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Elastic Strain Energy for Shearing Stresses

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Related Experiment Video

Updated: Jun 6, 2025

Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography

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Twin Peak Method for Estimating Tissue Viscoelasticity using Shear Wave Elastography.

Shuvrodeb Adikary¹, Matthew W Urban², Murthy N Guddati¹

¹North Carolina State University, Raleigh, NC, US.

|November 28, 2024

Summary

This study introduces a novel method for estimating tissue viscoelasticity using shear wave elastography (SWE). The technique accurately measures both elasticity and viscosity, offering a robust alternative for developing new biomarkers.

Keywords:

Ultrasound elastography attenuation liver elastography point measurements viscosity

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Last Updated: Jun 6, 2025

Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography

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Published on: May 10, 2022

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Studying Large Amplitude Oscillatory Shear Response of Soft Materials

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Published on: April 25, 2019

Area of Science:

Biomedical Engineering
Medical Imaging
Rheology

Background:

Tissue viscoelasticity is a valuable biomarker, but its estimation via shear wave elastography (SWE) is challenging.
Viscosity estimation is particularly difficult due to signal attenuation affecting shear wave motion and reducing signal-to-noise ratio.

Purpose of the Study:

To develop a robust and noise-resistant method for viscoelasticity estimation using SWE.
To provide an alternative approach for characterizing the mechanical properties of tissues.

Main Methods:

A novel inversion algorithm was developed, minimizing differences between simulated and measured twin peaks in the frequency-wavenumber domain.
The method analyzes slopes and deviations of twin peaks, which are sensitive to elasticity and viscosity, respectively.

Main Results:

The proposed method demonstrated effectiveness in characterizing mechanical properties.
In silico, ex vivo, and in vivo studies confirmed the algorithm's accuracy in estimating viscoelasticity.

Conclusions:

The developed approach accurately estimates tissue viscoelasticity, offering a robust alternative to existing methods.
This technique has the potential to contribute to the development of enhanced diagnostic biomarkers.