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Using Digital Image Correlation to Characterize Local Strains on Vascular Tissue Specimens
Published on: January 24, 2016
Novel volumetric strain energy function modeling of the dependence of aortic compressibility on smooth muscle state
Yuxin Zhang1, Yiwen Wang2, Lijie Zhou2
1College of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, PR China.
Abstract:
The active mechanical behavior of the vascular system is critical to circulatory homeostasis as a hemodynamic adaptive regulatory mechanism. Current mainstream vascular mechanics models focus on investigating the mechanical contribution of collagen and elastic fibers while ignoring the key variable of smooth muscle status. This limits their realism and clinical predictive power in simulating physiopathological remodeling of the vasculature. To quantify the effect of smooth muscle state on aortic wall compressibility and to characterize its regulatory ability, a novel state-dependent volumetric strain energy function model was proposed; based on the classical pressure-volume response experiments, the tissue compressibility behaviors under different smooth muscle activation states were quantitatively characterized, and it was confirmed that tissue compressibility was negatively correlated with smooth muscle activation state (compressibility was higher in the non-responsive samples); a two-parameter co-calibration scheme was adopted to simultaneously identify the state-dependent bulk modulus (Kx) and compressibility factor (α), and successfully established the three types of smooth muscle activation states: relaxation (Kr=6.46 MPa, αr=12.73), normal tension (Kn=6.95 MPa, αn=20.25), and contraction (Kc=9.83 MPa, αc=42.07). The closed-loop validation of the experiment and the model shows that the model achieves effective distinction of the compressibility response of the smooth muscle state, which provides a multi-state modeling strategy for vascular biomechanical modeling and has important theoretical value and clinical significance for the study of the vascular disease mechanism and the optimization of endovascular treatment devices.
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