Evidence map›Paper›PMID 32607328›Full record

ArticleWorld journal of clinical cases2020

Evaluation of internal and shell stiffness in the differential diagnosis of breast non-mass lesions by shear wave elastography.

Ping Xu, Mei Wu, Min Yang, Juan Xiao, Zheng-Min Ruan, Lan-Ying Wu

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Article in World journal of clinical cases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 16% 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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 15 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Ping XuDepartment of Ultrasound, Beijing Shijitan Hospital Affiliated to Capital Medical University, Beijing 100038, China.
Mei WuDepartment of Ultrasound, The Second Hospital of Shandong University, Jinan 250033, Shandong Province, China. a_may0212@163.com.
Min YangDepartment of Ultrasound, Beijing Shijitan Hospital Affiliated to Capital Medical University, Beijing 100038, China.
Juan XiaoEvidence-based Medicine Center, The Second Hospital of Shandong University, Jinan 250033, Shandong Province, China.
Zheng-Min RuanDepartment of Ultrasound, The Second Hospital of Shandong University, Jinan 250033, Shandong Province, China.
Lan-Ying WuDepartment of Ultrasound, Beijing Shijitan Hospital Affiliated to Capital Medical University, Beijing 100038, China.
Capital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe diagnostic specificity of conventional ultrasound for breast non-mass lesions (NMLs) is low at approximately 21%-43%. Shear wave elastography (SWE) can distinguish benign from malignant lesions by evaluating the internal and peripheral stiffness. SWE has good reproducibility and high diagnostic efficacy. However, there are very few independent studies on the diagnostic value of SWE in breast NMLs.

aimTo determine the value of SWE in the differential diagnosis of breast NMLs.

methodsThis study enrolled a total of 118 patients with breast NMLs who underwent SWE examinations in the Beijing Shijitan Hospital Affiliated to Capital Medical University and The Second Hospital of Shandong University from January 2019 to January 2020. The internal elastic parameters of the lesions were recorded, including maximum (Emax), mean (Emean) and minimum elastic values and the standard deviation. The following peripheral parameters were noted: Presence of a "stiff rim" sign; Emax, and Emean elasticity values within 1 mm, 1.5 mm, 2 mm, 2.5 mm and 3 mm from the edge of NMLs. The receiver operating characteristic curve of each parameter was drawn, and the areas under the curve were calculated.

resultsEmax, Emean and elastic values, and the standard deviation of the internal elastic values in malignant NMLs were significantly higher than those in benign NMLs (

conclusionThe "stiff rim" sign and multiple quantitative elastic values within and around the lesion had good diagnostic performance in the differential diagnosis of breast NMLs. Emax in peripheral tissue had better diagnostic efficiency than other parameters.

Indexed as

Breast tumorDiagnosisNon-mass lesionsShear wave elastographyStiff rim signUltrasound

Identifiers

PMID32607328
PMCPMC7322423
OpenAlexW3038058190

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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.