027 An image-derived, patient-specific computer simulation tool to test mitral valve treatment. (December 2018)

• Record Type: Journal Article
• Authors: Biffi, B; Capelli, C; Gritti, M; Fontana, M; Anderson, S; Davar, J; Parajmit, J; Whelan, C; Grasso, A; Schievano, S
• Is Part Of: Archives of disease in childhood. Volume 103:Supplement 2(2018)
• Page Start: A11
• Page End: A12
• Publication Date: 2018-12
• Subjects: Infants -- Diseases -- Periodicals; Newborn infants -- Diseases -- Periodicals; Fetus -- Diseases -- Periodicals; 618.920105
• DOI: 10.1136/goshabs.27
• Languages: English
• ISSNs: 1359-2998

Abstract

Abstract : Mitral valve (MV) function is the result of the mechanical interaction of different anatomical structures complexly arranged within the left heart (LH), with the blood flow. MV or LV structural abnormalities might cause valve regurgitation which in turn can lead to cardiac muscle overload and heart failure. Surgery remains the standard of care for operable patients, and interventional approaches for MV repair and replacement have more recently expanded the therapeutic options for high-risk patients. Patient-specific computational models of the heart are now becoming more and more reliable in reproducing realistic in-vivo conditions, allowing to investigate on the computer different therapeutic scenarios and to predict the most successful treatment. In this study, we describe the potential of a computational tool for MV modelling based on the integration of state-of-the-art patient medical imaging with fluid-structure interaction (FSI) computer simulations. A patient referred to our centre for MV regurgitation underwent both cardiac magnetic resonance (CMR) and 3D transoesophageal-echocardiogram (TOE). An automatic method was used to segment the MV from TOE and the LH from CMR and to compute patient-specific boundary conditions, which were used as input for the FSI simulation. Our simulation was able to reproduce realistic MV kinematic and flow velocity within the LH (figure 027-a). Incomplete leaflet coaptation (figure 027-b) confirmed the presence of regurgitant flow, as per patient pathological condition. The maximum, non-symmetrical stress distribution on the leaflets was found at the systolic peak. Our study showed that a patient's image information can be successfully integrated into computer simulations to accurately simulate LH and MV mechanics in a patient-specific case. Benefiting from a customisable and automatic implementation, such tool has the potential to simulate several surgical or interventional scenarios helping to identify the most suitable treatment, as well as to provide the ideal setting for the design of personalised MV device.