Uncertainty quantification for patient-specific domain in virtual aortic procedures: application to thoracic endovascular aortic repair

Simulating medical procedures requires accounting for inherent uncertainty in many numerical model parameters, such as material properties. Evaluating the impact of these uncertainties is crucial for identifying parameters needing precise definition and correctly interpreting simulation results. This study explores how uncertainties in modelling the aorta affect finite element outcomes of a thoracic endovascular aortic repair (TEVAR) procedure. Based on literature data, aortic wall thickness and mechanical properties were identified as the most uncertain. The aorta was modelled using shell elements with homogeneous thickness and assumed to behave as a linear elastic isotropic material. A design of experiments approach was used for uncertainty quantification and sensitivity analysis: wall thickness and Young's modulus were varied over 11 levels in a full factorial design, resulting in 121 simulations. Uncertainty was quantified using statistical metrics such as mean, standard deviation, coefficient of variation, and 95% confidence intervals. Results indicate wall thickness significantly affects aortic wall stress (σ_aorta), with minimal influence on stent stress (σ_stent) and device opening area (OA). Conversely, Young's modulus has limited impact on σ_aorta but affects σ_stent and OA to a greater extent. The highest uncertainty was observed in σ_aorta (~ 25% coefficient of variation), while σ_stent and OA showed lower variability (2.6% and 6.9%, respectively). These findings suggest that, in this model, accurate wall thickness definition is more critical than precise Young's modulus for reducing uncertainty in wall stress predictions. Therefore, literature-based averages for Young's modulus may be sufficient for simulating this procedure.