Evidence map›Paper›PMID 39904358›Full record

ArticleUltraschall in der Medizin (Stuttgart, Germany : 1980)2025

Identification of differentiating sonographic features between fibroadenomas and malignant tumors of the breast mimicking fibroadenomas: 10-year experience in 421 histologically verified cases.

Michael Swoboda, Johannes Deeg, Daniel Egle, Valentin Ladenhauf, Malik Galijasevic, Christoph Plöbst, Silke Haushammer, Birgit Amort, Mathias Pamminger, Leonhard Gruber

Abstract read
In one paragraph

Article in Ultraschall in der Medizin (Stuttgart, Germany : 1980), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Michael SwobodaRadiology, Medical University of Innsbruck, Innsbruck, Austria.
Johannes DeegRadiology, Medical University of Innsbruck, Innsbruck, Austria.ORCID 0000-0002-5139-4287
Daniel EgleDepartment of Gynecology, Medical University of Innsbruck, Innsbruck, Austria.
Valentin LadenhaufRadiology, Medical University of Innsbruck, Innsbruck, Austria.
Malik GalijasevicRadiology, Medical University of Innsbruck, Innsbruck, Austria.
Christoph PlöbstRadiology, Medical University of Innsbruck, Innsbruck, Austria.
Silke HaushammerRadiology, Medical University of Innsbruck, Innsbruck, Austria.
Birgit AmortRadiology, Medical University of Innsbruck, Innsbruck, Austria.
Mathias PammingerRadiology, Medical University of Innsbruck, Innsbruck, Austria.
Leonhard GruberRadiology, Medical University of Innsbruck, Innsbruck, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrasound is a highly effective imaging tool for assessing abnormalities within the breast. However, especially the identification of malignant tumors of the breast mimicking fibroadenomas (MTMF) by means of breast ultrasound can be challenging. This study aimed to identify reliable imaging characteristics of MTMF.This retrospective study was approved by the local ethics review board. After screening 623 patients, 421 cases with histologically verified fibroadenomas and MTMF between 2011 and 2021 were included. Sonographic features were compared to histopathological results and an algorithm-based quantitative ranking of predictors contributing most to the correct classification of malignant tumors was conducted.A total of 363 benign, 18 intermediate, and 40 malignant lesions were analyzed. Algorithm-based quantitative ranking showed that the most predictive features indicating malignancy were a hyperechoic rim (gain ratio merit 0.135 ± 0.004), an irregular border (0.057 ± 0.002), perilesional stiffening (0.054 ± 0.002), pectoral contact (0.051 ± 0.003), an irregular shape (0.029 ± 0.001), and irregular vasculature (0.027 ± 0.002).Ultrasound findings for fibroadenomas vary, making identification of MTMF challenging. Features such as indistinct margins and increased perilesional echogenicity are predictors for malignancy and should be considered during sonographic evaluation of fibroadenomas and MTMF.

Indexed as

Breast NeoplasmsFibroadenomaUltrasonography, MammaryAdultAgedAlgorithmsBreastDiagnosis, DifferentialFemaleHumansMiddle AgedRetrospective StudiesSensitivity and SpecificityYoung Adult

Identifiers

PMID39904358
PMCPMC12143934

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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.