Analyse de bioprothèse valvulaire aortique dégénérée par segmentation d'images TDM préopératoires

LTSI, université de Rennes 1, campus de Beaulieu, bâtiment 22, 35000 Rennes, France Inserm U1099, campus de Beaulieu, bâtiment 22, 35000 Rennes, France Department of Thoracic and Cardiovascular Surgery, University Hospital Pontchaillou, 35000 Rennes, France Therenva, CIC-IT, Rennes, France LIST, Southeast University, Nanjing, China CRIBs, Centre de Recherche en Information Biomedicale sino-francais, Rennes / Nanjing, France / China. ____________________________________________________________________________________________ Abstract In the next future, transcatheter aortic valve implantation could represent a minimally invasive option in case of bioprosthesis failure for patients at high surgical risk. CT based preoperative planning of this procedure could be useful to optimize valve-in-valve implantation. In this context, bioprosthesis 3D analysis seems to be necessary, particularly for leaflets. The goal of this study was to propose different methods to segment and characterize a degenerated bioprosthesis using standard preoperative CT scan images in order to map structural injury of bioprosthesis and, ultimately, to plan the best positioning for valve-in-valve implantation. We report our preliminary results on segmentation of a degenerated bioprosthesis in aortic position. Three different methods have been tested and all allowed obtaining segmentation of the different bioprosthesis components. Results were compared by means of quantitative criteria. Explanted bioprosthesis CT images were used as reference. Semi-automatic segmentation seems to provide an interesting approach for the morphological characterization of degenerated bioprosthesis.