Evidence map›Paper›PMID 32691540›Full record

ArticleKorean journal of radiology2020

Combination of Quantitative Parameters of Shear Wave Elastography and Superb Microvascular Imaging to Evaluate Breast Masses.

Eun Ji Lee, Yun Woo Chang

Open access · hybridAbstract read
In one paragraph

Article in Korean journal of radiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.3field-weighted citation impact, top 6% 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

19 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Comparative Evaluation of Superb Microvascular Imaging and Dynamic Contrast-Enhanced Magnetic Resonance Imaging in Differentiating Benign and Malignant Breast Masses.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2025
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  16. Association Between Vascular Index MeasuredFrontiers in oncology · 2022
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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

2 authors at 1 institution in 1 country.

Eun Ji LeeDepartment of Radiology, Soonchunhyang University Hospital Seoul, Seoul, Korea.ORCID 0000-0002-4860-2495
Yun Woo ChangDepartment of Radiology, Soonchunhyang University Hospital Seoul, Seoul, Korea. ywchang@schmc.ac.kr.ORCID 0000-0001-9704-8112
Soonchunhyang University Hospital Seoul · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to evaluate the diagnostic value of combining the quantitative parameters of shear wave elastography (SWE) and superb microvascular imaging (SMI) to breast ultrasound (US) to differentiate between benign and malignant breast masses. MATERIALS AND

methodsA total of 200 pathologically confirmed breast lesions in 192 patients were retrospectively reviewed using breast US with B-mode imaging, SWE, and SMI. Breast masses were assessed based on the breast imaging reporting and data system (BI-RADS) and quantitative parameters using the maximum elasticity (Emax) and ratio (Eratio) in SWE and the vascular index in SMI (SMI

resultsEmax with a cutoff value of 86.45 kPa had the highest AUC value compared to Eratio of 3.57 or SMI

conclusionCombining all quantitative values of SWE and SMI with B-mode US improved the diagnostic performance in differentiating between benign and malignant breast lesions.

Indexed as

AdultAgedAlgorithmsBreastBreast NeoplasmsDiagnostic Tests, RoutineElasticity Imaging TechniquesFemaleHumansMiddle AgedReproducibility of ResultsRetrospective StudiesSensitivity and SpecificityUltrasonography, MammaryBreastNeoplasmShear wave elastographySuperb microvascular imagingUltrasound

Identifiers

PMID32691540
PMCPMC7371619
OpenAlexW3041730720

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.