L’Imagerie par Résonance Magnétique (IRM) est une technique prometteuse largement répandue dans les milieux hospitaliers. Elle est non invasive, présente une bonne résolution spatiale et permet de visualiser en profondeur dans un organisme vivant. Elle possède cependant quelques défauts, dont sa faible sensibilité. Pour palier ce problème, il est possible d'utiliser des espèces hyperpolarisables telles que le xénon. Cependant, n’étant spécifique d’aucun récepteur biologique, le xénon nécessite d’être vectorisé. Pour ce faire, des auteurs ont proposé son encapsulation dans une cage moléculaire capable de reconnaître la cible biologique à imager. Les meilleurs candidats à ce jour sont les cryptophanes.Nous nous sommes fixés comme objectif dans cette thèse de concevoir et de synthétiser de nouvelles cages plus adaptées pour les applications en IRM 129Xe ainsi que des biosondes pertinentes pour se rapprocher d’applications in vivo. Dans une première partie de ma thèse, nous nous sommes intéressés au développement de nouvelles cages afin d’étudier et d’affiner les propriétés d’encapsulation du xénon au sein des cryptophanes. Dans les parties suivantes, nous nous sommes concentrés sur la conception de biosondes par fonctionnalisation de cryptophanes déjà décrits pour diverses applications d’intérêt biologique. D’une part, nous avons évalué la possibilité de détecter des métaux de manière plus spécifique et plus sensible grâce à l’IRM xénon hyperpolarisé. D’autre part, nous avons travaillé sur la conception de biosondes bimodales, afin de coupler des techniques complémentaires d’imagerie médicale. / Today, Magnetic Resonance Imaging (MRI) is a powerful clinically used imaging method which provides three-dimensional images with excellent resolution. However, conventional molecular MRI techniques that rely on the observation of water protons still suffer from reduced sensitivity and often lack selectivity. The use of hyperpolarized xenon can improve both the selectivity and sensitivity of the MRI method. As xenon has no specificity for any biological receptor, it needs to be vectorized. For this purpose, authors have proposed to encapsulate xenon inside molecular cages functionalized to recognize specific biological targets. The best candidates so far as biosensors are cryptophanes.The aim of this work is to design and synthesize new cryptophanes that are better suited for 129Xe MRI applications and relevant biosensors for future in vivo applications. In a first part, new cages were developed in order to study the encapsulation properties of xenon inside different cryptophanes. Then, biosensors were synthesized by functionnalization of known water-soluble cryptophanes for different applications of biological interest. We have therefore assessed the possibility of detecting metal ions specifically in a very sensitive way thanks to 129Xe MRI. New bimodal sensors were also designed and tested.

Chronic obstructive pulmonary disease (COPD) describes a range of lung conditions including emphysema, chronic bronchitis and small airways disease. While COPD is a major cause of death and debilitating illness, current clinical assessment methods are inadequate: they are a poor predictor of patient outcome and insensitive to mild disease. A new imaging technology, hyperpolarised xenon MRI, offers the hope of improved diagnostic techniques, based on regional measurements using functional imaging. There is a need for quantitative analysis techniques to assist in the interpretation of these images. The aim of this work is to develop these techniques as part of a clinical trial into hyperpolarised xenon MRI. In this thesis we develop a fully automated pipeline for deriving regional measurements of lung function, making use of the multiple imaging modalities available from the trial. The core of our pipeline is a novel method for automatically segmenting the pulmonary lobes from CT data. This method combines a Hessian-based filter for detecting pulmonary fissures with anatomical cues from segmented lungs, airways and pulmonary vessels. The pipeline also includes methods for segmenting the lungs from CT and MRI data, and the airways from CT data. We apply this lobar map to the xenon MRI data using a multi-modal image registration technique based on automatically segmented lung boundaries, using proton MRI as an intermediate stage. We demonstrate our pipeline by deriving lobar measurements of ventilated volumes and diffusion from hyperpolarised xenon MRI data. In future work, we will use the trial data to further validate the pipeline and investigate the potential of xenon MRI in the clinical assessment of COPD. We also demonstrate how our work can be extended to build personalised computational models of the lung, which can be used to gain insights into the mechanisms of lung disease.