Recent Advances in the Virtual Fields Method for Evaluating and Identifying Tissue Biomechanical Properties and...

Area of Science:

• Biomechanics
• Soft Tissue Mechanics
• Computational Mechanics

Background:

• Full-field measurement techniques provide high-resolution, volume-wide displacement data for soft tissues.
• The virtual fields method (VFM) is an inverse mechanics technique that leverages this data and equilibrium principles.
• VFM is crucial for identifying constitutive parameters in soft tissue mechanics, particularly hyperelastic models.

Purpose of the Study:

• To review the foundations of the VFM for soft tissue parameter identification.
• To highlight recent advances in VFM formulations and applications.
• To discuss the potential of VFM for real-time clinical applications in soft tissue modeling.

Main Methods:

• Review of VFM principles applied to soft tissue mechanics.
• Analysis of recent VFM advancements including automated virtual field generation.
• Exploration of VFM extensions to inelastic behavior and machine learning integration.

Main Results:

• Modern VFM formulations offer increased accessibility and automated virtual field generation.
• Enhanced VFM robustness allows for identification of regionally variable constitutive parameters.
• VFM has been extended to inelastic behaviors, in vivo applications, and machine learning integration.

Conclusions:

• Recent VFM advances significantly improve soft tissue characterization.
• The method shows great promise for real-time clinical applications in complex soft tissue modeling.
• VFM integration with machine learning opens new avenues for biomechanical analysis.