ArticleScientific reports2019
Identification of in vivo nonlinear anisotropic mechanical properties of ascending thoracic aortic aneurysm from patient-specific CT scans.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Holodiastolic Flow Reversal in the Descending Aorta: A Marker of Concomitant Acute Myocarditis and Aortitis in Children-A Case Series: Response to the Letter to the Editor.Pediatric cardiology · 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
- Wall Tensile Stress Maps of Human Aneurysmal Aorta Demonstrate a High Biaxiality Ratio Corresponds with Wall Tissue Microstructure and Local Oxidative Stress Response Distinctly for Bicuspid and Tricuspid Aortic Valve Patients.Annals of biomedical engineering · 2025Article
- An Image-Based Computational Framework to Evaluate the Material Stiffness of Arterial Tissue With High-Resolution Magnetic Resonance Imaging.Journal of biomechanical engineering · 2025Article
- Inverse finite element identification of murine aortic material properties:Computer methods in biomechanics and biomedical engineering · 2025Article
- The Influence of Material Properties and Wall Thickness on Predicted Wall Stress in Ascending Aortic Aneurysms: A Finite Element Study.Cardiovascular engineering and technology · 2025Article
- Estimating nonlinear anisotropic properties of healthy and aneurysm ascending aortas using magnetic resonance imaging.Biomechanics and modeling in mechanobiology · 2025Article
- Aortic tissue stiffness and tensile strength are correlated with density changes following proteolytic treatment.Journal of biomechanics · 2024Article
- PyTorch-FEA: Autograd-enabled finite element analysis methods with applications for biomechanical analysis of human aorta.Computer methods and programs in biomedicine · 2023Article
- Effective data sampling strategies and boundary condition constraints of physics-informed neural networks for identifying material properties in solid mechanics.Applied mathematics and mechanics · 2023Article
- Uncertainty Quantification in the In Vivo Image-Based Estimation of Local Elastic Properties of Vascular Walls.Journal of cardiovascular development and disease · 2023Article
- An image-based approach for the estimation of arterial local stiffnessFrontiers in bioengineering and biotechnology · 2023Article
- Characterizing atherosclerotic tissues:Frontiers in bioengineering and biotechnology · 2023Article
- Image-Based Finite Element Modeling Approach for Characterizing In Vivo Mechanical Properties of Human Arteries.Journal of functional biomaterials · 2022Review
- Medical Image-Based Computational Fluid Dynamics and Fluid-Structure Interaction Analysis in Vascular Diseases.Frontiers in bioengineering and biotechnology · 2022Review
- An inverse method for mechanical characterization of heterogeneous diseased arteries using intravascular imaging.Scientific reports · 2021Article
- Relative strain is a novel predictor of aneurysmal degeneration of the thoracic aorta: An ex vivo mechanical study.JVS-vascular science · 2021Article
- A generic physics-informed neural network-based constitutive model for soft biological tissues.Computer methods in applied mechanics and engineering · 2020Article
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Authors and funding
8 authors.
Funding
Abstract
Accurate identification of in vivo nonlinear, anisotropic mechanical properties of the aortic wall of individual patients remains to be one of the critical challenges in the field of cardiovascular biomechanics. Since only the physiologically loaded states of the aorta are given from in vivo clinical images, inverse approaches, which take into account of the unloaded configuration, are needed for in vivo material parameter identification. Existing inverse methods are computationally expensive, which take days to weeks to complete for a single patient, inhibiting fast feedback for clinicians. Moreover, the current inverse methods have only been evaluated using synthetic data. In this study, we improved our recently developed multi-resolution direct search (MRDS) approach and the computation time cost was reduced to 1~2 hours. Using the improved MRDS approach, we estimated in vivo aortic tissue elastic properties of two ascending thoracic aortic aneurysm (ATAA) patients from pre-operative gated CT scans. For comparison, corresponding surgically-resected aortic wall tissue samples were obtained and subjected to planar biaxial tests. Relatively close matches were achieved for the in vivo-identified and ex vivo-fitted stress-stretch responses. It is hoped that further development of this inverse approach can enable an accurate identification of the in vivo material parameters from in vivo image data.
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