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Elastic Strain Energy for Shearing Stresses

Elastic Strain Energy for Shearing Stresses

As discussed in previous lessons, strain energy in a material is the energy stored when it is elastically deformed, a concept crucial in materials science and mechanical engineering. This energy results from the internal work done against the cohesive forces within the material. When a material undergoes shearing stress and corresponding shearing strain, the strain energy density, which is the energy stored per unit volume, is calculated. Within the elastic limit, where the stress is...

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Related Experiment Video

Updated: May 14, 2025

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

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Published on: May 10, 2022

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

Shuvrodeb Adhikary¹, Matthew W Urban², Murthy N Guddati¹

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

Ultrasound in Medicine & Biology

|May 7, 2025

Summary

This summary is machine-generated.

This study introduces a novel method for measuring tissue viscoelasticity using shear wave elastography. The technique enhances accuracy by analyzing frequency-wavenumber domain peaks, improving biomarker development.

Keywords:

Attenuation Liver elastography Point measurements Ultrasound elastography Viscosity

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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 is challenging due to noise sensitivity.
Viscosity estimation is particularly difficult because attenuation degrades shear wave signal quality.

Purpose of the Study:

To develop a robust method for estimating tissue viscoelasticity using shear wave elastography.
To overcome the limitations of existing methods in handling noise and accurately characterizing mechanical properties.

Main Methods:

Proposed a novel viscoelasticity estimation technique based on analyzing twin peaks in the frequency-wavenumber (f-k) domain.
The method minimizes the difference between simulated and measured f-k domain twin peaks.
Utilized the sensitivity of twin peak slopes and deviations to elasticity and viscosity, respectively.

Main Results:

The proposed method demonstrates robustness against noise compared to other f-k domain features.
In silico, ex vivo, and in vivo validations confirmed the effectiveness of the inversion algorithm.
Accurate estimation of viscoelastic properties was achieved.

Conclusions:

The developed f-k domain twin peak analysis offers an effective approach for accurate viscoelasticity estimation.
This method has the potential to contribute to the development of enhanced diagnostic biomarkers.
The technique shows promise for clinical applications in characterizing tissue mechanical properties.