Evidence map›Paper›PMID 39720676›Full record

ArticleInternational journal of women's health2024

Incremental Value of Shear Wave Elastography and Contrast-Enhanced Ultrasound in the Differential Diagnosis of Breast Non-Mass-Like Lesions.

Hui Li, Lixia Chen, Shihao Xu

Abstract read
In one paragraph

Article in International journal of women's health, 2024. 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
–field-weighted citation impact
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.

  1. 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

3 authors.

Hui LiDepartment of Ultrasound Imaging, The First Affiliated Hospital of Wenzhou Medical University, WenZhou, ZheJiang, 325000, People's Republic of China.
Lixia ChenDepartment of Ultrasound Imaging, The First Affiliated Hospital of Wenzhou Medical University, WenZhou, ZheJiang, 325000, People's Republic of China.
Shihao XuDepartment of Ultrasound Imaging, The First Affiliated Hospital of Wenzhou Medical University, WenZhou, ZheJiang, 325000, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To analyse the parameters of shear wave elastography (SWE) and contrast-enhanced ultrasound (CEUS) in breast non-mass-like lesions (NMLs) and to evaluate the added diagnostic value of SWE and CEUS when combined with B-mode ultrasound (US) for differentiating NMLs. Methods: A total of 118 NMLs from 115 patients underwent US, SWE, and CEUS examinations. The SWE parameter with the highest areas under the receiver operating characteristic (ROC) curves (Az) and independent variables of CEUS obtained by logistic regression were used to adjust the BI-RADS-US (Breast Imaging Reporting and Data System for Ultrasound) classification. The adjusted BI-RADS risk stratification was then compared with the original classification. Additionally, the diagnostic effectiveness of US+SWE, US+CEUS, and US+SWE+CEUS combinations was calculated and compared. Results: The "stiff rim sign" was used as the optimal SWE indicator for BI-RADS adjustment. CEUS diagnostic criteria for adjustment included enhancement intensity, enhancement size, and the presence of radial or penetrating vessels. The Az values of US+SWE+CEUS and US+CEUS combinations were significantly higher than that of US alone ( Conclusion: Adding SWE and CEUS to conventional US enhances diagnostic accuracy for NMLs, offering a meaningful incremental value for BI-RADS classification in the assessment of NMLs.

Indexed as

breastcontrast-enhanced ultrasoundnon-mass-like lesionshear wave elastography

Identifiers

PMID39720676
PMCPMC11668051

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.