Fluid-structure interaction analysis of transcatheter aortic valve implantation

التفاصيل البيبلوغرافية
العنوان: Fluid-structure interaction analysis of transcatheter aortic valve implantation
المؤلفون: Fumagalli, Ivan, Polidori, Rebecca, Renzi, Francesca, Fusini, Laura, Quarteroni, Alfio, Pontone, Gianluca, Vergara, Christian
بيانات النشر: WILEY
مصطلحات موضوعية: cardiovascular-system, in-silico predictive investigation, wall shear-stress, image-based simulations, finite-element-method, fluid-structure interaction, computed tomography, algorithms, patient-specific analysis, transcatheter aortic valve implantation
الوصف: Transcatheter aortic valve implantation (TAVI) is a minimally invasive intervention for the treatment of severe aortic valve stenosis. The main cause of failure is the structural deterioration of the implanted prosthetic leaflets, possibly inducing a valvular re-stenosis 5-10 years after the implantation. Based solely on pre-implantation data, the aim of this work is to identify fluid-dynamics and structural indices that may predict the possible valvular deterioration, in order to assist the clinicians in the decision-making phase and in the intervention design. Patient-specific, pre-implantation geometries of the aortic root, the ascending aorta, and the native valvular calcifications were reconstructed from computed tomography images. The stent of the prosthesis was modeled as a hollow cylinder and virtually implanted in the reconstructed domain. The fluid-structure interaction between the blood flow, the stent, and the residual native tissue surrounding the prosthesis was simulated by a computational solver with suitable boundary conditions. Hemodynamical and structural indicators were analyzed for five different patients that underwent TAVI - three with prosthetic valve degeneration and two without degeneration - and the comparison of the results showed a correlation between the leaflets' structural degeneration and the wall shear stress distribution on the proximal aortic wall. This investigation represents a first step towards computational predictive analysis of TAVI degeneration, based on pre-implantation data and without requiring additional peri-operative or follow-up information. Indeed, being able to identify patients more likely to experience degeneration after TAVI may help to schedule a patient-specific timing of follow-up.
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=od_______185::5155197c120c94908118749d42b7245fTest
https://infoscience.epfl.ch/record/302336Test
حقوق: CLOSED
رقم الانضمام: edsair.od.......185..5155197c120c94908118749d42b7245f
قاعدة البيانات: OpenAIRE