Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions · 2015
Patient-specific finite element models to support clinical decisions: A lesson learnt from a case study of percutaneous pulmonary valve implantation.
Клинический случайСтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Bosi Giorgia M, Capelli Claudio, Khambadkone Sachin, Taylor Andrew M, Schievano Silvia
Аннотация
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.
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.
Предметные рубрики MeSH
AdolescentHumansMaleCardiac CatheterizationClinical Decision-MakingComputer SimulationFinite Element AnalysisFollow-Up StudiesHeart Valve ProsthesisMagnetic Resonance Imaging, CineModels, CardiovascularProsthesis DesignPulmonary Valve InsufficiencyRisk AssessmentSeverity of Illness IndexTreatment Outcome