Evidence map›Paper›PMID 38223094›Full record

ArticleQuantitative imaging in medicine and surgery2024

Multimodal ultrasound imaging for diagnostic differentiation of sclerosing adenosis from invasive ductal carcinoma.

Wen Li, Yan Zheng, Haizhen Liu, Zhengling Tai, Huihui Zhu, Zhaoxi Li, Qinghua Gu, Yonggang Li

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 20% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

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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

8 authors at 5 institutions in 1 country.

Wen Li *Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Yan Zheng *Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Haizhen Liu *Department of Ultrasound, Huadong Sanatorium, Wuxi, China.
Zhengling TaiDepartment of Ultrasound, Huadong Sanatorium, Wuxi, China.
Huihui ZhuDepartment of Ultrasound, Huadong Sanatorium, Wuxi, China.
Zhaoxi LiDepartment of Ultrasound, Huadong Sanatorium, Wuxi, China.
Qinghua GuDepartment of Radiology, Suzhou Yongding Hospital, Suzhou, China.
Yonggang LiDepartment of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
First Affiliated Hospital of Soochow University · CNHuadong Hospital · CNHuadong SanatoriumSoochow University · CNSuzhou Yongding Hospital

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Sclerosing adenosis (SA) is a common proliferative benign lesion without atypia in the breast that may mimic invasive ductal carcinoma (IDC) on medical imaging, leading to it often being misdiagnosed and mistreated. Consequently, the purpose of this study was to assess the diagnostic value of multimodal ultrasound imaging in distinguishing SA from IDC. Methods: Multimodal ultrasound imaging, including automated breast volume scan (ABVS), elasticity imaging (EI), and color Doppler flow imaging (CDFI), were performed on 120 consecutive patients comprising 122 breast lesions (54 SA, 68 IDC). All lesions were pathologically confirmed. Multimodal ultrasound imaging features were compared between the two groups. Binary logistic regression analysis based on ABVS, EI, and CDFI was conducted to formulate a logistic regression equation for differentiating SA from IDC. The diagnostic performances of ABVS, EI, CDFI, and their combination were compared by the receiver operating characteristic (ROC) curve analysis. Results: The sensitivity, specificity, and accuracy of ABVS, EI, CDFI, and their combination in differentiating SA from IDC were, respectively, 75.00%, 72.22%, and 73.77%; 86.76%, 72.22%, and 80.33%; 73.53%, 64.81%, and 69.67%; and 88.24%, 74.07%, and 81.97%. Combining multimodal ultrasound imaging yielded an area under the curve (AUC) of 0.895 (95% confidence interval: 0.827-0.943), which was higher than that of ABVS, EI, and CDFI, with AUC values of 0.736, 0.795, and 0.692, respectively, and the difference was statistically significant (ABVS Conclusions: The preliminary results suggested that multimodal ultrasound imaging can improve the diagnostic accuracy of SA and provide additional information for differential diagnosis of SA and IDC.

Indexed as

automated breast volume scan (ABVS)color Doppler flow imaging (CDFI)elasticity imaging (EI)invasive ductal carcinoma (IDC)multimodal ultrasound imagingSclerosing adenosis (SA)

Identifiers

PMID38223094
PMCPMC10784066
OpenAlexW4390428860

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.