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Abstract Objective. Arterial viscosity is emerging as an important biomarker, in addition to the widely used arterial elasticity. This paper presents an approach to estimate arterial viscoelasticity using shear wave elastography (SWE).Approach. While dispersion characteristics are often used to estimate elasticity from SWE data, they are not sufficiently sensitive to viscosity. Driven by this, we develop a full waveform inversion (FWI) methodology, based on directly matching predicted and measured wall velocity in space and time, to simultaneously estimate both elasticity and viscosity. Specifically, we propose to minimize an objective function capturing the correlation between measured and predicted responses of the anterior wall of the artery.Results. The objective function is shown to be well-behaving (generally convex), leading us to effectively use gradient optimization to invert for both elasticity and viscosity. The resulting methodology is verified with synthetic data polluted with noise, leading to the conclusion that the proposed FWI is effective in estimating arterial viscoelasticity.Significance. Accurate estimation of arterial viscoelasticity, not just elasticity, provides a more precise characterization of arterial mechanical properties, potentially leading to a better indicator of arterial health.
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This content will become publicly available on August 1, 2026
Twin Peak Method for Estimating Tissue Viscoelasticity Using Shear Wave Elastography
Tissue viscoelasticity is becoming an increasingly useful biomarker beyond elasticity and can theoretically be estimated using shear wave elastography by inverting the propagation and attenuation characteristics of shear waves. Estimating viscosity is often more difficult than elasticity because attenuation, the main effect of viscosity, leads to poor signal-to-noise ratio of the shear wave motion. In the present work, we provide an alternative to existing methods of viscoelasticity estimation, based on peaks in the frequency–wavenumber (f–k) domain, which are considered more robust against noise compared with other features in the f–k domain. Specifically, the method minimizes the difference between simulated and measured versions of two sets of peaks (twin peaks) in the f–k domain, obtained first by traversing through each frequency and then by traversing through each wavenumber. The slopes and deviation of the twin peaks are sensitive to elasticity and viscosity, respectively, leading to the effectiveness of the proposed inversion algorithm for characterizing mechanical properties. This expected effectiveness is confirmed through in silico verification, followed by ex vivo validation and in vivo application, indicating that the proposed approach can be used effectively in accurately estimating viscoelasticity, thus potentially contributing to the development of enhanced biomarkers.
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- Award ID(s):
- 2111234
- PAR ID:
- 10659424
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Ultrasound in Medicine & Biology
- Volume:
- 51
- Issue:
- 8
- ISSN:
- 0301-5629
- Page Range / eLocation ID:
- 1160 to 1171
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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