Uncertainty quantification of acceleration-induced 4D Flow MRI variability propagation into image-based computational aortic hemodynamics.

4D Flow MRI is widely used to define patient-specific boundary conditions for CFD models. To ensure clinical feasibility, scan times are often reduced using accelerated acquisition strategies, which may introduce additional uncertainty in the measured velocity fields. This study quantifies how additional variability observed with increasing acceleration propagates through image-based CFD workflows and affects the reliability of derived hemodynamic biomarkers. Thirteen healthy volunteers underwent one reference Q Flow and six 4D Flow MRI acquisitions with acceleration factors (AF) of 3 to 18 on a clinical 1.5T scanner. Patient-specific CFD models of the aortic arch were generated for each dataset. Uncertainty propagation was analyzed in three steps: (1) comparison of MRI-derived inflow velocities between accelerated 4D Flow MRI and reference, (2) evaluation of velocity deviations throughout the numerical domain, and (3) sensitivity analysis of CFD-derived hemodynamic parameters, i.e. shear stresses, turbulence metrics, helicity and energy loss. Relative errors in mean MRI inflow velocity remained below 10% for AF≤12 but increased at higher acceleration. While propagated velocity errors in the ascending aorta were comparable to inflow-level deviations, discrepancies amplified in the descending aorta. A parameter-dependent robustness hierarchy was identified: Velocity and laminar shear stresses exhibited lowest (<30%), turbulence-related parameters and energy loss showed intermediate (40-70%), and helicity demonstrated highest sensitivity (>80%). This workflow-specific sensitivity remained consistent across acceleration levels. Thus, the reliability of CFD-derived biomarkers is driven more strongly by intrinsic parameter sensitivity than by acceleration alone, and this study provides an evaluation of parameter-dependent, acceleration-associated evaluation of hemodynamic parameters under given in-vivo acquisition conditions.