Hemodynamic Evaluation of a Biological and Mechanical Aortic Valve Prosthesis Using Patient‐Specific MRI‐Based CFD. Issue 1 (29th August 2017)

• Record Type: Journal Article
• Authors: Hellmeier, Florian; Nordmeyer, Sarah; Yevtushenko, Pavlo; Bruening, Jan; Berger, Felix; Kuehne, Titus; Goubergrits, Leonid; Kelm, Marcus
• Is Part Of: Artificial organs. Volume 42:Issue 1(2018)
• Page Start: 49
• Page End: 57
• Publication Date: 2017-08-29
• Subjects: Patient‐specific simulation -- —Aortic hemodynamics -- —Aortic valve replacement -- —Virtual intervention -- —4D flow MRI; Artificial organs -- Periodicals; 617.956
• DOI: 10.1111/aor.12955
• Languages: English
• ISSNs: 0160-564X

Abstract

Abstract: Modeling different treatment options before a procedure is performed is a promising approach for surgical decision making and patient care in heart valve disease. This study investigated the hemodynamic impact of different prostheses through patient‐specific MRI‐based CFD simulations. Ten time‐resolved MRI data sets with and without velocity encoding were obtained to reconstruct the aorta and set hemodynamic boundary conditions for simulations. Aortic hemodynamics after virtual valve replacement with a biological and mechanical valve prosthesis were investigated. Wall shear stress (WSS), secondary flow degree (SFD), transvalvular pressure drop (TPD), turbulent kinetic energy (TKE), and normalized flow displacement (NFD) were evaluated to characterize valve‐induced hemodynamics. The biological prostheses induced significantly higher WSS (medians: 9.3 vs. 8.6 Pa, P = 0.027) and SFD (means: 0.78 vs. 0.49, P = 0.002) in the ascending aorta, TPD (medians: 11.4 vs. 2.7 mm Hg, P = 0.002), TKE (means: 400 vs. 283 cm 2 /s 2, P = 0.037), and NFD (means: 0.0994 vs. 0.0607, P = 0.020) than the mechanical prostheses. The differences between the prosthesis types showed great inter‐patient variability, however. Given this variability, a patient‐specific evaluation is warranted. In conclusion, MRI‐based CFD offers an opportunity to assess the interactions between prosthesis and patient‐specific boundary conditions, which may help in optimizing surgical decision making and providing additional guidance to clinicians.