Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.0
3.8
Journals
Bioengineering
Special Issues
Breast Cancer: From Precision Medicine to Diagnostics
share announcement

Breast Cancer: From Precision Medicine to Diagnostics

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 935

Special Issue Editor

Dr. Kosuke Kawaguchi

E-Mail Website
Guest Editor
Department of Breast Surgery, Kyoto University Hospital, Graduate School of Medicine, Shogoin Sakyo-ku, Kyoto 606-8507, Japan
Interests: breast cancer; breast imaging

Special Issue Information

Dear Colleagues,

Breast cancer is a complex and heterogeneous disease that affects millions of women worldwide. In recent years, significant advancements have been made in the fields of precision medicine, diagnostics, and novel treatment options for patients with breast cancer. Precision medicine allows for more personalized and targeted treatment strategies based on an individual's unique genetic makeup, helping to improve patient outcomes and reduce the risk of recurrence. Diagnostic tools, such as genetic testing and imaging techniques, have also evolved to provide more accurate and early detection of breast cancer, leading to better prognosis and survival rates.

Novel treatment options, such as immunotherapy and targeted therapies, are revolutionizing the way breast cancer is treated, offering more effective and less toxic alternatives to traditional chemotherapy. These innovative approaches are paving the way for more personalized and tailored treatment plans for patients with breast cancer, ultimately improving survival rates and patients’ quality of life. In this era of rapid advancements in breast cancer research, it is crucial to continue exploring new avenues in precision medicine, diagnostics, and treatment options to further improve outcomes for patients battling this devastating disease.

Dr. Kosuke Kawaguchi
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 short 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. Bioengineering is an international peer-reviewed open access monthly 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 2700 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

  • breast cancer
  • precision medicine
  • diagnostics
  • novel treatment options
  • personalized treatment
  • tumor microenvironment
  • breast imaging

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.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (2 papers)

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

Research

Jump to: Review

19 pages, 620 KiB  
Article
Local Extremum Mapping for Weak Supervision Learning on Mammogram Classification and Localization
by Minjuan Zhu, Lei Zhang, Lituan Wang, Zizhou Wang, Yan Wang and Guangwu Qian
Bioengineering 2025, 12(4), 325; https://doi.org/10.3390/bioengineering12040325 - 21 Mar 2025
Viewed by 357
Abstract
The early and accurate detection of breast lesions through mammography is crucial for improving survival rates. However, the existing deep learning-based methods often rely on costly pixel-level annotations, limiting their scalability in real-world applications. To address this issue, a novel local extremum mapping [...] Read more.
The early and accurate detection of breast lesions through mammography is crucial for improving survival rates. However, the existing deep learning-based methods often rely on costly pixel-level annotations, limiting their scalability in real-world applications. To address this issue, a novel local extremum mapping (LEM) mechanism is proposed for mammogram classification and weakly supervised lesion localization. The proposed method first divides the input mammogram into multiple regions and generates score maps through convolutional neural networks. Then, it identifies the most informative regions by filtering local extrema in the score maps and aggregating their scores for final classification. This strategy enables lesion localization with only image-level labels, significantly reducing annotation costs. Experiments on two public mammography datasets, CBIS-DDSM and INbreast, demonstrate that the proposed method achieves competitive performance. On the INbreast dataset, LEM improves classification accuracy to 96.3% with an AUC of 0.976. Furthermore, the proposed method effectively localizes lesions with a dice similarity coefficient of 0.37, outperforming Grad-CAM and other baseline approaches. These results highlight the practical significance and potential clinical applications of our approach, making automated mammogram analysis more accessible and efficient. Full article
(This article belongs to the Special Issue Breast Cancer: From Precision Medicine to Diagnostics)
►▼ Show Figures

Figure 1

Review

Jump to: Research

15 pages, 1538 KiB  
Review
Breathomics: A Non-Invasive Approach for the Diagnosis of Breast Cancer
by Hélène Yockell-Lelièvre, Romy Philip, Palash Kaushik, Ashok Prabhu Masilamani and Sarkis H. Meterissian
Bioengineering 2025, 12(4), 411; https://doi.org/10.3390/bioengineering12040411 - 12 Apr 2025
Viewed by 363
Abstract
Breast cancer is the most commonly diagnosed cancer worldwide, underscoring the critical need for effective early detection methods to reduce mortality. Traditional detection techniques, such as mammography, present significant limitations, particularly in women with dense breast tissue, highlighting the need for alternative screening [...] Read more.
Breast cancer is the most commonly diagnosed cancer worldwide, underscoring the critical need for effective early detection methods to reduce mortality. Traditional detection techniques, such as mammography, present significant limitations, particularly in women with dense breast tissue, highlighting the need for alternative screening approaches. Breathomics, based on the analysis of Volatile Organic Compounds (VOCs) present in exhaled breath, offers a non-invasive, potentially transformative diagnostic tool. These VOCs are metabolic byproducts from various organs of the human body whose presence and varying concentrations in breath are reflective of different health conditions. This review explores the potential of breathomics, highlighting its promise as a rapid, cost-effective screening approach for breast cancer, facilitated through the integration of portable solutions like electronic noses (e-noses). Key considerations for clinical translation—including patient selection, environmental confounders, and different breath collection methods—will be examined in terms of how each of them affects the breath profile. However, there are also challenges such as patient variability in VOC signatures, and the need for standardization in breath sampling protocols. Future research should prioritize standardizing sampling and analytical procedures and validating their clinical utility through large-scale clinical trials. Full article
(This article belongs to the Special Issue Breast Cancer: From Precision Medicine to Diagnostics)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-2
Back to TopTop