Finite Element Simulation of the Three-Dimensional Residual Stress Field Using a Patient-Specific Aortic Model

Area of Science:

• Biomedical Engineering
• Computational Mechanics
• Cardiovascular Research

Background:

• Residual stress (RS) in the aorta is crucial for in vivo stress distribution, impacting aortic physiology and pathology.
• Quantifying the 3D residual stress field is complex due to patient-specific and heterogeneous distributions.
• Understanding aortic residual stress is vital for diagnosing and treating aortic diseases.

Purpose of the Study:

• To propose a stress-driven anisotropic growth model for qualitatively predicting the 3D residual stress field in patient-specific human aortic wall models.
• To predict the 3D residual stress field under in vivo stress conditions, adjusting for transmural stress heterogeneity.
• To validate the model's predictions against experimental data and explore the influence of transmural stress heterogeneity.

Main Methods:

• Development of a stress-driven anisotropic growth model.
• Patient-specific human aortic wall modeling.
• Virtual opening angle and lateral bending tests.
• Parametric study on transmural stress heterogeneity.

Main Results:

• The model successfully predicted patient-specific 3D residual stress fields achieving in vivo stress states.
• Simulated opening angles varied axially, peaking at the aortic arch, consistent with experimental data.
• Lateral bending simulations also showed good agreement with literature findings.
• Parametric analysis indicated that opening and bending angles are sensitive to in vivo transmural stress heterogeneity.

Conclusions:

• The proposed model offers a method for predicting patient-specific 3D heterogeneous residual and in vivo stress fields.
• This approach can advance the exploration of aortic disease pathogenesis and treatment strategies.
• Accurate residual stress prediction is key to understanding aortic biomechanics and disease progression.