OBJECTIVES AND BACKGROUND: Patient-specific finite element (FE) simulations were used to assess different transcatheter valve devices and help select the most appropriate treatment strategy for a patient (17-year-old male) with borderline dimensions for Melody® percutaneous pulmonary valve implantation (PPVI). METHODS AND RESULTS: Patient-specific implantation site morphology was derived from cardiovascular magnetic resonance (CMR) images along with the implantation site mechanical behavior by coupling systolic/diastolic dimensions and the pressure gradient in a linear elastic model, and iterative tuning. In this way, the model accounted for the mechanical response not only of the arterial wall, but also of the surrounding tissue. Four stents (2 balloon-expandable including prestenting and 2 self-expandable) were virtually implanted and the stent final configuration, anchoring, migration forces, arterial wall stresses, paravalvular regurgitation, and device mechanical performance were evaluated. A Sapien29 device with prestenting was indicated as the optimal approach for this specific patient as it had a fully open valve, safe anchoring along the entire circumference, low risk of paravalvular leak, and arterial rupture. However, at the time of the PPVI procedure, after balloon sizing, device implantation was suspended due to perceived high risk of device embolization. CONCLUSIONS: FE analysis allows a comparison between different treatment scenarios to add information to the clinical decision making process. However, further studies are required to fully predict patient-specific response to stenting and therefore true clinical outcomes.
OBJECTIVES AND BACKGROUND: Patient-specific finite element (FE) simulations were used to assess different transcatheter valve devices and help select the most appropriate treatment strategy for a patient (17-year-old male) with borderline dimensions for Melody® percutaneous pulmonary valve implantation (PPVI). METHODS AND RESULTS: Patient-specific implantation site morphology was derived from cardiovascular magnetic resonance (CMR) images along with the implantation site mechanical behavior by coupling systolic/diastolic dimensions and the pressure gradient in a linear elastic model, and iterative tuning. In this way, the model accounted for the mechanical response not only of the arterial wall, but also of the surrounding tissue. Four stents (2 balloon-expandable including prestenting and 2 self-expandable) were virtually implanted and the stent final configuration, anchoring, migration forces, arterial wall stresses, paravalvular regurgitation, and device mechanical performance were evaluated. A Sapien29 device with prestenting was indicated as the optimal approach for this specific patient as it had a fully open valve, safe anchoring along the entire circumference, low risk of paravalvular leak, and arterial rupture. However, at the time of the PPVI procedure, after balloon sizing, device implantation was suspended due to perceived high risk of device embolization. CONCLUSIONS: FE analysis allows a comparison between different treatment scenarios to add information to the clinical decision making process. However, further studies are required to fully predict patient-specific response to stenting and therefore true clinical outcomes.
Authors: Reza Avazmohammadi; João S Soares; David S Li; Samarth S Raut; Robert C Gorman; Michael S Sacks Journal: Annu Rev Biomed Eng Date: 2019-06-04 Impact factor: 9.590
Authors: Giovanni Biglino; Claudio Capelli; Jan Bruse; Giorgia M Bosi; Andrew M Taylor; Silvia Schievano Journal: Heart Date: 2016-10-25 Impact factor: 5.994
Authors: Giorgia M Bosi; Claudio Capelli; Mun Hong Cheang; Nicola Delahunty; Michael Mullen; Andrew M Taylor; Silvia Schievano Journal: J Biomech Date: 2018-02-20 Impact factor: 2.712