Evidence map›Paper›PMID 36333449›Full record

ArticleScientific reports2022

Viscoelasticity assessment of tumoral skin with the use of a novel contact-free palpation methodology based upon surface waves.

A Bergheau, J-L Perrot, R Vargiolu, H Zahouani

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. 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
1.6field-weighted citation impact, top 19% 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

3 citing papers in PubMed, 10 citations in OpenAlex.

  1. TowardFrontiers in bioengineering and biotechnology · 2026
    Review
  2. 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

4 authors at 4 institutions in 1 country.

A BergheauLaboratory of Tribology and System Dynamics (LTDS), UMR 5513 CNRS, ECL-ENISE, Ecole Centrale de Lyon, University of Lyon, 36 Avenue Guy de Collongue, 69134, Ecully, France. alexandre.bergheau@ec-lyon.fr.
J-L PerrotCentre Hospitalier Universitaire de Saint-Etienne, Saint-Priest-en-Jarez, France.
R VargioluLaboratory of Tribology and System Dynamics (LTDS), UMR 5513 CNRS, ECL-ENISE, Ecole Centrale de Lyon, University of Lyon, 36 Avenue Guy de Collongue, 69134, Ecully, France.
H ZahouaniLaboratory of Tribology and System Dynamics (LTDS), UMR 5513 CNRS, ECL-ENISE, Ecole Centrale de Lyon, University of Lyon, 36 Avenue Guy de Collongue, 69134, Ecully, France.
Centre Hospitalier Universitaire de Saint-Étienne · FRCentre National de la Recherche Scientifique · FRLaboratoire de Tribologie et Dynamique des Systèmes · FRUniversité Claude Bernard Lyon 1 · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ensuing pilot investigation sheds new light on characterizing tumoral and non-tumoral human skin mechanical properties that will not only assist the dermatologist's diagnosis but also could constitute the creation of an Artificial Intelligence database for upcoming research. A modern, non-invasive, and contact-free methodology-UNDERSKIN-was developed, and hinges upon Fourier transform computations that permit the analysis of surface wave dispersion with a specific skin inversion model and viscoelastic model. It yields a detailed look at how particle movements of the medium propagate throughout its near sub-surface, hence a novel knowledge of the mechanical responses of skin tumors. The research results display the tumors' viscoelastic responses alongside their respective healthy skin outcomes for each skin layer as well as the dermatologist's touch analysis. Although dermatologists are capable of sensing and having a fair overall assessment of what they are palpating, they are unable heretofore to quantify it and inform where the firmness or softness derives from, which it is necessary to be acquainted with so as to perform an accurate diagnosis, prognosis, treatment, future surgery, and teledermatology.

Indexed as

Artificial IntelligenceSkin NeoplasmsHumansPalpationSkinViscosity

Identifiers

PMID36333449
PMCPMC9636432
OpenAlexW4308169946

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.