Abstract
BACKGROUND: Mitral valve repair (MVR) has been considered superior to mitral replacement for degenerative MV disease and even rheumatic diseases. However, the repair rate varies widely depending on the medical center and the surgeons' experience. The aim of our study was to apply three-dimensional printing (3DP) and computational fluid dynamics (CFD) in surgical simulation to provide reference for surgical decision-making, especially for inexperienced surgeons. METHODS: Our study included retrospective and prospective cohorts. We first enrolled the retrospective cohort of 35 patients who were prepared to have MVR, aiming at exploring the feasibility of surgical simulation using 3DP and CFD. Three-dimensional transesophageal echocardiography (3D-TEE) and computed tomography angiography (CTA) were performed for all patients, and imaging data were fused to construct a 3D digital model. Next, the model was used to make the 3DP dynamic model and for CFD analysis. Mitral repair was simulated in both the 3DP dynamic model and CFD to predict surgical outcomes (grade of regurgitation and vena contracta width) and possible complications (systolic anterior motion, left ventricular outflow tract obstruction). Second, a prospective cohort of 20 patients was studied with 10 patients placed in a 3DP-guided group and 10 in an image-guided group. Rate of transformation to mitral replacement, surgery time, surgical outcomes, and surgical complications were compared between groups. RESULTS: Of the 35 patients retrospectively enrolled, 14 underwent MVR and 21 were transferred to mitral replacement. Surgical simulation for the 14 MVR patients showed high consistency with in vivo results. The result of surgical simulation for the 21 patients transferred to mitral replacement showed that 7 might have benefited from MVR. In the prospective cohort, the rate of transformation to mitral replacement and surgery time in the 3DP-guided group were significantly lower than those in the image-guided group. CONCLUSIONS: 3DP and CFD models based on image data can be used for in vitro surgical simulation. These emerging technologies are now changing traditional models of diagnosis and treatment, and the role of imaging data will no longer be limited to diagnosis but will contribute more to assisting surgeons in choosing treatment strategies.