Salwa B Anam1, Brandon J Kovarovic1, Ram P Ghosh1, Matteo Bianchi1, Ashraf Hamdan2, Rami Haj-Ali3, Danny Bluestein4,5. 1. Biofluids Research Group, Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA. 2. Department of Cardiology, Rabin Medical Center, 4941492, Petah Tikva, Israel. 3. School of Mechanical Engineering, Faculty of Engineering, Tel Aviv University, Ramat Aviv, 69978, Tel Aviv, Israel. 4. Biofluids Research Group, Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, USA. danny.bluestein@stonybrook.edu. 5. Department of Biomedical Engineering, Stony Brook University, T8-050 Health Sciences Center, Stony Brook, NY, 11794-8084, USA. danny.bluestein@stonybrook.edu.
Abstract
INTRODUCTION: Bicuspid aortic valve (BAV) is the most common congenital cardiac malformation, which had been treated off-label by transcatheter aortic valve replacement (TAVR) procedure for several years, until its recent approval by the Food and Drug Administration (FDA) and Conformité Européenne (CE) to treat BAVs. Post-TAVR complications tend to get exacerbated in BAV patients due to their inherent aortic root pathologies. Globally, due to the paucity of randomized clinical trials, clinicians still favor surgical AVR as the primary treatment option for BAV patients. While this warrants longer term studies of TAVR outcomes in BAV patient cohorts, in vitro experiments and in silico computational modeling can be used to guide the surgical community in assessing the feasibility of TAVR in BAV patients. Our goal is to combine these techniques in order to create a modeling framework for optimizing pre-procedural planning and minimize post-procedural complications. MATERIALS AND METHODS: Patient-specific in silico models and 3D printed replicas of 3 BAV patients with different degrees of post-TAVR paravalvular leakage (PVL) were created. Patient-specific TAVR device deployment was modeled in silico and in vitro-following the clinical procedures performed in these patients. Computational fluid dynamics simulations and in vitro flow studies were performed in order to obtain the degrees of PVL in these models. RESULTS: PVL degree and locations were consistent with the clinical data. Cross-validation comparing the stent deformation and the flow parameters between the in silico and the in vitro models demonstrated good agreement. CONCLUSION: The current framework illustrates the potential of using simulations and 3D printed models for pre-TAVR planning and assessing post-TAVR complications in BAV patients.
INTRODUCTION: Bicuspid aortic valve (BAV) is the most common congenital cardiac malformation, which had been treated off-label by transcatheter aortic valve replacement (TAVR) procedure for several years, until its recent approval by the Food and Drug Administration (FDA) and Conformité Européenne (CE) to treat BAVs. Post-TAVR complications tend to get exacerbated in BAV patients due to their inherent aortic root pathologies. Globally, due to the paucity of randomized clinical trials, clinicians still favor surgical AVR as the primary treatment option for BAV patients. While this warrants longer term studies of TAVR outcomes in BAV patient cohorts, in vitro experiments and in silico computational modeling can be used to guide the surgical community in assessing the feasibility of TAVR in BAV patients. Our goal is to combine these techniques in order to create a modeling framework for optimizing pre-procedural planning and minimize post-procedural complications. MATERIALS AND METHODS: Patient-specific in silico models and 3D printed replicas of 3 BAV patients with different degrees of post-TAVR paravalvular leakage (PVL) were created. Patient-specific TAVR device deployment was modeled in silico and in vitro-following the clinical procedures performed in these patients. Computational fluid dynamics simulations and in vitro flow studies were performed in order to obtain the degrees of PVL in these models. RESULTS: PVL degree and locations were consistent with the clinical data. Cross-validation comparing the stent deformation and the flow parameters between the in silico and the in vitro models demonstrated good agreement. CONCLUSION: The current framework illustrates the potential of using simulations and 3D printed models for pre-TAVR planning and assessing post-TAVR complications in BAV patients.
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