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Updated: Feb 4, 2026

In vitro Assessment of Aortic Regurgitation Using Four-Dimensional Flow Magnetic Resonance Imaging
Published on: February 25, 2022
Validation of pressure drop assessment using 4D flow MRI-based turbulence production in various shapes of aortic
Hojin Ha1,2,3, John-Peder Kvitting2,3,4, Petter Dyverfeldt2,3
1Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon, Republic of Korea.
Purpose:
To validate pressure drop measurements using 4D flow MRI-based turbulence production in various shapes of stenotic stenoses.
Methods:
In vitro flow phantoms with seven different 3D-printed aortic valve geometries were constructed and scanned with 4D flow MRI with six-directional flow encoding (ICOSA6). The pressure drop through the valve was non-invasively predicted based on the simplified Bernoulli, the extended Bernoulli, the turbulence production, and the shear-scaling methods. Linear regression and agreement of the predictions with invasively measured pressure drop were analyzed.
Results:
All pressure drop predictions using 4D Flow MRI were linearly correlated to the true pressure drop but resulted in different regression slopes. The regression slope and 95% limits of agreement for the simplified Bernoulli method were 1.35 and 11.99 ± 21.72 mm Hg. The regression slope and 95% limits of agreement for the extended Bernoulli method were 1.02 and 0.74 ± 8.48 mm Hg. The regression slope and 95% limits of agreement for the turbulence production method were 0.89 and 0.96 ± 8.01 mm Hg. The shear-scaling method presented good correlation with an invasively measured pressure drop, but the regression slope varied between 0.36 and 1.00 depending on the shear-scaling coefficient.
Conclusion:
The pressure drop assessment based on the turbulence production method agrees well with the extended Bernoulli method and invasively measured pressure drop in various shapes of the aortic valve. Turbulence-based pressure drop estimation can, as a complement to the conventional Bernoulli method, play a role in the assessment of valve diseases.
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