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Updated: Aug 5, 2026
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In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging
Published on: February 25, 2022
Uncertainty quantification of acceleration-induced 4D Flow MRI variability propagation into image-based computational
Tianai Wang1, Levi Juhl1, Theresa Degreif2
1Cardiovascular Engineering, Applied Medical Engineering, RWTH Aachen University, Aachen, Germany.
Computers in Biology and Medicine
|July 30, 2026
Summary
Accelerated 4D Flow MRI (magnetic resonance imaging) introduces variability in hemodynamic biomarkers. Parameter sensitivity, not just acceleration, dictates the reliability of computational fluid dynamics (CFD) results.
Area of Science:
- Cardiovascular Imaging and Hemodynamics
- Medical Physics and Engineering
Background:
- Four-dimensional Flow MRI (4D Flow MRI) is crucial for patient-specific computational fluid dynamics (CFD) models.
- Accelerated acquisition strategies in 4D Flow MRI reduce scan times but may introduce velocity field uncertainties.
- Understanding the impact of these uncertainties on derived hemodynamic biomarkers is vital for clinical feasibility.
Purpose of the Study:
- To quantify the propagation of variability from accelerated 4D Flow MRI through CFD workflows.
- To assess the impact of acceleration-induced uncertainty on the reliability of hemodynamic biomarkers.
- To establish a parameter-dependent hierarchy of robustness against acquisition acceleration.
Main Methods:
- Thirteen healthy volunteers underwent reference and accelerated (AF 3-18) 4D Flow MRI acquisitions.
- Patient-specific CFD models of the aortic arch were created for each dataset.
- Uncertainty propagation was analyzed by comparing inflow velocities, evaluating velocity deviations, and performing sensitivity analysis on CFD-derived parameters (shear stresses, turbulence, helicity, energy loss).
Main Results:
- Relative errors in mean inflow velocity remained <10% for AF≤12, increasing at higher accelerations.
- Velocity discrepancies amplified in the descending aorta compared to the ascending aorta.
- A robustness hierarchy was identified: Velocity/laminar shear stress (<30%), turbulence/energy loss (40-70%), and helicity (>80%) showed increasing sensitivity to acceleration.
Conclusions:
- The reliability of CFD-derived biomarkers is primarily influenced by intrinsic parameter sensitivity rather than acceleration alone.
- Helicity is the most sensitive parameter to acceleration-induced variability, while velocity and laminar shear stress are the most robust.
- This study provides crucial insights into acceleration-associated uncertainties for hemodynamic parameter evaluation in clinical 4D Flow MRI-CFD workflows.
