Computational modeling of the arterial wall based on layer-specific histological data

Area of Science:

• Biomechanics
• Materials Science
• Computational Modeling

Background:

• Arterial walls possess a complex, layered structure (intima, media, adventitia).
• Each layer functions as a fiber-reinforced composite material, crucial for vascular mechanics.

Purpose of the Study:

• To develop and compare two distinct modeling approaches for simulating arterial wall layer anisotropy.
• To investigate the influence of fiber dispersion, including waviness, on material behavior.
• To validate computational models against experimental data from human aorta layers.

Main Methods:

• Embedded Fiber (EF) approach: Directly models fiber microstructure and anisotropy at the element level.
• Angular Integration (AI) approach: Homogenizes fiber effects into constitutive equations using anisotropic terms.
• Incorporation of fiber dispersion (angular distribution and waviness) in both models.
• Validation using published experimental data for human aorta layers.

Main Results:

• Both EF and AI approaches successfully capture the anisotropic behavior of individual arterial wall layers.
• The study establishes correlations between phenomenological AI parameters and physically interpretable EF parameters.
• Fiber waviness was identified as a significant factor influencing material anisotropy, previously unconsidered.

Conclusions:

• The developed models provide accurate simulations of arterial wall layer mechanics using histological data.
• This research facilitates the calibration of homogenized models based on microstructural details.
• Enhanced understanding of arterial wall structure-function relationships is achieved, aiding future cardiovascular research.