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Ross CJ, Laurence DW, Aggarwal A, Hsu MC, Mir A, Burkhart HM, Lee CH. Bayesian Optimization-Based Inverse Finite Element Analysis for Atrioventricular Heart Valves. Ann Biomed Eng 2024; 52:611-626. [PMID: 37989903 PMCID: PMC10926997 DOI: 10.1007/s10439-023-03408-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 11/07/2023] [Indexed: 11/23/2023]
Abstract
Inverse finite element analysis (iFEA) of the atrioventricular heart valves (AHVs) can provide insights into the in-vivo valvular function, such as in-vivo tissue strains; however, there are several limitations in the current state-of-the-art that iFEA has not been widely employed to predict the in-vivo, patient-specific AHV leaflet mechanical responses. In this exploratory study, we propose the use of Bayesian optimization (BO) to study the AHV functional behaviors in-vivo. We analyzed the efficacy of Bayesian optimization to estimate the isotropic Lee-Sacks material coefficients in three benchmark problems: (i) an inflation test, (ii) a simplified leaflet contact model, and (iii) an idealized AHV model. Then, we applied the developed BO-iFEA framework to predict the leaflet properties for a patient-specific tricuspid valve under a congenital heart defect condition. We found that the BO could accurately construct the objective function surface compared to the one from a [Formula: see text] grid search analysis. Additionally, in all cases the proposed BO-iFEA framework yielded material parameter predictions with average element errors less than 0.02 mm/mm (normalized by the simulation-specific characteristic length). Nonetheless, the solutions were not unique due to the presence of a long-valley minima region in the objective function surfaces. Parameter sets along this valley can yield functionally equivalent outcomes (i.e., closing behavior) and are typically observed in the inverse analysis or parameter estimation for the nonlinear mechanical responses of the AHV. In this study, our key contributions include: (i) a first-of-its-kind demonstration of the BO method used for the AHV iFEA; and (ii) the evaluation of a candidate AHV in-silico modeling approach wherein the chordae could be substituted with equivalent displacement boundary conditions, rendering the better iFEA convergence and a smoother objective surface.
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Affiliation(s)
- Colton J Ross
- Biomechanics & Biomaterials Design Laboratory, School of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK, USA
| | | | - Ankush Aggarwal
- Glasgow Computational Engineering Centre, James Watt School of Engineering, University of Glasgow, Glasgow, UK
| | - Ming-Chen Hsu
- Department of Mechanical Engineering, Iowa State University, Ames, IA, USA
| | - Arshid Mir
- Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma, OK, USA
| | - Harold M Burkhart
- Department of Surgery, University of Oklahoma Health Sciences Center, Oklahoma, OK, USA
| | - Chung-Hao Lee
- Biomechanics & Biomaterials Design Laboratory, School of Aerospace and Mechanical Engineering, University of Oklahoma, Norman, OK, USA.
- Department of Bioengineering, University of California Riverside, Riverside, CA, USA.
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Mathur M, Meador WD, Malinowski M, Jazwiec T, Timek TA, Rausch MK. Texas TriValve 1.0 : a reverse‑engineered, open model of the human tricuspid valve. ENGINEERING WITH COMPUTERS 2022; 38:3835-3848. [PMID: 37139164 PMCID: PMC10153581 DOI: 10.1007/s00366-022-01659-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 04/13/2022] [Indexed: 05/05/2023]
Abstract
Nearly 1.6 million Americans suffer from a leaking tricuspid heart valve. To make matters worse, current valve repair options are far from optimal leading to recurrence of leakage in up to 30% of patients. We submit that a critical step toward improving outcomes is to better understand the "forgotten" valve. High-fidelity computer models may help in this endeavour. However, the existing models are limited by averaged or idealized geometries, material properties, and boundary conditions. In our current work, we overcome the limitations of existing models by (reverse) engineering the tricuspid valve from a beating human heart in an organ preservation system. The resulting finite-element model faithfully captures the kinematics and kinetics of the native tricuspid valve as validated against echocardiographic data and others' previous work. To showcase the value of our model, we also use it to simulate disease-induced and repair-induced changes to valve geometry and mechanics. Specifically, we simulate and compare the effectiveness of tricuspid valve repair via surgical annuloplasty and via transcatheter edge-to-edge repair. Importantly, our model is openly available for others to use. Thus, our model will allow us and others to perform virtual experiments on the healthy, diseased, and repaired tricuspid valve to better understand the valve itself and to optimize tricuspid valve repair for better patient outcomes.
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Affiliation(s)
- Mrudang Mathur
- Department of Mechanical Engineering, University of Texas at Austin, Austin, TX 78712, USA
| | - William D. Meador
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX 78712, USA
| | - Marcin Malinowski
- Cardiothoracic Surgery, Spectrum Health, Grand Rapids, MI 49503, USA
- Department of Cardiac Surgery, Medical University of Silesia School of Medicine in Katowice, Katowice, Poland
| | - Tomasz Jazwiec
- Cardiothoracic Surgery, Spectrum Health, Grand Rapids, MI 49503, USA
- Department of Cardiac, Vascular and Endovascular Surgery and Transplantology, Medical University of Silesia in Katowice, Silesian Centre for Heart Diseases, Zabrze, Poland
| | - Tomasz A. Timek
- Cardiothoracic Surgery, Spectrum Health, Grand Rapids, MI 49503, USA
| | - Manuel K. Rausch
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX 78712, USA
- Department of Aerospace Engineering & Engineering Mechanics, University of Texas at Austin, Austin, TX 78712, USA
- Oden Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX 78712, USA
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