Evidence map›Paper›PMID 32980784›Full record

ArticleUltrasonics2021

Dispersion curve calculation in viscoelastic tissue-mimicking materials using non-parametric, parametric, and high-resolution methods.

Piotr Kijanka, Matthew W Urban

Abstract read
In one paragraph

Article in Ultrasonics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Piotr KijankaDepartment of Robotics and Mechatronics, AGH University of Science and Technology, 30-059 Krakow, Poland. Electronic address: piotr.kijanka@agh.edu.pl.
Matthew W UrbanDepartment of Radiology, Mayo Clinic, Rochester, MN 55905, USA; Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, USA.

Funding

Measurement of Renal Viscoelastic Properties with UltrasoundR01DK092255 · NIDDK · MAYO CLINIC ROCHESTER · PI URBAN, MATTHEW WILLIAM · 2012 to 2022
$5.2M
NIDDK NIH HHS R01 DK092255
6 · The paper itself

Abstract

Ultrasound shear wave elastography is a modality used for noninvasive, quantitative evaluation of soft tissue mechanical properties. A common way of exploring the tissue viscoelasticity is through analyzing the shear wave velocity dispersion curves. The variation of phase velocity with frequency or wavelength is called the dispersion curve. An increase of the available spectrum to be used for phase velocity estimation is meaningful for a tissue dispersion analysis in vivo. A number of available methods for dispersion relation estimation exist which can give diffuse results due the presence of noise in the measured data. In this work we compare six selected methods used for dispersion curve calculation in viscoelastic materials. Non-parametric, parametric and high-resolution methods were examined and compared. We tested selected methods on digital phantom data created using finite-difference-based method in tissue-mimicking viscoelastic media as well as on the experimental custom tissue-mimicking phantoms. In addition, we evaluated the algorithms with different levels of added white Gaussian noise to the shear wave particle velocity from numerical phantoms. Tests conducted showed that more advanced methods can offer better frequency resolution, and less variance than the fast Fourier transform. In addition, the non-parametric Blackman-Tukey approach exhibits similar performance and can be interchangeably used for shear wave phase velocity dispersion curves calculation.

Indexed as

AcousticBlackman-TukeyEigenvectorElasticElastodynamicFinite differenceFourier transformMinimum Variance Distortionless Response (MVDR)Modified covarianceMultiple Signal Classification (MUSIC)PhantomSoft materialViscoelastic

Identifiers

PMID32980784
PMCPMC7850297

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.