Giulia Luraghi1, Francesco Migliavacca2, Alberto García-González3, Claudio Chiastra2,4, Alexia Rossi5, Davide Cao5, Giulio Stefanini5, Jose Felix Rodriguez Matas2. 1. Laboratory of Biological Structure Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering "Giulio Natta", Piazza L. da Vinci 32, 20133, Milan, Italy. giulia.luraghi@polimi.it. 2. Laboratory of Biological Structure Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering "Giulio Natta", Piazza L. da Vinci 32, 20133, Milan, Italy. 3. Laboratori de Càlcul Numèric (LaCàN), E.T.S. de Ingenieros de Caminos, Canales y Puertos, Universitat Politècnica de Catalunya (UPC), Jordi Girona 1-3, 08034, Barcelona, Spain. 4. PoliToBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Turin, Italy. 5. Department of Biomedical Sciences, Humanitas University, via Rita Levi Montalcini 4, 20090, Pieve Emanuele, MI, Italy.
Abstract
PURPOSE: Transcatheter aortic valve replacement (TAVR) is a minimally invasive treatment for high-risk patients with aortic diseases. Despite its increasing use, many influential factors are still to be understood and require continuous investigation. The best numerical approach capable of reproducing both the valves mechanics and the hemodynamics is the fluid-structure interaction (FSI) modeling. The aim of this work is the development of a patient-specific FSI methodology able to model the implantation phase as well as the valve working conditions during cardiac cycles. METHODS: The patient-specific domain, which included the aortic root, native valve and calcifications, was reconstructed from CT images, while the CAD model of the device, metallic frame and pericardium, was drawn from literature data. Ventricular and aortic pressure waveforms, derived from the patient's data, were used as boundary conditions. The proposed method was applied to two real clinical cases, which presented different outcomes in terms of paravalvular leakage (PVL), the main complication after TAVR. RESULTS: The results confirmed the clinical prognosis of mild and moderate PVL with coherent values of regurgitant volume and effective regurgitant orifice area. Moreover, the final release configuration of the device and the velocity field were compared with postoperative CT scans and Doppler traces showing a good qualitative and quantitative matching. CONCLUSION: In conclusion, the development of realistic and accurate FSI patient-specific models can be used as a support for clinical decisions before the implantation.
PURPOSE: Transcatheter aortic valve replacement (TAVR) is a minimally invasive treatment for high-risk patients with aortic diseases. Despite its increasing use, many influential factors are still to be understood and require continuous investigation. The best numerical approach capable of reproducing both the valves mechanics and the hemodynamics is the fluid-structure interaction (FSI) modeling. The aim of this work is the development of a patient-specific FSI methodology able to model the implantation phase as well as the valve working conditions during cardiac cycles. METHODS: The patient-specific domain, which included the aortic root, native valve and calcifications, was reconstructed from CT images, while the CAD model of the device, metallic frame and pericardium, was drawn from literature data. Ventricular and aortic pressure waveforms, derived from the patient's data, were used as boundary conditions. The proposed method was applied to two real clinical cases, which presented different outcomes in terms of paravalvular leakage (PVL), the main complication after TAVR. RESULTS: The results confirmed the clinical prognosis of mild and moderate PVL with coherent values of regurgitant volume and effective regurgitant orifice area. Moreover, the final release configuration of the device and the velocity field were compared with postoperative CT scans and Doppler traces showing a good qualitative and quantitative matching. CONCLUSION: In conclusion, the development of realistic and accurate FSI patient-specific models can be used as a support for clinical decisions before the implantation.
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