ArticleJournal of the mechanical behavior of biomedical materials2022
Linking collagen fiber architecture to tissue-level biaxial mechanical behaviors of porcine semilunar heart valve cusps.
Article in Journal of the mechanical behavior of biomedical materials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 11 citations in OpenAlex.
- Pyriphenone modification of glutaraldehyde pretreated bovine pericardium mitigates advanced glycation end products, calcification, and platelet adhesion.Acta biomaterialia · 2026Article
- Full-Field Assessment of Geometry and Collagenous Architecture of Porcine Valve Leaflets via Laser Micrometry and Quantitative Polarized Light Imaging.Journal of biophotonics · 2025Article
- Strategies for Development of Synthetic Heart Valve Tissue Engineering Scaffolds.Progress in materials science · 2023Article
- Focusing on the Native Matrix Proteins in Calcific Aortic Valve Stenosis.JACC. Basic to translational science · 2023Review
- A Bayesian constitutive model selection framework for biaxial mechanical testing of planar soft tissues: Application to porcine aortic valves.Journal of the mechanical behavior of biomedical materials · 2023Article
- Strain energy density as a Gaussian process and its utilization in stochastic finite element analysis: application to planar soft tissues.Computer methods in applied mechanics and engineering · 2023Article
- Benchtop characterization of the tricuspid valve leaflet pre-strains.Acta biomaterialia · 2022Article
- Ex vivo experimental characterizations for understanding the interrelationship between tissue mechanics and collagen microstructure of porcine mitral valve leaflets.Journal of the mechanical behavior of biomedical materials · 2022Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
Abstract
The semilunar heart valves regulate the blood flow from the ventricles to the major arteries through the opening and closing of the scallop shaped cusps. These cusps are composed of collagen fibers that act as the primary loading-bearing component. The load-dependent collagen fiber architecture has been previously examined in the existing literature; however, these studies relied on chemical clearing and tissue modifications to observe the underlying changes in response to mechanical loads. In the present study, we address this gap in knowledge by quantifying the collagen fiber orientations and alignments of the aortic and pulmonary cusps through a multi-scale, non-destructive experimental approach. This opto-mechanical approach, which combines polarized spatial frequency domain imaging and biaxial mechanical testing, provides a greater field of view (10-25mm) and faster imaging time (45-50s) than other traditional collagen imaging techniques. The birefringent response of the collagen fibers was fit with a von Mises distribution, while the biaxial mechanical testing data was implemented into a modified full structural model for further analysis. Our results showed that the semilunar heart valve cusps are more extensible in the tissue's radial direction than the circumferential direction under all the varied biaxial testing protocols, together with greater material anisotropy among the pulmonary valve cusps compared to the aortic valve cusps. The collagen fibers were shown to reorient towards the direction of the greatest applied loading and incrementally realign with the increased applied stress. The collagen fiber architecture within the aortic valve cusps were found to be more homogeneous than the pulmonary valve counterparts, reflecting the differences in the physiological environments experienced by these two semilunar heart valves. Further, the von Mises distribution fitting highlighted the presence and contribution of two distinct fiber families for each of the two semilunar heart valves. The results from this work would provide valuable insight into connecting tissue-level mechanics to the underlying collagen fiber architecture-an essential information for the future development of high-fidelity aortic/pulmonary valve computational models.
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