ArticleJournal of the mechanical behavior of biomedical materials2017
A new inverse method for estimation of in vivo mechanical properties of the aortic wall.
Article in Journal of the mechanical behavior of biomedical materials, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- An Experimental and Computational Investigation to Establish the Mechanical Behaviour of Paediatric Aortic Coarctation Tissue.Annals of biomedical engineering · 2026Article
- Investigating the role of structural wall stress in aortic growth prognosis in acute uncomplicated type B aortic dissection.Biomechanics and modeling in mechanobiology · 2025Article
- Estimating nonlinear anisotropic properties of healthy and aneurysm ascending aortas using magnetic resonance imaging.Biomechanics and modeling in mechanobiology · 2025Article
- Non-invasive estimation of material properties of normal and dissected human ascending aortasFrontiers in bioengineering and biotechnology · 2025Article
- Biomechanical stress analysis of Type-A aortic dissection at pre-dissection, post-dissection, and post-repair states.Computers in biology and medicine · 2025Article
- Temporal geometric mapping defines morphoelastic growth model of Type B aortic dissection evolution.Computers in biology and medicine · 2024Article
- Layer-specific biomechanical and histological properties of normal and dissected human ascending aortas.Heliyon · 2024Article
- On the Material Constitutive Behavior of the Aortic Root in Patients with Transcatheter Aortic Valve Implantation.Cardiovascular engineering and technology · 2024Article
- Effect of Nonlinear Hyperelastic Property of Arterial Tissues on the Pulse Wave Velocity Based on the Unified-Fiber-Distribution (UFD) Model.Annals of biomedical engineering · 2023Article
- PyTorch-FEA: Autograd-enabled finite element analysis methods with applications for biomechanical analysis of human aorta.Computer methods and programs in biomedicine · 2023Article
- Biomechanical Characterisation of Thoracic Ascending Aorta with Preserved Pre-Stresses.Bioengineering (Basel, Switzerland) · 2023Article
- Inverse material parameter estimation of patient-specific finite element models at the carotid bifurcation: The impact of excluding the zero-pressure configuration and residual stress.International journal for numerical methods in biomedical engineering · 2023Article
- Image-Based Finite Element Modeling Approach for Characterizing In Vivo Mechanical Properties of Human Arteries.Journal of functional biomaterials · 2022Review
- Engineering analysis of aortic wall stress and root dilatation in the V-shape surgery for treatment of ascending aortic aneurysms.Interactive cardiovascular and thoracic surgery · 2022Article
- Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications.Applied sciences (Basel, Switzerland) · 2022Article
- A machine learning model to estimate myocardial stiffness from EDPVR.Scientific reports · 2022Article
- Uncertainty quantification in subject-specific estimation of local vessel mechanical properties.International journal for numerical methods in biomedical engineering · 2021Article
- Surrogate models based on machine learning methods for parameter estimation of left ventricular myocardium.Royal Society open science · 2021Article
- A generic physics-informed neural network-based constitutive model for soft biological tissues.Computer methods in applied mechanics and engineering · 2020Article
- The Impact of Self-Expandable Transcatheter Aortic Valve Replacement on Concomitant Functional Mitral Regurgitation: A Comprehensive Engineering Analysis.Structural heart : the journal of the Heart Team · 2020Article
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3 authors.
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Abstract
The aortic wall is always loaded in vivo, which makes it challenging to estimate the material parameters of its nonlinear, anisotropic constitutive equation from in vivo image data. Previous approaches largely relied on either computationally expensive finite element models or simplifications of the geometry or material models. In this study, we investigated a new inverse method based on aortic wall stress computation. This approach consists of the following two steps: (1) computing an "almost true" stress field from the in vivo geometries and loading conditions, (2) building an objective function based on the "almost true" stress fields, constitutive equations and deformation relations, and estimating the material parameters by minimizing the objective function. The method was validated through numerical experiments by using the in vivo data from four ascending aortic aneurysm (AsAA) patients. The results demonstrated that the method is computationally efficient. This novel approach may facilitate the personalized biomechanical analysis of aortic tissues in clinical applications, such as in the rupture risk analysis of ascending aortic aneurysms.
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