Patient-specific in-silico models of transcatheter aortic valve implantation (TAVI) have gained a high level of complexity and accuracy and may become a relevant tool for supporting clinical decision-making and device design. When focusing on patient-specific material properties, the advanced age and the lack of ex-vivo material characterizations makes particularly challenging the utilize of reliable material parameters for patient-specific computational simulations of TAVI. This study focuses on the calibration of patient-specific constitutive descriptors for both the aortic wall and calcific aortic valve using an inverse approach and imaging data. Once the optimal material parameters were obtained, numerical simulations of the pre-TAVI scenario were found in agreement with CT imaging, thereby leading to a robust non-invasive approach for in-vivo assessment of material properties.
Catalano C., Cannata S., Gandolfo C., Pasta S. (2023). An Inverse Analysis for the Assessment of Material Properties of TAVI Patients. In Eighth National Congress of Bioengineering – Proceedings 2023. Patron Editore S.r.l..
An Inverse Analysis for the Assessment of Material Properties of TAVI Patients
Catalano C.;Gandolfo C.;Pasta S.
2023-01-01
Abstract
Patient-specific in-silico models of transcatheter aortic valve implantation (TAVI) have gained a high level of complexity and accuracy and may become a relevant tool for supporting clinical decision-making and device design. When focusing on patient-specific material properties, the advanced age and the lack of ex-vivo material characterizations makes particularly challenging the utilize of reliable material parameters for patient-specific computational simulations of TAVI. This study focuses on the calibration of patient-specific constitutive descriptors for both the aortic wall and calcific aortic valve using an inverse approach and imaging data. Once the optimal material parameters were obtained, numerical simulations of the pre-TAVI scenario were found in agreement with CT imaging, thereby leading to a robust non-invasive approach for in-vivo assessment of material properties.File | Dimensione | Formato | |
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