Evidence map›Paper›PMID 30312358›Full record

ArticlePloS one2018

Viscoelastic parameters as discriminators of breast masses: Initial human study results.

Viksit Kumar, Max Denis, Adriana Gregory, Mahdi Bayat, Mohammad Mehrmohammadi, Robert Fazzio, Mostafa Fatemi, Azra Alizad

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
–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

35 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  12. Surface Compression Alters in Vivo VisR Stiffness, Viscosity, and Anisotropy Measurements in Human Breast.IEEE open journal of ultrasonics, ferroelectrics, and frequency control · 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

8 authors.

Viksit KumarDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, United States of America.ORCID 0000-0003-0056-5223
Max DenisDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, United States of America.
Adriana GregoryDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, United States of America.
Mahdi BayatDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, United States of America.
Mohammad MehrmohammadiDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, United States of America.
Robert FazzioDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, United States of America.
Mostafa FatemiDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, United States of America.
Azra AlizadDepartment of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, United States of America.ORCID 0000-0002-7658-1572

Funding

Multi-parameter Nonlinear Elasticity Mapping of Breast MassesR01CA195527 · NCI · MAYO CLINIC ROCHESTER · PI ALIZAD, AZRA, FATEMI, MOSTAFA · 2016 to 2020
$2.8M
Classification of breast masses based on visco-elastic propertiesR01CA168575 · NCI · MAYO CLINIC ROCHESTER · PI FATEMI, MOSTAFA, INSANA, MICHAEL F · 2013 to 2018
$2.5M
Combined Acoustic Imaging and Viscoelastic Parameters Estimation in Breast CancerR01CA148994 · NCI · MAYO CLINIC ROCHESTER · PI ALIZAD, AZRA · 2011 to 2015
$2.4M
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 CA148994NCI NIH HHS R01 CA168575NCI NIH HHS R01 CA174723NCI NIH HHS R01 CA195527NIBIB NIH HHS R01 EB017213
6 · The paper itself

Abstract

Shear wave elastography is emerging as a clinically valuable diagnostic tool to differentiate between benign and malignant breast masses. Elastography techniques assume that soft tissue can be modelled as a purely elastic medium. However, this assumption is often violated as soft tissue exhibits viscoelastic properties. In order to explore the role of viscoelastic parameters in suspicious breast masses, a study was conducted on a group of patients using shear wave dispersion ultrasound vibrometry in the frequency range of 50-400 Hz. A total of 43 female patients with suspicious breast masses were recruited before their scheduled biopsy. Of those, 15 patients did not meet the data selection criteria. Voigt model based shear elasticity showed a significantly (p = 7.88x10(-6)) higher median value for the 13 malignant masses (16.76±13.10 kPa) compared to 15 benign masses (1.40±1.12 kPa). Voigt model based shear viscosity was significantly different (p = 4.13x10(-5)) between malignant (8.22±3.36 Pa-s) and benign masses (2.83±1.47 Pa-s). Moreover, the estimated time constant from the Voigt model, which is dependent on both shear elasticity and viscosity, differed significantly (p = 6.13x10(-5)) between malignant (0.68±0.33 ms) and benign masses (3.05±1.95 ms). Results suggest that besides elasticity, viscosity based parameters like shear viscosity and time constant can also be used to differentiate between malignant and benign breast masses.

Indexed as

BreastBreast DiseasesBreast NeoplasmsDiagnosis, DifferentialElasticityElasticity Imaging TechniquesFemaleHumansMiddle AgedUltrasonographyViscosity

Identifiers

PMID30312358
PMCPMC6185851

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.