Estimation parr spectroscopie de résonance magnétique des concentrations des métabolites cérébraux in vivo chez le petit animal (une analyse quantitative avec QUEST)

La spectroscopoie de résonance magnétique (SRM) permet d'accéder, de façon non invasive, aux concentrations des substances chimiques -métabolites - d'un tissu vivant. Le sujet de cete thèse concerne d'une part, le développement des protocoles expérimentaux d'acquisition des signaux SRM proton in vivo à temps d'écho courts à 4.7T et à 7T chez le petit animal et d'autre part, le traitement des données pour l'estimation des métabolites cérébraux. La méthode QUEST, développée dans notre laboratoire, a été exploitée. Cette méthode de quantification du domaine temporel fondée sur une base de connaissance de métabolites repose sur une modélisation semi-paramétrique des signaux acquis à temps d'échos courts. L'influence de deux approches alternatives pour obtenir la base des métabolites (mesure in vitro des signaux des métabolites en solution ou simulation des signaux par Mécanique Quantique) sur l'estimation des concentrations des métabolites cérébraux a été évaluée. Des développements méthodologiques visant l'acquisition in vivo du signal de ligne de base provenant notamment des macromolécules ont été réalisés. L'influence de la stratégie de prise en compte du signal de ligne de base sur la précision des estimations a également été étudiée avec la méthode QUEST. Également nous avons estimé les temps de relaxation in vivo et in vitro des principaux métabolites cérébraux à 4.7T et à 7T. Les protocoles, mis en oeuvre au cours de la thèse, ont été exploités afin d'étudier des modèles murins de pathologies neurologiques tel que l'épilepsieLocalized brain proton magnetic resonance spectroscopy (1H MRS) can non-invasively provide - by quantification of brain metabolites - biochemical information from living tissues. Te purposes of this work were : 1) to set up the localize brain 1H MRS at short echo time at 7T and 4.7T on small animals ; 2) to quantify the concentration of brain metabolites. The QUEST method, developed in our laboratory, was used. This method is based on a metabolite basis-set prior-knowledge and fits a time-domain model function, a combination of metabolite basis-set signals, directly to the low SNR in vivo data. The influence of the two basis-set approaches (an in vitro basis-set made of the measured signals of aqueous solutions and a simulated basis-set made of the theoretical metabolite signals quantum mechanically simulated) on the metabolite concentration estimates was evaluated. Methodological developments aiming the acquisiation of the background signal were performed. The influence of the background-accommodation strategy on the metabolite concentration estimates was also studied using QUEST. We have also estimated the relaxation times in vitro and in vivo of the principal brain metabolites at 4.7T et 7A. The acquisition protocols, which were set up during this work, were used to study different models of neurological pathologies such as the epilepsyLYON1-BU.Sciences (692662101) / SudocSudocFranceF

Quantification method using the Morlet wavelet for magnetic resonance spectroscopic signals with macromolecular contamination

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Morlet wavelet analysis of magnetic resonance spectroscopic signals with macromolecular contamination

We apply the Morlet wavelet transform to character- izing Magnetic Resonance Spectroscopy (MRS) signals acquired at short echo-time. These signals usually contain contributions from metabolites, water and a baseline which mainly originates from large molecules, known as macromolecules, and lipids. The baseline accommodation is one of the major obstructions in in vivo short echo-time MRS quantification as its shape and intensity are not known a priori. In this paper, the simulated signal of the N-acetylaspartate (NAA) metabolite is used as a test signal to be recovered after adding the in vivo macromolecular signal. The in vivo macromolecule MRS signal was acquired on a horizontal 4.7T Biospec system. By optimizing the inversion time, which represents the delay between the inversion pulse and the first pulse of the PRESS sequence, the metabolites are nullified while the others are maintained. The metabolite-nullified signal from a volume-of-interest centralized in the hippocampus of a healthy mouse, which was a combination of residual water, baseline and noise, was added to the signal of NAA. The amplitude of the metabolite is also varied to visualize the sensitivity of the wavelet transform at different ratios between the intensity of the macromolecular and the metabolite signals. Compared to the simulated signal of NAA, the signal decays much faster. The time- scale representation of the wavelet can therefore distinguish the two signals without any additional pre-processing. The amplitude of the metabolite is also correctly derived although at earlier time it still has an effect of the baseline

Analyzing magnetic resonance spectroscopic signals with macromolecular contamination by the Morlet wavelet

We study the Morlet wavelet transform on characterizing Magnetic Resonance Spectroscopy (MRS) signals acquired at short echo-time. These MRS signals usually contain contributions from metabolites, water and a baseline which mainly originates from large molecules, known as mac-romolecules, and lipids. As its shape and intensity are not known a priori, the baseline accommodation becomes one of the major obstructions in in vivo short echo-time MRS quanti-fication. We acquired an in vivo macromolecule MRS signal on a horizontal 4.7T Biospec system by optimizing the inversion time, which represents the delay between the inversion pulse and the first pulse of the PRESS sequence. As a consequence, the metabolites are nullified while the others are maintained. The metabolite-nullified signal from a volume-of-interest cen-tralized in the hippocampus of a healthy mouse was a combi-nation of residual water, baseline and noise. Compared to the simulated signal of creatine, the signal decays much faster. The time-scale representation of the wavelet can therefore distin-guish the two signals without any additional pre-processing. The amplitude of the metabolite is also correctly derived al-though at earlier time it still has an effect of the baseline. In addition, we also show that the Morlet wavelet can be used to characterize different lineshapes, e.g. Lorentzian, Gaussian or Voigt, which are generally used to model the MRS signals. That is, the first derivative of the modulus of the wavelet trans-form relates to the damping effect of the Lorentzian lineshape while its second derivative indicates the second-order broaden-ing of the Gaussian and Voigt. The performance of the wavelet when applied to an in vitro creatine is also presented

Targeted deletion of liver glucose-6 phosphatase mimics glycogen storage disease type 1a including development of multiple adenomas.

International audienceThis is the first report of a viable animal model of the hepatic pathology of GSD1a, including the late development of hepatocellular adenomas