Evidence map›Paper›PMID 27488348›Full record

ArticleUltrasonic imaging2017

Virtual Breast Quasi-static Elastography (VBQE).

David Rosen, Yu Wang, Jingfeng Jiang

Abstract read
In one paragraph

Article in Ultrasonic imaging, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Modeling Uncertainty of Strain Ratio Measurements in Ultrasound Breast Strain Elastography: A Factorial Experiment.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2020
    Article
  3. Article
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

3 authors.

David Rosen1 Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, USA.
Yu Wang1 Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, USA.
Jingfeng Jiang1 Department of Biomedical Engineering, Michigan Technological University, Houghton, MI, USA.

Funding

Virtual Breast Project: Improving Noninvasive Characterization of TumorsR15CA179409 · NCI · MICHIGAN TECHNOLOGICAL UNIVERSITY · PI JIANG, JINGFENG · 2014 to 2014
$453k
NCI NIH HHS R15 CA179409
6 · The paper itself

Abstract

Viscoelasticity Imaging (VEI) has been proposed to measure relaxation time constants for characterization of in vivo breast lesions. In this technique, an external compression force on the tissue being imaged is maintained for a fixed period of time to induce strain creep. A sequence of ultrasound echo signals is then utilized to generate time-resolved strain measurements. Relaxation time constants can be obtained by fitting local time-resolved strain measurements to a viscoelastic tissue model (e.g., a modified Kevin-Voigt model). In this study, our primary objective is to quantitatively evaluate the contrast transfer efficiency (CTE) of VEI, which contains useful information regarding image interpretations. Using an open-source simulator for virtual breast quasi-static elastography (VBQE), we conducted a case study of contrast transfer efficiency of VEI. In multiple three-dimensional (3D) numerical breast phantoms containing various degrees of heterogeneity, finite element (FE) simulations in conjunction with quasi-linear viscoelastic constitutive tissue models were performed to mimic data acquisition of VEI under freehand scanning. Our results suggested that there were losses in CTE, and the losses could be as high as -18 dB. FE results also qualitatively corroborated clinical observations, for example, artifacts around tissue interfaces.

Indexed as

Elasticity Imaging TechniquesFinite Element AnalysisHumansPhantoms, ImagingSoftwareStress, MechanicalUltrasonography, MammaryViscositybreast cancerelastographyfinite element modelingviscoelastic imaging

Identifiers

PMID27488348
PMCPMC5290217

What OpenQuestion holds

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Registered trials

None linked

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.