Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
8.0
4.5
Journals
Cancers
Special Issues
Detection of Breast Cancer with Mammography
share announcement

Detection of Breast Cancer with Mammography

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Methods and Technologies Development".

Deadline for manuscript submissions: 15 April 2026 | Viewed by 1247

Special Issue Editor

Dr. Luca Nicosia

E-Mail Website
Guest Editor
Breast Imaging Division, Radiology Department, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy
Interests: breast imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are excited to announce the call for submissions to a Special Issue of Cancers focusing on the topic of "Detection of Breast Cancer with Mammography". Mammography remains one of the most widely used imaging techniques for the early detection of breast cancer. This Special Issue aims to explore the latest advancements, challenges, and opportunities in the field of mammographic screening for breast cancer.

We invite researchers and clinicians to submit original research articles and reviews that cover various aspects of mammography in breast cancer detection, including, but not limited to, the following:

  1. Novel imaging technologies and techniques in mammography;
  2. Computer-aided detection and artificial intelligence in mammography;
  3. The optimization of mammographic screening protocols;
  4. Evaluating the effectiveness and limitations of mammography;
  5. Radiomics and machine learning in mammographic interpretation;
  6. Patient experience and adherence to mammographic screening.

All submitted articles will undergo a rigorous peer review process to ensure the highest scientific quality and relevance to this field. We encourage contributions from experts in the fields of breast cancer research, radiology, and oncology.

By consolidating the latest research findings and clinical experiences, we aim to enhance the accuracy, efficiency, and accessibility of breast cancer detection with mammography. We believe that your valuable contributions will significantly contribute to the success of this Special Issue.

Should you have any questions, require further information, or need any assistance, please do not hesitate to reach out to us. We are here to support and facilitate your participation in this Special Issue.

Thank you for your attention to this matter, and we look forward to receiving your valuable submissions.

Dr. Luca Nicosia
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mammography
  • breast cancer detection
  • imaging technologies
  • artificial intelligence
  • radiomics

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (1 paper)

Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

12 pages, 1742 KiB  
Article
Influence of Breast Density and Menopausal Status on Background Parenchymal Enhancement in Contrast-Enhanced Mammography: Insights from a Retrospective Analysis
by Luca Nicosia, Luciano Mariano, Carmen Mallardi, Adriana Sorce, Samuele Frassoni, Vincenzo Bagnardi, Cristian Gialain, Filippo Pesapane, Claudia Sangalli and Enrico Cassano
Cancers 2025, 17(1), 11; https://doi.org/10.3390/cancers17010011 - 24 Dec 2024
Viewed by 773
Abstract
Background: Contrast-enhanced mammography (CEM) has recently gained recognition as an effective alternative to breast magnetic resonance imaging (MRI) for assessing breast lesions, offering both morphological and functional imaging capabilities. However, the phenomenon of background parenchymal enhancement (BPE) remains a critical consideration, as it [...] Read more.
Background: Contrast-enhanced mammography (CEM) has recently gained recognition as an effective alternative to breast magnetic resonance imaging (MRI) for assessing breast lesions, offering both morphological and functional imaging capabilities. However, the phenomenon of background parenchymal enhancement (BPE) remains a critical consideration, as it can affect the interpretation of images by obscuring or mimicking lesions. While the impact of BPE has been well-documented in MRI, limited data are available regarding the factors influencing BPE in CEM and its relationship with breast cancer (BC) characteristics. Materials: This retrospective study included 116 patients with confirmed invasive BC who underwent CEM prior to biopsy and surgery. Data collected included patient age, breast density, receptor status, tumor grading, and the Ki-67 proliferation index. BPE was evaluated by two radiologists using the 2022 ACR BI-RADS lexicon for CEM. Statistical analyses were conducted to assess the relationship between BPE, patient demographics, and tumor characteristics. Results: The study found a significant association between higher levels of BPE and specific patient characteristics. In particular, increased BPE was more commonly observed in patients with higher breast density (p < 0.001) and those who were pre-menopausal (p = 0.029). Among patients categorized under density level B, the majority exhibited minimal BPE, while those in categories C and D showed progressively higher levels of BPE, indicating a clear trend correlating higher breast density with increased enhancement. Additionally, pre-menopausal patients demonstrated a higher likelihood of moderate to marked BPE compared to post-menopausal patients. Despite these significant associations, the analysis did not reveal a meaningful correlation between BPE intensity and tumor subtypes (p = 0.77) or tumor grade (p = 0.73). The inter-reader agreement for BPE assessment was substantial, as indicated by a weighted kappa of 0.78 (95% CI: 0.68–0.89), demonstrating consistent evaluation between radiologists. Conclusions: These findings suggest that BPE in CEM is influenced by factors like breast density and age, aligning with patterns observed in MRI studies. However, BPE intensity was not associated with tumor subtypes or grades, indicating a poorer prognosis. These insights highlight the potential of BPE as a risk biomarker in preventive follow-up, particularly for patients with high breast density and pre-menopausal status. Further multicentric and prospective studies are needed to validate these results and deepen the understanding of BPE’s role in CEM diagnostics. Full article
(This article belongs to the Special Issue Detection of Breast Cancer with Mammography)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-1
Back to TopTop