Credibility assessment of patient-specific modeling in transcatheter aortic valve implantation—Part 2: Uncertainty quantification and sensitivity analysis

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 <i>in silico</i> 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 <i>in silico</i> 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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Publication Details

Journal
APL Bioengineering
Published
2025-09-25
DOI
https://doi.org/10.1063/5.0280959
Citations
2
Primary Topic
Nuclear Engineering Thermal-Hydraulics
Type
article
Field-Weighted Citation Impact
9.99
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article

Credibility assessment of patient-specific modeling in transcatheter aortic valve implantation—Part 2: Uncertainty quantification and sensitivity analysis

Chiara Catalano, Caterina Maria Gandolfo, Stefano Cannata, Nils Götzen et al.
2 citations
APL Bioengineering
Nuclear Engineering Thermal-Hydraulics
9.99
article

Credibility assessment of patient-specific modeling in transcatheter aortic valve implantation—Part 2: Uncertainty quantification and sensitivity analysis

Chiara Catalano, Caterina Maria Gandolfo, Stefano Cannata, Nils Götzen, Salvatore Pasta, Giovanni Gentile, Roberta Scuoppo, T. Turgut
article en
2 citations

Abstract

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 <i>in silico</i> 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 <i>in silico</i> 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.

APL BioengineeringVol. 9(4)
Dr. F.P. Fischer-Stichting (Netherlands) (NL), International YMCA University of Applied Sciences (DE), Istituto Mediterraneo per i Trapianti e Terapie ad Alta Specializzazione (IT), University of Palermo (IT)
Openalex Percentile: Top 2%
Nuclear Engineering Thermal-Hydraulics
9.99
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