Preoperative morphological analysis of degenerated aortic bioprosthesis by CT images segmentation. Implications for valve-in-valve procedure

Objective: The valve-in-valve procedure is being proposed in the next future as an option for patients with failing aortic bioprosthesis and excessive surgical risk. A morphological assessment by 3D analysis of the degenerated bioprosthesis could be helpful for case selection, improved planning and mapping of valve-in-valve procedure. The aim of the study was to assess the feasibility of CT based 3D analysis of degenerated aortic bioprostheses.Methods: 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. Three methods for semi-automatic segmentation were proposed: the interactive region growing (IRG), the stick region growing (Stick RG) and the stick exhaustive search (SES). After reoperation, segmentation methods were applied to CT images of the explanted prostheses (ex-vivo images).Results: Noise reduction obtained by improved stick filter showed best results comparing to anisotropic diffusion filters. All segmentation methods applied to 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.Conclusions: ECG-gated CT images allow morphologically reliable images of failing aortic bioprostheses but need a preprocessing to reduce noise and artifacts. Stick region based segmentation seems to provide an interesting approach for the morphological characterization of degenerated bioprostheses. These preliminary results need to be supported by additional data.