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4D Flow MRI quantification of blood flow patterns, turbulence and pressure drop in normal and stenotic prosthetic heart valves

Ha, Hojin,Kvitting, John-Peder Escobar,Dyverfeldt, Petter,Ebbers, Tino Elsevier 2019 Magnetic resonance imaging Vol.55 No.-
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Abstract Purpose To assess valvular flow characteristics and pressure drop in a variety of normal and stenotic prosthetic heart valves (PHVs) using 4D Flow MRI. Materials and methods In-vitro flow phantoms with four different PHVs were studied: Medtronic-Hall tilting disc, St. Jude Medical standard bileaflet (STJM), Medtronic CoreValve Evolut R and Edwards SAPIEN 3. The valvular flow characteristics were investigated in normal and stenotic PHVs by using 4D Flow MRI. Results The results showed that each valve provided a different amount of signal loss in the 4D Flow MRI. The defect size of the signal loss from each valve was 37.5 mm, 39.0 mm, 37.5 mm and 51.0 mm for the Tilting disk, STJM, SAPIEN 3 and CoreValve, respectively. The 4D Flow MRI-based estimation of the elevation of the pressure drop through the stenotic PHV using both Bernoulli-based and turbulence-based methods correlated well with the true values for the Tilting disc, STJM and SAPIEN 3 valve. However, the obstructive hemodynamics in the stenotic CoreValve was not clearly identified due to the large signal void from the long struts, resulting in a severe underestimation of the pressure drop using 4D Flow MRI. Conclusion The Tilting disc, STJM and SAPIEN 3 valves provided reasonable estimates of peak velocity, turbulence production and the corresponding pressure drop. In contrast, the large strut of the CoreValve and corresponding signal void prevented accurate measurements of the velocity and turbulence production; therefore, 4D Flow MRI prediction of the pressure drop through the CoreValve was not feasible.
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Non-invasive estimation of relative pressure in turbulent flow using virtual work-energy

Marlevi, David,Ha, Hojin,Dillon-Murphy, Desmond,Fernandes, Joao F.,Fovargue, Daniel,Colarieti-Tosti, Massimiliano,Larsson, Matilda,Lamata, Pablo,Figueroa, C. Alberto,Ebbers, Tino,Nordsletten, David A. Elsevier 2020 Medical image analysis Vol.60 No.-
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Abstract Vascular pressure differences are established risk markers for a number of cardiovascular diseases. Relative pressures are, however, often driven by turbulence-induced flow fluctuations, where conventional non-invasive methods may yield inaccurate results. Recently, we proposed a novel method for non-turbulent flows, νWERP, utilizing the concept of virtual work-energy to accurately probe relative pressure through complex branching vasculature. Here, we present an extension of this approach for turbulent flows: νWERP-t. We present a theoretical method derivation based on flow covariance, quantifying the impact of flow fluctuations on relative pressure. νWERP-t is tested on a set of in-vitro stenotic flow phantoms with data acquired by 4D flow MRI with six-directional flow encoding, as well as on a patient-specific in-silico model of an acute aortic dissection. Over all tests νWERP-t shows improved accuracy over alternative energy-based approaches, with excellent recovery of estimated relative pressures. In particular, the use of a guaranteed divergence-free virtual field improves accuracy in cases where turbulent flows skew the apparent divergence of the acquired field. With the original νWERP allowing for assessment of relative pressure into previously inaccessible vasculatures, the extended νWERP-t further enlarges the method's clinical scope, underlining its potential as a novel tool for assessing relative pressure in-vivo. Highlights <UL> <LI> vWERP-t uses virtual work-energy to accurately assess turbulent relative pressure. </LI> <LI> In-vitro, vWERP-t shows 1:1 agreement with invasive measurements of relative pressure. </LI> <LI> In transient flow, vWERP-t shows significant improvement compared to other approaches. </LI> <LI> vWERP-t guarantees divergence free flow even in turbulent fields, improving accuracy. </LI> </UL> Graphical abstract [DISPLAY OMISSION]

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