Recent Advances in Breast Cancer Screening

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Oncology".

Deadline for manuscript submissions: closed (15 July 2024) | Viewed by 2764

Special Issue Editors


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Guest Editor
Breast Imaging Division, IEO European Institute of Oncology IRCCS, Milan, Italy
Interests: breast cancer

Special Issue Information

Dear Colleagues,

Breast cancer is the most prevalent cancer among women worldwide. In recent decades, substantial advances in breast imaging have provided improved methods for reaching early diagnosis, increasing the survival rates in women with breast cancer.

As breast imaging technologies have become more advanced, radiologists have gained the ability to detect the smallest of malignancies at very early stages; now more than ever, women have a fighting chance against breast cancer. Particularly, advances in medical imaging and genetic knowledge and the introduction of artificial intelligence technology in radiological practice have paved the way to true personalized medicine.

Mammography is currently the only screening test that has been shown to reduce breast cancer-related mortality. However, the large amount of mammography produced every year, the consequent high proportion of false-negative and false-positive results reported, and the shortage of trained radiologists capable of interpreting these exams are just part of the screening management problem, leading to additional economical costs and inequalities between low- and high-income countries.

Recently, mammography by full-field digital mammography systems, including digital breast tomosynthesis and contrast-enhanced spectral mammography, optimized the lesion to background contrast with resultant improvement in the sensitivity of the technique for cancer detection, facilitated by computer-aided detection.

Advances in ultrasound (including automated breast ultrasound) also have the potential to greatly improve the specificity of breast imaging with regard to cancer detection and lesion characterization.

Additionally, several large studies indicate that magnetic resonance imaging (MRI) has a role in early diagnosis of high-risk patients, in addition to its role in staging (facilitating the choice of the most appropriate surgery) and in the assessment of the response to chemotherapy and endocrine therapy.

Such advances in medical imaging together with the introduction of artificial intelligence technology in radiological practice have paved the way to a true personalized medicine. As clinicians gather more and better evidence of how effective these technologies are, they are consistently re-evaluating their methods in an effort to provide a more personalized approach to breast cancer screening based on patients’ individual risk factors.

For this Special Issue, we are soliciting original studies, meta-analysis, reviews, pictorial review, and letters investigating the new frontiers of breast cancer screening.

Dr. Anna Rotili
Dr. Filippo Pesapane
Guest Editors

Manuscript Submission Information

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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. Medicina 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 2200 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
  • cancer screening
  • breast screening
  • breast imaging
  • oncology
  • mammography
  • magnetic resonance imaging
  • contrast enhanced mammography
  • ultrasound
  • personalized medicine
  • radiomics
  • artificial intelligence

Published Papers (1 paper)

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