Evidence map›Paper›PMID 38473232›Full record

ArticleCancers2024

The Correlation between Morpho-Dynamic Contrast-Enhanced Mammography (CEM) Features and Prognostic Factors in Breast Cancer: A Single-Center Retrospective Analysis.

Claudia Lucia Piccolo, Ilenia Celli, Claudio Bandini, Manuela Tommasiello, Matteo Sammarra, Lorenzo Faggioni, Dania Cioni, Bruno Beomonte Zobel, Emanuele Neri

Abstract read
In one paragraph

Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

9 authors.

Claudia Lucia PiccoloDepartment of Radiology, Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy.
Ilenia CelliDepartment of Radiology, Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy.
Claudio BandiniDepartment of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy.
Manuela TommasielloDepartment of Radiology, Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy.
Matteo SammarraDepartment of Radiology, Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy.
Lorenzo FaggioniDepartment of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy.ORCID 0000-0001-5262-4489
Dania CioniDepartment of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy.ORCID 0000-0002-5120-886X
Bruno Beomonte ZobelDepartment of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 00128 Roma, Italy.ORCID 0000-0001-9227-5535
Emanuele NeriDepartment of Translational Research, Academic Radiology, University of Pisa, 56126 Pisa, Italy.ORCID 0000-0001-7950-4559

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer, a major contributor to female mortality globally, presents challenges in detection, prompting exploration beyond digital mammography. Contrast-Enhanced Mammography (CEM), integrating morphological and functional information, emerges as a promising alternative, offering advantages in cost-effectiveness and reduced anxiety compared to MRI. This study investigates CEM's correlation with breast cancer prognostic factors, encompassing histology, grade, and molecular markers. In a retrospective analysis involving 114 women, CEM revealed diverse lesion characteristics. Statistical analyses identified correlations between specific CEM features, such as spiculated margins and irregular shape, and prognostic factors like tumor grade and molecular markers. Notably, spiculated margins predicted lower grade and HER2 status, while irregular shape correlated with PgR and Ki-67 status. The study emphasizes CEM's potential in predicting breast cancer prognosis, shedding light on tumor behavior. Despite the limitations, including sample size and single-observer analysis, the findings advocate for CEM's role in stratifying breast cancers based on biological characteristics. CEM features, particularly spiculated margins, irregular shape, and enhancement dynamics, may serve as valuable indicators for personalized treatment decisions. Further research is crucial to validate these correlations and enhance CEM's clinical utility in breast cancer assessment.

Indexed as

breast cancercontrast-enhanced mammographycontrast mediamagnetic resonance imaging

Identifiers

PMID38473232
PMCPMC10931312

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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.