title: A combination of experimental and numerical methods to investigate the role of strain rate on the mechanical properties and collagen fiber orientations of the healthy and atherosclerotic human coronary arteries.
abstract: Atherosclerosis enables to alter not only the microstructural but also the physical properties of the arterial walls by plaque forming. Few studies so far have been conducted to calculate the isotropic or anisotropic mechanical properties of the healthy and atherosclerotic human coronary arteries. To date there is a paucity of knowledge on the mechanical response of the arteries under different strain rates. Therefore, the objective of the concurrent research was to comprehend whether the alteration in the strain rates of the human atherosclerotic arteries in comparison with the healthy ones contribute to the biomechanical behaviors. To do this, healthy and atherosclerotic human coronary arteries were removed from 18 individuals during autopsy. Histological analyses by both an expert histopathologist and an imaged-based recognizer software were performed to figure out the average angle of collagen fibers in the healthy and atherosclerotic arterial walls. Thereafter, the samples were subjected to 3 diverse strain rates, i.e., 5, 20, and 50 mm/min, until the material failure occurs. The stress-strain diagrams of the arterial tissues were calculated in order to capture their linear elastic and nonlinear hyperelastic mechanical properties. In addition, Artificial Neural Networks (ANNs) was employed to predict the alteration of mean angle of collagen fibers during load bearing up to failure. The findings suggest that strain rate has a significant (p < 0.05) role in the linear elastic and nonlinear hyperelastic mechanical properties as well as the mean angle of collagen fibers of the atherosclerotic arteries, whereas no specific impact on the healthy ones. Furthermore, the mean angle of collagen fibers during the load bearing up to the failure at each strain rate was well predicted by the proposed ANNs code.
authors: a Tissue Engineering and Biological Systems Research Laboratory, School of Mechanical Engineering, Iran University of Science and Technology , Tehran , Iran.|b Basir Health Research Center , Tehran , Iran.
authors: Alireza
authors: A
authors: Karimi
authors: c Department of Biomedical Engineering , Amirkabir University of Technology , Tehran , Iran.
authors: Seyyed Mohammadali
authors: SM
authors: Rahmati
authors: d Department of Mechanical Engineering , Kyushu University , Nishi-ku , Fukuoka , Japan.
authors: Toshihiro
authors: T
authors: Sera
authors: d Department of Mechanical Engineering , Kyushu University , Nishi-ku , Fukuoka , Japan.
authors: Susumu
authors: S
authors: Kudo
authors: a Tissue Engineering and Biological Systems Research Laboratory, School of Mechanical Engineering, Iran University of Science and Technology , Tehran , Iran.
authors: Mahdi
authors: M
authors: Navidbakhsh
mesh_terms: D050197:Atherosclerosis / Q000378:metabolism*; D003094:Collagen / Q000378:metabolism*; D003331:Coronary Vessels / Q000378:metabolism* / Q000503:physiopathology*; D055119:Elastic Modulus / Q000502:physiology; D006801:Humans; D066298:In Vitro Techniques; D016571:Neural Networks, Computer; D013314:Stress, Mechanical
chemical_list: D003094:Collagen
keywords: Artificial Neural Networks; Mooney-Rivlin; atherosclerosis; collagen fiber; coronary artery; elastic modulus; mechanical properties