Transcatheter aortic valve implantation (TAVI) benefits from patient-specific computational modeling, yet model credibility remains a challenge. The ASME V&V40 standard provides a framework for assessing uncertainty and sensitivity in in silico predictions, ensuring reliability in clinical decision-making. This study evaluates uncertainty quantification (UQ) and sensitivity analysis of a patient-specific TAVI model using the ASME V&V40 standard to enhance model credibility. Four patient-specific TAVI models with 23 and 26 mm SAPIEN 3 Ultra (S3) devices were developed using finite-element simulations for deployment and fluid-structure interaction analysis for hemodynamic analysis. Uncertain parameters included anatomical features, material properties, hemodynamic conditions, and procedural variables. A surrogate model was constructed with Gaussian-process regression, and probabilistic assessment was conducted via quasi-Monte Carlo analysis. Sensitivity analysis identified key parameters influencing model outputs. The surrogate model accurately predicted device diameter (mean relative error <1%), with balloon expansion volume and stent-frame material properties being the most influential. Hemodynamic predictions exhibited greater uncertainty, with effective orifice area and pressure gradient showing deviations beyond the 5% validation threshold. This study establishes a framework for UQ in patient-specific TAVI modeling, demonstrating reliable device deployment predictions. The findings support integrating in silico models into clinical decision-making, benefiting clinicians, manufacturers, and regulatory bodies. This study is complemented by a first part dedicated to the discrete validation of the patient-specific TAVI model against clinical data.
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