Evidence map›Paper›PMID 30296217›Full record

ArticleIEEE transactions on medical imaging2019

Local Phase Velocity Based Imaging: A New Technique Used for Ultrasound Shear Wave Elastography.

Piotr Kijanka, Matthew W Urban

Abstract read
In one paragraph

Article in IEEE transactions on medical imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

28 citing papers in PubMed.

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  14. Correlation-based full-waveform shear wave elastography.Physics in medicine and biology · 2023
    Article
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  18. Imaging the Local Nonlinear Viscoelastic Properties of Soft Tissues: Initial Validation and Expected Benefits.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2022
    Article
  19. Article
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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 Kijanka
Matthew W Urban

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 an imaging modality for noninvasive evaluation of tissue mechanical properties. However, many current techniques overestimate lesions dimension or shape especially when small inclusions are taken into account. In this paper, we propose a new method called local phase velocity-based imaging (LPVI) as an alternative technique to measure tissue elasticity. Two separate acquisitions with ultrasound push beams focused once on the left side and once on the right side of the inclusion were generated. A local shear wave velocity is then recovered in the frequency domain (for a single frequency or frequency band) for both acquired data sets. Finally, a two-dimensional shear wave velocity map is reconstructed by combining maps from two separate acquisitions. Robust and accurate shear wave velocity maps are reconstructed using the proposed LPVI method in calibrated liver fibrosis tissue mimicking homogeneous phantoms, a calibrated elastography phantom with stepped cylinder inclusions and a homemade gelatin phantom with ex vivo porcine liver inclusion. Results are compared with an existing phase velocity-based imaging approach and a group velocity-based method considered as the state of the art. Results from the phantom study showed that increased frequency improved the shape of the reconstructed inclusions and contrast-to-noise ratio between the target and background.

Indexed as

AlgorithmsAnimalsElasticity Imaging TechniquesHumansImage Interpretation, Computer-AssistedLiverLiver CirrhosisPhantoms, ImagingSwine

Identifiers

PMID30296217
PMCPMC6467061

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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.