Evidence map›Paper›PMID 29373598›Full record

ArticlePloS one2018

Quantitative characterization of viscoelastic behavior in tissue-mimicking phantoms and ex vivo animal tissues.

Ashkan Maccabi, Andrew Shin, Nikan K Namiri, Neha Bajwa, Maie St John, Zachary D Taylor, Warren Grundfest, George N Saddik

Open access · goldAbstract 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 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
3.6field-weighted citation impact, top 7% of its field
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

26 citing papers in PubMed, 58 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Review
  9. Article
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Integrating mechanical sensor readouts into organ-on-a-chip platforms.Frontiers in bioengineering and biotechnology · 2022
    Review
  19. Review
  20. 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

8 authors at 1 institution in 1 country.

Ashkan MaccabiDepartment of Electrical Engineering, University of California, Los Angeles, Los Angeles, CA, United States of America.ORCID 0000-0002-6048-6669
Andrew ShinWellman Center for Photomedicine, Massachusetts General Hospital, Boston, MA, United States of America.
Nikan K NamiriDepartment of Bioengineering, University of California, Los Angeles, Los Angeles, CA, United States of America.
Neha BajwaCenter for Advanced Surgical and Interventional Technology, CASIT, Los Angeles, CA, United States of America.
Maie St JohnDepartment of Head and Neck Surgery, David Geffen School of Medicine, Los Angeles, CA, United States of America.
Zachary D TaylorCenter for Advanced Surgical and Interventional Technology, CASIT, Los Angeles, CA, United States of America.
Warren GrundfestDepartment of Electrical Engineering, University of California, Los Angeles, Los Angeles, CA, United States of America.
George N SaddikCenter for Advanced Surgical and Interventional Technology, CASIT, Los Angeles, CA, United States of America.
University of California, Los Angeles · US

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Samuel Wheeler French · 1985 to 2026
$134.5M
Vision Research Core at UCLAP30EY000331 · NEI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Gregory Darin Field, DAVID S WILLIAMS · 1985 to 2026
$16.8M
BIOMECHANICAL ANALYSIS IN STRABISMUS SURGERYR01EY008313 · NEI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI JOSEPH Louis DEMER · 1991 to 2026
$15.0M
NCI NIH HHS P30 CA016042NEI NIH HHS P30 EY000331NEI NIH HHS R01 EY008313NIH HHS EY000331NIH HHS EY008313
6 · The paper itself

Abstract

Viscoelasticity of soft tissue is often related to pathology, and therefore, has become an important diagnostic indicator in the clinical assessment of suspect tissue. Surgeons, particularly within head and neck subsites, typically use palpation techniques for intra-operative tumor detection. This detection method, however, is highly subjective and often fails to detect small or deep abnormalities. Vibroacoustography (VA) and similar methods have previously been used to distinguish tissue with high-contrast, but a firm understanding of the main contrast mechanism has yet to be verified. The contributions of tissue mechanical properties in VA images have been difficult to verify given the limited literature on viscoelastic properties of various normal and diseased tissue. This paper aims to investigate viscoelasticity theory and present a detailed description of viscoelastic experimental results obtained in tissue-mimicking phantoms (TMPs) and ex vivo tissues to verify the main contrast mechanism in VA and similar imaging modalities. A spherical-tip micro-indentation technique was employed with the Hertzian model to acquire absolute, quantitative, point measurements of the elastic modulus (E), long term shear modulus (η), and time constant (τ) in homogeneous TMPs and ex vivo tissue in rat liver and porcine liver and gallbladder. Viscoelastic differences observed between porcine liver and gallbladder tissue suggest that imaging modalities which utilize the mechanical properties of tissue as a primary contrast mechanism can potentially be used to quantitatively differentiate between proximate organs in a clinical setting. These results may facilitate more accurate tissue modeling and add information not currently available to the field of systems characterization and biomedical research.

Indexed as

ElasticityModels, AnimalPhantoms, ImagingViscosityAnimalsMaleRats, Sprague-DawleySwine

Identifiers

PMID29373598
PMCPMC5786325
OpenAlexW2784632870

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.