In vivo parameter identification in arteries considering multiple levels of smooth muscle activity

Area of Science:

• Biomechanics
• Medical Engineering
• Physiology

Background:

• Existing in vivo methods for artery parameter identification use continuum-mechanical models.
• These models are fit to clinical data via minimization problems to determine mechanical properties.
• Incorporating smooth muscle activity increases model parameters, risking overparameterization.

Purpose of the Study:

• To extend an existing in vivo parameter identification method for arteries to include smooth muscle activity.
• To prevent overparameterization by fitting the model to clinical data from multiple arterial states.
• To uniquely identify model parameters representing arterial mechanical properties.

Main Methods:

• A continuum-mechanical model was extended to account for smooth muscle activity.
• The model was fit to clinical data from the human abdominal aorta under three conditions: basal, constricted, and dilated.
• Simultaneous fitting to these three conditions was used to prevent overparameterization and ensure unique parameter identification.

Main Results:

• A unique set of model parameters was identified by fitting to clinical data from varied smooth muscle activity levels.
• The enhanced model demonstrated good agreement with the clinical data.
• The method successfully prevented overparameterization despite the increased model complexity.

Conclusions:

• The extended in vivo parameter identification method accurately characterizes arterial mechanical properties, including smooth muscle activity.
• Simultaneously analyzing data from different physiological states is effective in preventing overparameterization in complex biomechanical models.
• This approach provides a more robust and accurate understanding of arterial mechanics in vivo.