Computational modeling of tissue damage preceding aortic dissection: a coupled biphasic and reactive viscoelastic framework

Figures

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  Fig. 1. Methodological workflow of the integrated approach. Experimental inputs (radial tensile tests and microstructural imaging) inform the constitutive model of the solid matrix. The framework is deployed through two modeling strategies: an analytical model for parameter identification and a Finite element model (FEBio) for poromechanical validation, leading to the final mechanical characterization of the aortic tissue

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  Fig. 2. Step-by-step preparation of circular aortic tissue samples: A segment of the porcine descending thoracic aorta used for specimen harvesting; B, C extraction of four cylindrical specimens (10 mm diameter) from the highlighted region; D detailed view of the specimen bonded to the cylindrical metal platens; E final experimental setup with the sample mounted on the Bose Electroforce system and submerged in a saline bath at 37 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{\circ }$$\end{document}∘C

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  Fig. 3. Representative stages of the step-relaxation radial tensile test: A initial configuration after the first increment of 0.082 mm; B intermediate state (approx. step 25) showing substantial elongation; C pre-failure state characterized by maximum stretch, thinning, and onset of interlamellar delamination; D final mechanical rupture of the specimen

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  Fig. 4. Experimental engineering stress–time curves of the aortic specimens under multi-step radial tension. The plot is enhanced with strategic kinematic indicators, highlighted by vertical dashed lines at key deformation thresholds calculated from the 2.0 mm initial tissue thickness: \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda \approx 1.5$$\end{document}λ≈1.5 (representing the moderate out-of-plane strain threshold at the 12th step), \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda \approx 1.8$$\end{document}λ≈1.8 (capturing the microstructural damage acceleration regime at the 20th step), and λ> 2.0λ>2.0 (identifying the deep damage state at the 25th step preceding ultimate macroscopic failure)

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  Fig. 5. Microstructural reorganization of the aortic media. Merged SHG (collagen, green) and TPEF (elastin, red) image in the unstretched state (A) and fully stretched state (B); Gaussian distribution of fiber orientation from \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu \approx 31^\circ$$\end{document}μ≈31∘ in unstretched state to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu \approx 95^\circ$$\end{document}μ≈95∘ in stretched state (C)

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  Fig. 6. Comparison between experimental engineering stress–time curves (dashed colored lines) and the individual model predictions (thin solid black lines) for the analyzed specimens (n = 5n=5). The thick red dashed line represents the global ensemble average of the model predictions, demonstrating the capacity of the constitutive framework to capture the central trend of the mechanical envelope without non-linear parameter distortion

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  Fig. 7. Validation of the numerical framework (first relaxation step). Experimental engineering stress (colored markers) versus FEBio simulations (solid black lines) for the five aortic specimens. The overlap confirms the model’s accuracy in capturing dissipative kinetics and validates the numerical implementation

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  Fig. 8. Spatio-temporal evolution of fluid flux across the specimen cross-section. The contour plots illustrate the fluid velocity magnitude (mm/s), while white arrows represent the flux vectors. A At t = 0.1t=0.1 s, inward vectors show the initial suction effect (swelling) driven by the rapid radial expansion. B,C At t = 5t=5 s and t = 30t=30 s, the reversal of vector direction shows the outward fluid exudation (relaxation phase), characterized by a decay in flux magnitude from \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10^{-4}$$\end{document}10-4 to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$10^{-5}$$\end{document}10-5 mm/s. This transition highlights the role of fluid redistribution in the overall stress-relaxation process