent une supériorité de la performance du mode GRE-EPI vis-à-vis celle du mode SE-EPI en termes des valeurs moyennes du pourcentage de l’ampleur d’effet et du score t associés à l’activité neuronale en réponse au stimulus. L’expérience visant la quantification du CBF démontra la capacité de la séquence pCASL développée au cours de ce projet de calculer des valeurs de la perfusion de la matière grise ainsi que du cerveau entier se retrouvant dans une plage de valeurs qui sont physiologiquement acceptables, mais qui demeurent inférieures à celles obtenues par la séquence pCASL développée par le groupe de recherche extérieur. Des expériences futures seront effectuées pour optimiser le fonctionnement des séquences présentées dans ce mémoire en plus de quantifier l’efficacité d’inversion de la séquence pCASL.
Magnetic resonance imaging (MRI) is an important tool for the qualitative and quantitative investigation of brain physiology. The investigation of neuronal activation using this modality is made possible by the detection of concomitantly-arising hemodynamic changes in the brain’s vasculature, such as localized increases of the cerebral blood flow (CBF) or the variation of the concentration of paramagnetic deoxyhemoglobin in venous vessels. To study the formation of functional contrasts that stem from these changes in MRI, two pulse sequences were developed in this thesis to carry out experiments in blood oxygenation level dependent (BOLD) and perfusion functional MRI (fMRI). The first objective laid out in this work was the development of an echo planar imaging (EPI) sequence permitting the interleaved acquisition of images using gradient-echo EPI and spin-echo EPI to assess the performances of these imaging techniques in a BOLD fMRI experiment involving a visual stimulation paradigm in 4 healthy adult subjects. The second main objective of this thesis was the development of a pseudo-continuous arterial spin labelling (pCASL) sequence for the quantification of cerebral blood flow (CBF) at rest. This sequence was tested on 3 healthy adult subjects and compared to an externally-developed pCASL sequence to assess its performance. The results of the BOLD fMRI experiment indicated that the performance of GRE-EPI was superior to that of SE-EPI in terms of the average percent effect size and t-score associated with stimulus-driven neuronal activation. The CBF quantification experiment demonstrated the ability of the in-house pCASL sequence to compute values of CBF that are within a range of physiologically-acceptable values while remaining inferior to those computed using the externally-developed pCASL sequence. Future experiments will focus on the optimization of the sequences presented in this thesis as well as on the quantification of the pCASL sequence’s labelling efficiency.