Why the study?
Accelerated 4D Flow MRI acquisition strategies reduce scan times but may introduce uncertainty in measured velocity fields, and it was unclear how this variability propagates through CFD workflows to affect hemodynamic biomarkers.
How does acceleration-induced variability in 4D Flow MRI propagate into computational fluid dynamics models of aortic hemodynamics?
Cross-Sectional (n=13)
How does acceleration-induced variability in 4D Flow MRI propagate into computational fluid dynamics models of aortic hemodynamics?
Accelerated 4D Flow MRI up to an acceleration factor of 12 yields acceptable inflow velocity errors, but the reliability of downstream CFD-derived biomarkers depends heavily on the intrinsic sensitivity of the specific parameter.
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.
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Wang et al. (2026) conducted a cross-sectional in Healthy (n=13). Accelerated 4D Flow MRI (acceleration factors 3 to 18) vs. Reference Q Flow MRI was evaluated on Relative errors in mean MRI inflow velocity and sensitivity of CFD-derived hemodynamic parameters.
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