Extension of the Optimized Virtual Fields Method to estimate viscoelastic material parameters from 3D dynamic...

Area of Science:

• Biomechanics and medical imaging
• Soft tissue mechanics
• Computational mechanics

Background:

• In-vivo mechanical property measurement is crucial for biomechanics and medicine, aiding in early cancer diagnosis and traumatic brain injury studies.
• Magnetic Resonance Elastography (MRE) provides 3D displacement data, but inverse methods for parameter identification face challenges with pressure waves and experimental noise.
• Existing inverse methods struggle with noise-corrupted spatial derivatives and pressure wave artifacts in MRE data.

Purpose of the Study:

• To adapt and evaluate the Optimized Virtual Fields Method (OVFM) for identifying elastic and viscoelastic material parameters from MRE data.
• To assess the OVFM's robustness to spatial resolution and experimental noise using simulated MRE data.
• To address challenges in identifying parameters for quasi-incompressible materials and propose a criterion for local identification quality assessment.

Main Methods:

• The Optimized Virtual Fields Method (OVFM) was adapted for identifying material parameter maps from 3D displacement fields obtained via MRE.
• The study analyzed the sensitivity of OVFM to spatial resolution and noise using 3D analytically simulated displacement data.
• An a posteriori criterion was developed to estimate the local quality of parameter identification.

Main Results:

• The OVFM demonstrated robustness to noise and effectively handled pressure waves in MRE data.
• The study quantified the impact of spatial resolution and noise on the accuracy of identified material parameters.
• OVFM provided a natural solution for identifying parameters in quasi-incompressible materials.
• An a posteriori criterion for assessing local identification quality was successfully proposed.

Conclusions:

• The Optimized Virtual Fields Method (OVFM) is a robust and effective tool for identifying soft tissue mechanical properties from MRE data, even with noise and limited spatial resolution.
• OVFM offers solutions to long-standing challenges in inverse problems, including those related to quasi-incompressible materials.
• The proposed a posteriori criterion enhances the reliability of MRE-based material property identification.