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Corso P, Obrist D. On the role of aortic valve architecture for physiological hemodynamics and valve replacement, Part I: Flow configuration and vortex dynamics. Comput Biol Med 2024; 176:108526. [PMID: 38749328 DOI: 10.1016/j.compbiomed.2024.108526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 04/22/2024] [Accepted: 04/26/2024] [Indexed: 05/31/2024]
Abstract
Aortic valve replacement has become an increasing concern due to the rising prevalence of aortic stenosis in an ageing population. Existing replacement options have limitations, necessitating the development of improved prosthetic aortic valves. In this study, flow characteristics during systole in a stenotic aortic valve case are compared with those downstream of two newly designed surgical bioprosthetic aortic valves (BioAVs). To do so, advanced three-dimensional fluid-structure interaction simulations are conducted and dedicated analysis methods to investigate jet flow configuration and vortex dynamics are developed. Our findings reveal that the stenotic case maintains a high jet flow eccentricity due to a fixed orifice geometry, resulting in flow separation and increased vortex stretching and tilting in the commissural low-flow regions. One BioAV design introduces non-axisymmetric leaflet motion, which reduces the maximum jet velocity and forms more vortical structures. The other BioAV design produces a fixed symmetric triangular jet shape due to non-moving leaflets and exhibits favourable vorticity attenuation, revealed by negative temporally and spatially averaged projected vortex stretching values, and significantly reduced drag. Therefore, this study highlights the benefits of custom-designed aortic valves in the context of their replacement through comprehensive and novel flow analyses. The results emphasise the importance of analysing jet flow, vortical structures, momentum balance and vorticity transport for thoroughly evaluating aortic valve performance.
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Affiliation(s)
- Pascal Corso
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
| | - Dominik Obrist
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
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Corso P, Obrist D. On the role of aortic valve architecture for physiological hemodynamics and valve replacement, Part II: Spectral analysis and anisotropy. Comput Biol Med 2024; 176:108552. [PMID: 38754219 DOI: 10.1016/j.compbiomed.2024.108552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 04/14/2024] [Accepted: 04/29/2024] [Indexed: 05/18/2024]
Abstract
Severe aortic valve stenosis can lead to heart failure and aortic valve replacement (AVR) is the primary treatment. However, increasing prevalence of aortic stenosis cases reveal limitations in current replacement options, necessitating improved prosthetic aortic valves. We investigate flow disturbances downstream of severe aortic stenosis and two bioprosthetic aortic valve (BioAV) designs using advanced energy-based analyses. Three-dimensional high-fidelity fluid-structure interaction simulations have been conducted and a dedicated and novel spectral analysis has been developed to characterise the kinetic energy (KE) carried by eddies in the wavenumber space. In addition, new field quantities, i.e. modal KE anisotropy intensity as well as normalised helicity intensity, are introduced. Spectral analysis shows kinetic energy (KE) decay variations, with the stenotic case aligning with Kolmogorov's theory, while BioAV cases differing. We explore the impact of flow helicity on KE transfer and decay in BioAVs. Probability distributions of modal KE anisotropy unveil flow asymmetries in the stenotic and one BioAV cases. Moreover, an inverse correlation between temporally averaged modal KE anisotropy and normalised instantaneous helicity intensity is noted, with the coefficient of determination varying among the valve configurations. Leaflet dynamics analysis highlights a stronger correlation between flow and biomechanical KE anisotropy in one BioAV due to higher leaflet displacement magnitude. These findings emphasise the role of valve architecture in aortic turbulence as well as its importance for BioAV performance and energy-based design enhancement.
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Affiliation(s)
- Pascal Corso
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.
| | - Dominik Obrist
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
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Tsolaki E, Corso P, Zboray R, Avaro J, Appel C, Liebi M, Bertazzo S, Heinisch PP, Carrel T, Obrist D, Herrmann IK. Multiscale multimodal characterization and simulation of structural alterations in failed bioprosthetic heart valves. Acta Biomater 2023; 169:138-154. [PMID: 37517619 DOI: 10.1016/j.actbio.2023.07.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 06/30/2023] [Accepted: 07/24/2023] [Indexed: 08/01/2023]
Abstract
Calcific degeneration is the most frequent type of heart valve failure, with rising incidence due to the ageing population. The gold standard treatment to date is valve replacement. Unfortunately, calcification oftentimes re-occurs in bioprosthetic substitutes, with the governing processes remaining poorly understood. Here, we present a multiscale, multimodal analysis of disturbances and extensive mineralisation of the collagen network in failed bioprosthetic bovine pericardium valve explants with full histoanatomical context. In addition to highly abundant mineralized collagen fibres and fibrils, calcified micron-sized particles previously discovered in native valves were also prevalent on the aortic as well as the ventricular surface of bioprosthetic valves. The two mineral types (fibres and particles) were detectable even in early-stage mineralisation, prior to any macroscopic calcification. Based on multiscale multimodal characterisation and high-fidelity simulations, we demonstrate that mineral occurrence coincides with regions exposed to high haemodynamic and biomechanical indicators. These insights obtained by multiscale analysis of failed bioprosthetic valves serve as groundwork for the evidence-based development of more durable alternatives. STATEMENT OF SIGNIFICANCE: Bioprosthetic valve calcification is a well-known clinically significant phenomenon, leading to valve failure. The nanoanalytical characterisation of bioprosthetic valves gives insights into the highly abundant, extensive calcification and disorganization of the collagen network and the presence of calcium phosphate particles previously reported in native cardiovascular tissues. While the collagen matrix mineralisation can be primarily attributed to a combination of chemical and mechanical alterations, the calcified particles are likely of host cellular origin. This work presents a straightforward route to mineral identification and characterization at high resolution and sensitivity, and with full histoanatomical context and correlation to hemodynamic and biomechanical indicators, hence providing design cues for improved bioprosthetic valve alternatives.
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Affiliation(s)
- Elena Tsolaki
- Laboratory for Particles-Biology Interactions, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), Lerchenfeldstrasse 5, St. Gallen 9014, Switzerland; Nanoparticle Systems Engineering Laboratory, Department of Mechanical and Process Engineering, Institute of Energy and Process Engineering, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland
| | - Pascal Corso
- ARTORG Center for Biomedical Engineering Research, University of Bern, Freiburgstrasse 3, Bern 3010, Switzerland
| | - Robert Zboray
- Center for X-Ray Analytics, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), Ueberlandstrasse 129, Duebendorf 8600, Switzerland
| | - Jonathan Avaro
- Center for X-Ray Analytics, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), Ueberlandstrasse 129, Duebendorf 8600, Switzerland
| | | | - Marianne Liebi
- Center for X-Ray Analytics, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), Ueberlandstrasse 129, Duebendorf 8600, Switzerland; Paul Scherrer Institute, PSI, Villigen 5232, Switzerland; Department of Physics, Chalmers University of Technology, Gothenburg 41296, Sweden
| | - Sergio Bertazzo
- Department of Medical Physics and Biomedical Engineering, University College London, WC1E 6BT, UK; London Centre for Nanotechnology, University College London, WC1E 6BT, UK
| | - Paul Philipp Heinisch
- Department of Cardiovascular Surgery, Inselspital, University of Bern, Freiburgstrasse 18, Bern 3010, Switzerland; Department of Congenital and Pediatric Heart Surgery, German Heart Center Munich, Technische Universität München, Germany
| | - Thierry Carrel
- Department of Cardiovascular Surgery, Inselspital, University of Bern, Freiburgstrasse 18, Bern 3010, Switzerland; Department of Cardiac Surgery, University Hospital Zurich (USZ), Rämistrasse 101, Zürich 8091, Switzerland.
| | - Dominik Obrist
- ARTORG Center for Biomedical Engineering Research, University of Bern, Freiburgstrasse 3, Bern 3010, Switzerland.
| | - Inge K Herrmann
- Laboratory for Particles-Biology Interactions, Department of Materials Meet Life, Swiss Federal Laboratories for Materials Science and Technology (Empa), Lerchenfeldstrasse 5, St. Gallen 9014, Switzerland; Nanoparticle Systems Engineering Laboratory, Department of Mechanical and Process Engineering, Institute of Energy and Process Engineering, ETH Zurich, Sonneggstrasse 3, Zurich 8092, Switzerland.
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Zhang J, Rothenberger SM, Brindise MC, Markl M, Rayz VL, Vlachos PP. Wall Shear Stress Estimation for 4D Flow MRI Using Navier-Stokes Equation Correction. Ann Biomed Eng 2022; 50:1810-1825. [PMID: 35943617 PMCID: PMC10263099 DOI: 10.1007/s10439-022-02993-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 06/09/2022] [Indexed: 12/30/2022]
Abstract
This study introduces a novel wall shear stress (WSS) estimation method for 4D flow MRI. The method improves the WSS accuracy by using the reconstructed pressure gradient and the flow-physics constraints to correct velocity gradient estimation. The method was tested on synthetic 4D flow data of analytical Womersley flow and flow in cerebral aneurysms and applied to in vivo 4D flow data acquired in cerebral aneurysms and aortas. The proposed method's performance was compared to the state-of-the-art method based on smooth-spline fitting of velocity profile and the WSS calculated from uncorrected velocity gradient. The proposed method improved the WSS accuracy by as much as 100% for the Womersley flow and reduced the underestimation of mean WSS by 39 to 50% for the synthetic aneurysmal flow. The predicted mean WSS from the in vivo aneurysmal data using the proposed method was 31 to 50% higher than the other methods. The predicted aortic WSS using the proposed method was 3 to 6 times higher than the other methods and was consistent with previous CFD studies and the results from recently developed methods that take into account the limited spatial resolution of 4D flow MRI. The proposed method improves the accuracy of WSS estimation from 4D flow MRI, which can help predict blood vessel remodeling and progression of cardiovascular diseases.
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Affiliation(s)
- Jiacheng Zhang
- School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, USA
| | - Sean M Rothenberger
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, 47907, USA
| | - Melissa C Brindise
- Department of Mechanical Engineering, Pennsylvania State University, University Park, PA, 16802, USA
| | - Michael Markl
- Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
- McCormick School of Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Vitaliy L Rayz
- School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, USA
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, 47907, USA
| | - Pavlos P Vlachos
- School of Mechanical Engineering, Purdue University, West Lafayette, IN, 47907, USA.
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, 47907, USA.
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Kazemi A, Padgett DA, Callahan S, Stoddard M, Amini AA. Relative pressure estimation from 4D flow MRI using generalized Bernoulli equation in a phantom model of arterial stenosis. MAGMA (NEW YORK, N.Y.) 2022; 35:733-748. [PMID: 35175449 DOI: 10.1007/s10334-022-01001-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 01/07/2022] [Accepted: 01/09/2022] [Indexed: 06/14/2023]
Abstract
OBJECTIVE Arterial stenosis is a significant cardiovascular disease requiring accurate estimation of the pressure gradients for determining hemodynamic significance. In this paper, we propose Generalized Bernoulli Equation (GBE) utilizing interpolated-based method to estimate relative pressures using streamlines and pathlines from 4D Flow MRI. METHODS 4D Flow MRI data in a stenotic phantom model and computational fluid dynamics simulated velocities generated under identical flow conditions were processed by Generalized Bernoulli Equation (GBE), Reduced Bernoulli Equations (RBE), as well as the Simple Bernoulli Equation (SBE) which is clinically prevalent. Pressures derived from 4D flow MRI and noise corrupted CFD velocities were compared with pressures generated directly with CFD as well as pressures obtained using Millar catheters under identical flow conditions. RESULTS It was found that SBE and RBE methods underestimated the relative pressure for lower flow rates while overestimating the relative pressure at higher flow rates. Specifically, compared to the reference pressure, SBE underestimated the maximum relative pressure by 22[Formula: see text] for a pulsatile flow data with peak flow rate [Formula: see text] and overestimated by around 40[Formula: see text] when [Formula: see text]. In contrast, for GBE method the relative pressure values were overestimated by 15[Formula: see text] with [Formula: see text]and around 10[Formula: see text] with [Formula: see text]. CONCLUSION GBE methods showed robust performance to additive image noise compared to other methods. Our findings indicate that GBE pressure estimation over pathlines attains the highest level of accuracy compared to GBE over streamlines, and the SBE and RBE methods.
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Affiliation(s)
- Amirkhosro Kazemi
- Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA
- Robley Rex VA Medical Center, Louisville, KY, USA
| | | | - Sean Callahan
- Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA
- Robley Rex VA Medical Center, Louisville, KY, USA
| | - Marcus Stoddard
- Cardiovascular Division, University of Louisville, Louisville, KY, USA
- Robley Rex VA Medical Center, Louisville, KY, USA
| | - Amir A Amini
- Electrical and Computer Engineering, University of Louisville, Louisville, KY, USA.
- Robley Rex VA Medical Center, Louisville, KY, USA.
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