Evidence map›Paper›PMID 37590110›Full record

ArticleIEEE transactions on bio-medical engineering2024

A Force-Matched Approach to Large-Strain Nonlinearity in Elasticity Imaging for Breast Lesion Characterization.

David P Rosen, Rohit Nayak, Yuqi Wang, Daniel Gendin, Nicholas B Larson, Robert T Fazzio, Assad A Oberai, Timothy J Hall, Paul E Barbone, Azra Alizad and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in IEEE transactions on bio-medical engineering, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 24% 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.

  1. Pooled it
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

11 authors at 5 institutions in 1 country.

David P Rosen
Rohit Nayak
Yuqi Wang
Daniel Gendin
Nicholas B Larson
Robert T Fazzio
Assad A Oberai
Timothy J Hall
Paul E Barbone
Azra Alizad
Mostafa Fatemi
Mayo Clinic · USUniversity of Wisconsin–Madison · USBoston University · USCalifornia Institute of Technology · USSouthwestern Medical Center · US

Funding

Multi-parameter Nonlinear Elasticity Mapping of Breast MassesR01CA195527 · NCI · MAYO CLINIC ROCHESTER · PI ALIZAD, AZRA, FATEMI, MOSTAFA · 2016 to 2020
$2.8M
NCI NIH HHS R01 CA195527
6 · The paper itself

Abstract

objectiveUltrasound elasticity imaging is a class of ultrasound techniques with applications that include the detection of malignancy in breast lesions. Although elasticity imaging traditionally assumes linear elasticity, the large strain elastic response of soft tissue is known to be nonlinear. This study evaluates the nonlinear response of breast lesions for the characterization of malignancy using force measurement and force-controlled compression during ultrasound imaging.

methods54 patients were recruited for this study. A custom force-instrumented compression device was used to apply a controlled force during ultrasound imaging. Motion tracking derived strain was averaged over lesion or background ROIs and matched with compression force. The resulting force-matched strain was used for subsequent analysis and curve fitting.

resultsGreater median differences between malignant and benign lesions were observed at higher compressional forces (p-value < 0.05 for compressional forces of 2-6N). Of three candidate functions, a power law function produced the best fit to the force-matched strain. A statistically significant difference in the scaling parameter of the power function between malignant and benign lesions was observed (p-value = 0.025).

conclusionsWe observed a greater separation in average lesion strain between malignant and benign lesions at large compression forces and demonstrated the characterization of this nonlinear effect using a power law model. Using this model, we were able to differentiate between malignant and benign breast lesions. SIGNIFICANCE: With further development, the proposed method to utilize the nonlinear elastic response of breast tissue has the potential for improving non-invasive lesion characterization for potential malignancy.

Indexed as

Breast NeoplasmsElasticity Imaging TechniquesBreastDiagnosis, DifferentialElasticityFemaleHumansSensitivity and SpecificityUltrasonography, Mammary

Identifiers

PMID37590110
PMCPMC10843664
OpenAlexW4385945554

What OpenQuestion holds

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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.