Magnetic Resonance Imaging (MRI) is an important diagnostic tool for imaging soft tissue without the use of ionizing radiation. Moreover, through advanced signal processing, MRI can provide more than just anatomical information, such as estimates of tissue-specific physical properties. Signal processing lies at the very core of the MRI process, which involves input design, information encoding, image reconstruction, and advanced filtering. Based on signal modeling and estimation, it is possible to further improve the images, reduce artifacts, mitigate noise, and obtain quantitative tissue information. In quantitative MRI, different physical quantities are estimated from a set of collected images. The optimization problems solved are typically nonlinear, and require intelligent and application-specific algorithms to avoid suboptimal local minima. This thesis presents several methods for efficiently solving different parameter estimation problems in MRI, such as multi-component T2 relaxometry, temporal phase correction of complex-valued data, and minimizing banding artifacts due to field inhomogeneity. The performance of the proposed algorithms is evaluated using both simulation and in-vivo data. The results show improvements over previous approaches, while maintaining a relatively low computational complexity. Using new and improved estimation methods enables better tissue characterization and diagnosis. Furthermore, a sequence design problem is treated, where the radio-frequency excitation is optimized to minimize image artifacts when using amplifiers of limited quality. In turn, obtaining higher fidelity images enables improved diagnosis, and can increase the estimation accuracy in quantitative MRI.

Current quantitative nuclear magnetic resonance (NMR) technics offer biomarkers that allow performing non-invasive longitudinal studies for the follow up of therapeutic trials in neuromuscular disorders (NMD). In contrast to fat degeneration, the mechanisms of inflammation/oedema/necrosis and fibrosis are characteristic signs of disease activity, which makes their quantification a promising source of crucial biomarkers for longitudinal studies. This thesis work consisted on the implementation of more precise quantitative NMR methods adapted to the clinical study of skeletal muscle (SKM) for : (i) detection and quantification of sites of disease activity by T2-mapping of muscle water ; (ii) investigation of the different pathophysiological mechanisms underlying T2 alterations ; and (iii) Detection and quantification of muscle fibrosis. We implemented two methods for T2 mapping of muscle water. The first one is based on a multi-spin-echo sequence du type CPMG. In this method the 1H-NMR signals from water and lipids are acquired simultaneously. The acquired data are fitted to a tri-exponential model, in which water and fat signals are separated by exploring the T2 difference between water and fat. This method allows extraction of muscle water T2-value in the presence of fat infiltration. The second method is based on a " partially spoiled steady state free precession " (pSSFP) sequence. In contrast to the first method, which demands a sophisticated post-treatment of images acquired at 17 different echo-times, with the pSSFP a T2-mapping is extracted from two 3D data sets. 3D acquisition is compatible with spectrally selective water excitation, which eliminates signal contribution from lipids. Both methods were validated experimentally on patients and healthy subjects. The results demonstrated their capacity to detect and quantify disease activity sites. This 2 works have been published in two international journals : Azzabou, de Sousa, Araujo, & Carlier, 2014. Journal of Magnetic Resonance Imaging. DOI 10.1002/jmri.24613 (in press); et de Sousa, Vignaud, Araujo, & Carlier . 2012. Magnetic Resonance in Medicine. 67:1379-1390. Although it was shown to reveal disease activity, mono-exponential T2 of muscle water is non-specific to what concerns the mechanisms underlying its alterations. It has been long known that T2 relaxation in SKM tissue is multi-exponential. This is currently accepted to reveal anatomical compartmentation of myowater. We implemented a method for localized spectroscopic CPMG acquisition. CPMG data respect echo-time sampling and signal to noise ration limits for allowing robust multiexponential analysis. This work allowed us to establish a compartmentation model that perfectly explains the multi-exponential T2 relaxation observed in SKM tissue. This work was published in the " Biophysical Journal " (Araujo, Fromes & Carlier 2014. New Insights on skeletal muscle tissue compartments revealed by T2 NMR relaxometry. (In press)). Pilot studies performed in patients show promising results and suggest potential application of the method in clinical studies. Fibrosis starts with an excessive accumulation of intramuscular connective tissue (IMCT). We have explored the " Ultrashort time to echo " (UTE) method with the aim to detect and characterize the signal from IMCT. In a first study we characterized in vivo a short T2 component (~500 µs) in SKM, and we collected evidences suggesting that this component might reflect IMCT. Then we implemented a methodology that allowed imaging this short component in SKM tissue for the first time.

Actuellement, des méthodes quantitatives de résonance magnétique nucléaire (RMN) offrent des biomarqueurs qui permettent la réalisation d’études longitudinales pour le suivi de l’évolution des maladies neuromusculaires et des essais thérapeutiques de manière non-invasive. A la différence de la dégénérescence graisseuse, les processus d’inflammation/œdème/nécrose et fibrose sont des signes d’activité des maladies et leurs quantifications constitueraient ainsi de biomarqueurs parfaitement adaptés pour le suivi thérapeutique. Ce travail de thèse a consisté à mettre en place des méthodologies quantitatives plus précises et adaptées à l’étude clinique du muscle pour : (i) détecter et quantifier des sites d’activité de maladies par la cartographie T2 de l’eau ; (ii) identifier les différents processus pathophysiologiques qui sont à l’origine des altérations du T2 ; et (iii) détecter et quantifier la fibrose musculaire. Nous avons implémenté deux méthodes pour la quantification du T2 de l’eau dans le muscle. La première est basée sur une séquence d’écho de spin du type CPMG, où les signaux provenant des protons des lipides et de l’eau sont acquis simultanément et séparés à postériori par un traitement tri-exponentiel qui exploite la différence entre les T2 qui caractérisent les signaux de l’eau et de la graisse. La deuxième technique est basée sur une séquence de « partially spoiled steady state free precession (pSSFP) ». Différemment de la première technique qui nécessite un traitement assez élaboré sur des images acquises à 17 temps d’écho différents, dans la pSSFP la cartographie T2 est extraite à partir de deux séries de données 3D. L’acquisition 3D est compatible avec des techniques de sélection spectrale de l’eau, ce qui évite la contamination par les signaux des lipides. Les deux méthodes ont été validées expérimentalement chez des malades et des sujets sains et ont démontré leur capacité à détecter et quantifier des sites d’activité de maladies. Ces deux travaux font l’objet de deux publications dans des journaux scientifiques internationaux : Azzabou, de Sousa, Araujo, & Carlier, 2014. Journal of Magnetic Resonance Imaging. DOI 10.1002/jmri.24613 (in press); et de Sousa, Vignaud, Araujo, & Carlier . 2012. Magnetic Resonance in Medicine. 67:1379-1390. Malgré le fait de permettre la détection des sites d’activité de maladies, la mesure mono-exponentielle du T2 de l’eau par imagerie reste non-spécifique vis-à-vis des processus physiologiques à l’origine de l’augmentation du T2. Il est connu que la relaxation T2 du muscle squelettique n’est pas mono-exponentielle. Cela est interprété comme une conséquence de la compartimentation anatomique de l’eau tissulaire. Nous avons mis au point une méthode pour l’acquisition localisée de données CPMG. Cette technique permet l’acquisition des données dans des conditions nécessaires pour la réalisation de traitements multi-exponentiels précis. Ce travail nous a permis d’établir un modèle de compartimentation qui explique parfaitement la relaxation T2 dans le muscle. Il a fait l’objet d’un article publié dans le « Biophysical Journal » (Araujo, Fromes & Carlier 2014. New Insights on skeletal muscle tissue compartments revealed by T2 NMR relaxometry. (In press)). Les essais réalisés chez des sujets malades suggèrent un grand potentiel pour l’application de la méthode dans des études cliniques. La formation de la fibrose commence avec une accumulation excessive de tissu conjonctif intramusculaire (TCIM). Nous avons exploité la technique « Ultrashort Time-to-Echo » (UTE) pour essayer de détecter et caractériser le signal du TCIM. Dans une première étude, nous avons caractérisé in vivo une composante à T2 court (~500 µs) dans le muscle, et nous avons trouvé des indices qui suggèrent qu’elle représente le TCIM. Dans une deuxième étude, nous avons mis au point une méthodologie qui a permis d’imager cette composante à T2 court dans le muscle pour la première fois. / Current quantitative nuclear magnetic resonance (NMR) technics offer biomarkers that allow performing non-invasive longitudinal studies for the follow up of therapeutic trials in neuromuscular disorders (NMD). In contrast to fat degeneration, the mechanisms of inflammation/oedema/necrosis and fibrosis are characteristic signs of disease activity, which makes their quantification a promising source of crucial biomarkers for longitudinal studies. This thesis work consisted on the implementation of more precise quantitative NMR methods adapted to the clinical study of skeletal muscle (SKM) for : (i) detection and quantification of sites of disease activity by T2-mapping of muscle water ; (ii) investigation of the different pathophysiological mechanisms underlying T2 alterations ; and (iii) Detection and quantification of muscle fibrosis. We implemented two methods for T2 mapping of muscle water. The first one is based on a multi-spin-echo sequence du type CPMG. In this method the 1H-NMR signals from water and lipids are acquired simultaneously. The acquired data are fitted to a tri-exponential model, in which water and fat signals are separated by exploring the T2 difference between water and fat. This method allows extraction of muscle water T2-value in the presence of fat infiltration. The second method is based on a « partially spoiled steady state free precession » (pSSFP) sequence. In contrast to the first method, which demands a sophisticated post-treatment of images acquired at 17 different echo-times, with the pSSFP a T2-mapping is extracted from two 3D data sets. 3D acquisition is compatible with spectrally selective water excitation, which eliminates signal contribution from lipids. Both methods were validated experimentally on patients and healthy subjects. The results demonstrated their capacity to detect and quantify disease activity sites. This 2 works have been published in two international journals : Azzabou, de Sousa, Araujo, & Carlier, 2014. Journal of Magnetic Resonance Imaging. DOI 10.1002/jmri.24613 (in press); et de Sousa, Vignaud, Araujo, & Carlier . 2012. Magnetic Resonance in Medicine. 67:1379-1390. Although it was shown to reveal disease activity, mono-exponential T2 of muscle water is non-specific to what concerns the mechanisms underlying its alterations. It has been long known that T2 relaxation in SKM tissue is multi-exponential. This is currently accepted to reveal anatomical compartmentation of myowater. We implemented a method for localized spectroscopic CPMG acquisition. CPMG data respect echo-time sampling and signal to noise ration limits for allowing robust multiexponential analysis. This work allowed us to establish a compartmentation model that perfectly explains the multi-exponential T2 relaxation observed in SKM tissue. This work was published in the « Biophysical Journal » (Araujo, Fromes & Carlier 2014. New Insights on skeletal muscle tissue compartments revealed by T2 NMR relaxometry. (In press)). Pilot studies performed in patients show promising results and suggest potential application of the method in clinical studies. Fibrosis starts with an excessive accumulation of intramuscular connective tissue (IMCT). We have explored the « Ultrashort time to echo » (UTE) method with the aim to detect and characterize the signal from IMCT. In a first study we characterized in vivo a short T2 component (~500 µs) in SKM, and we collected evidences suggesting that this component might reflect IMCT. Then we implemented a methodology that allowed imaging this short component in SKM tissue for the first time.