Evidence map›Paper›PMID 28257467›Full record

ArticlePloS one2017

Diagnostic features of quantitative comb-push shear elastography for breast lesion differentiation.

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

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Trial
  2. Article
  3. Ultrasound elastography evaluation of age-related muscle atrophy: AnProceedings of meetings on acoustics. Acoustical Society of America · 2023
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Evaluation of Reconstruction Parameters for 2-D Comb-Push Ultrasound Shear Wave Elastography.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2019
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. 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

9 authors.

Mahdi BayatDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, MN, United States of America.ORCID http://orcid.org/0000-0001-9069-0823
Max DenisDepartment of Radiology, Mayo Clinic College of Medicine, SW, Rochester, MN, United States of America.
Adriana GregoryDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, MN, United States of America.
Mohammad MehrmohammadiDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, MN, United States of America.
Viksit KumarDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, MN, United States of America.
Duane MeixnerDepartment of Radiology, Mayo Clinic College of Medicine, SW, Rochester, MN, United States of America.
Robert T FazzioDepartment of Radiology, Mayo Clinic College of Medicine, SW, Rochester, MN, United States of America.
Mostafa FatemiDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, MN, United States of America.
Azra AlizadDepartment of Physiology and Biomedical Engineering, Mayo Clinic College of Medicine, Rochester, MN, United States of America.ORCID http://orcid.org/0000-0002-7658-1572

Funding

Combined Acoustic Imaging and Viscoelastic Parameters Estimation in Breast CancerR01CA148994 · NCI · MAYO CLINIC ROCHESTER · PI ALIZAD, AZRA · 2011 to 2015
$2.4M
NCI NIH HHS R01 CA148994
6 · The paper itself

Abstract

backgroundLesion stiffness measured by shear wave elastography has shown to effectively separate benign from malignant breast masses. The aim of this study was to evaluate different aspects of Comb-push Ultrasound Shear Elastography (CUSE) performance in differentiating breast masses.

methodsWith written signed informed consent, this HIPAA- compliant, IRB approved prospective study included patients from April 2014 through August 2016 with breast masses identified on conventional imaging. Data from 223 patients (19-85 years, mean 59.93±14.96 years) with 227 suspicious breast masses identifiable by ultrasound (mean size 1.83±2.45cm) were analyzed. CUSE was performed on all patients. Three regions of interest (ROI), 3 mm in diameter each, were selected inside the lesion on the B-mode ultrasound which also appeared in the corresponding shear wave map. Lesion elasticity values were measured in terms of the Young's modulus. In correlation to pathology results, statistical analyses were performed.

resultsPathology revealed 108 lesions as malignant and 115 lesions as benign. Additionally, 4 lesions (BI-RADS 2 and 3) were considered benign and were not biopsied. Average lesion stiffness measured by CUSE resulted in 84.26% sensitivity (91 of 108), 89.92% specificity (107 of 119), 85.6% positive predictive value, 89% negative predictive value and 0.91 area under the curve (P<0.0001). Stiffness maps showed spatial continuity such that maximum and average elasticity did not have significantly different results (P > 0.21).

conclusionCUSE was able to distinguish between benign and malignant breast masses with high sensitivity and specificity. Continuity of stiffness maps allowed for choosing multiple quantification ROIs which covered large areas of lesions and resulted in similar diagnostic performance based on average and maximum elasticity. The overall results of this study, highlights the clinical value of CUSE in differentiation of breast masses based on their stiffness.

Indexed as

AgedAged, 80 and overBiopsyBreastBreast NeoplasmsDiagnosis, DifferentialElasticity Imaging TechniquesFemaleHumansMiddle AgedNeoplasmsUltrasonography, Mammary

Identifiers

PMID28257467
PMCPMC5336209

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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.