Le but de cette étude est d’évaluer la faisabilité de l’analyse tomodensitométrique 3D des bioprothèses aortiques pour faciliter leur évaluation morphologique durant le suivi et d’aider la sélection de cas et améliorer la planification d’une procédure valvein-valve. Le challenge était représenté par le rehaussement des feuillets valvulaires, en raison d’images très bruitées. Un angio-scanner synchronisé était réalisé chez des patients porteurs d’une bioprotèses aortique dégénérée avant réintervention (images in-vivo). Différentes méthodes pour la réduction du bruit étaient proposées. La reconstruction tridimensionnelle des bioprothèses était réalisée en utilisant des méthodes de segmentation de régions par "sticks". Après réopération ces méthodes étaient appliquées aux images scanner des bioprothèses explantées (images ex-vivo) et utilisées comme référence. La réduction du bruit obtenue par le filtre stick modifié montrait meilleurs résultats en rapport signal/bruit en comparaison aux filtres de diffusion anisotropique. Toutes les méthodes de segmentation ont permis une reconstruction 3D des feuillets. L’analyse qualitative a montré une bonne concordance entre les images obtenues in-vivo et les altérations des bioprothèses. Les résultats des différentes méthodes étaient comparés par critères volumétriques et discutés. Les bases d'une première approche de visualisation spatio-temporelle d'images TDM 3D+T de la prothèse valvulaire ont été proposés. Elle implique des techniques de rendu volumique et de compensation de mouvement. Son application à la valve native a aussi été envisagée. Les images scanner des bioprothèses aortiques nécessitent un traitement de débruitage et de réduction des artéfacts de façon à permettre le rehaussement des feuillets prothétiques. Les méthodes basées sticks semblent constituer une approche pertinente pour caractériser morphologiquement la dégénérescence des bioprothèses. / The aim of the study was to assess the feasibility of CT based 3D analysis of degenerated aortic bioprostheses to make easier their morphological assessment. This could be helpful during regular follow-up and for case selection, improved planning and mapping of valve-in-valve procedure. The challenge was represented by leaflets enhancement because of highly noised CT images. Contrast-enhanced ECG-gated CT scan was performed in patients with degenerated aortic bioprostheses before reoperation (in-vivo images). Different methods for noise reduction were tested and proposed. 3D reconstruction of bioprostheses components was achieved using stick based region segmentation methods. After reoperation, segmentation methods were applied to CT images of the explanted prostheses (exvivo images). Noise reduction obtained by improved stick filter showed best results in terms of signal to noise ratio comparing to anisotropic diffusion filters. All segmentation methods applied to the best phase of in-vivo images allowed 3D bioprosthetic leaflets reconstruction. Explanted bioprostheses CT images were also processed and used as reference. Qualitative analysis revealed a good concordance between the in-vivo images and the bioprostheses alterations. Results from different methods were compared by means of volumetric criteria and discussed. A first approach for spatiotemporal visualization of 3D+T images of valve bioprosthesis has been proposed. Volume rendering and motion compensation techniques were applied to visualize different phases of CT data. Native valve was also considered. ECG-gated CT images of aortic bioprostheses need a preprocessing to reduce noise and artifacts in order to enhance prosthetic leaflets. Stick based methods seems to provide an interesting approach for the morphological characterization of degenerated bioprostheses.

The aim of the study was to assess the feasibility of CT based 3D analysis of degenerated aortic bioprostheses to make easier their morphological assessment. This could be helpful during regular follow-up and for case selection, improved planning and mapping of valve-in-valve procedure. The challenge was represented by leaflets enhancement because of highly noised CT images. Contrast-enhanced ECG-gated CT scan was performed in patients with degenerated aortic bioprostheses before reoperation (in-vivo images). Different methods for noise reduction were tested and proposed. 3D reconstruction of bioprostheses components was achieved using stick based region segmentation methods. After reoperation, segmentation methods were applied to CT images of the explanted prostheses (exvivo images). Noise reduction obtained by improved stick filter showed best results in terms of signal to noise ratio comparing to anisotropic diffusion filters. All segmentation methods applied to the best phase of in-vivo images allowed 3D bioprosthetic leaflets reconstruction. Explanted bioprostheses CT images were also processed and used as reference. Qualitative analysis revealed a good concordance between the in-vivo images and the bioprostheses alterations. Results from different methods were compared by means of volumetric criteria and discussed. A first approach for spatiotemporal visualization of 3D+T images of valve bioprosthesis has been proposed. Volume rendering and motion compensation techniques were applied to visualize different phases of CT data. Native valve was also considered. ECG-gated CT images of aortic bioprostheses need a preprocessing to reduce noise and artifacts in order to enhance prosthetic leaflets. Stick based methods seems to provide an interesting approach for the morphological characterization of degenerated bioprostheses.