Inverse parameter fitting of biological tissues: a response surface approach

Area of Science:

• Biomedical Engineering
• Materials Science
• Computational Mechanics

Background:

• Accurate characterization of biological tissue material properties is crucial for medical device design, surgical simulation, and diagnostic imaging.
• Existing methods for determining tissue constitutive parameters can be complex and time-consuming.
• Nonlinear anisotropic behavior is a common characteristic of soft biological tissues.

Purpose of the Study:

• To present and validate a semi-global inverse method for determining material parameters of biological tissues.
• To apply the method to nonlinear anisotropic constitutive models for aortic sinus, aortic wall, and aortic valve tissues.
• To demonstrate the method's efficacy using experimental data from uniaxial and inflation tests.

Main Methods:

• Employed a semi-global inverse method based on the successive response surface method.
• Developed numerical simulations of uniaxial and inflation tests for aortic tissues.
• Fitted constitutive parameters by comparing simulation predictions to experimental data (force-displacement for uniaxial, 3D coordinates for inflation).

Main Results:

• The inverse method successfully identified constitutive parameters for both aortic sinus/wall and aortic valve tissues.
• Predictions using the converged parameters showed excellent agreement with experimental data for both test types.
• The method demonstrated consistent and reliable identification of model parameters.

Conclusions:

• The presented semi-global inverse method is effective for characterizing the material properties of biological tissues.
• This approach offers a robust tool for biomedical material characterization.
• The method holds potential for applications in diagnostic imaging and the development of advanced medical technologies.