Evidence map›Paper›PMID 29989938›Full record

ArticleIEEE transactions on bio-medical engineering2018

Automated In Vivo Sub-Hertz Analysis of Viscoelasticity (SAVE) for Evaluation of Breast Lesions.

Mahdi Bayat, Alireza Nabavizadeh, Viksit Kumar, Adriana Gregory, Michael Insana, Azra Alizad, Mostafa Fatemi

Abstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Ultrasound Based Viscoelasticity Imaging Tool for Differentiation of Breast Lesions.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025
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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

7 authors.

Mahdi Bayat
Alireza Nabavizadeh
Viksit Kumar
Adriana Gregory
Michael Insana
Azra Alizad
Mostafa Fatemi

Funding

Classification of breast masses based on visco-elastic propertiesR01CA168575 · NCI · MAYO CLINIC ROCHESTER · PI FATEMI, MOSTAFA, INSANA, MICHAEL F · 2013 to 2018
$2.5M
Viscoelastic Parameters estimation and imaging for Thyroid Nodule differentiationR01EB017213 · NIBIB · MAYO CLINIC ROCHESTER · PI ALIZAD, AZRA, CHEN, SHIGAO · 2014 to 2017
$2.2M
Generalized waveform methods for breast viscoelasticity mappingR01CA174723 · NCI · MAYO CLINIC ROCHESTER · PI FATEMI, MOSTAFA · 2014 to 2018
$1.8M
NCI NIH HHS R01 CA168575NCI NIH HHS R01 CA174723NIBIB NIH HHS R01 EB017213
6 · The paper itself

Abstract

We present an automated method for acquiring images and contrast parameters based on mechanical properties of breast lesions and surrounding tissue at load frequencies less than 1 Hz. The method called sub-Hertz analysis of viscoelasticity (SAVE) uses a compression device integrated with ultrasound imaging to perform in vivo ramp-and-hold uniaxial creep-like test on human breast in vivo. It models the internal deformations of tissues under constant surface stress as a linear viscoelastic response. We first discuss different aspects of our unique measurement approach and the expected variability of the viscoelastic parameters estimated based on a simplified one-dimensional reconstruction model. Finite-element numerical analysis is used to justify the advantages of using imaging contrast over viscoelasticity values. We then present the results of SAVE applied to a group of patients with breast masses undergoing biopsy.

Indexed as

BreastBreast NeoplasmsElasticityElasticity Imaging TechniquesFemaleHumansImage Interpretation, Computer-AssistedUltrasonography, MammaryViscosity

Identifiers

PMID29989938
PMCPMC6043422

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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.