Advances in Breast Cancer Imaging

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

Deadline for manuscript submissions: 31 July 2024 | Viewed by 2278

Special Issue Editors


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Guest Editor
1. Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, 1649-004 Lisboa, Portugal
2. UBI, NECE—Research Center in Business Sciences, Universidade da Beira Interior, Rua Marquês d’Ávila e Bolama, 6201-001 Covilhã, Portugal
Interests: breast cancer imaging; medical imaging; image processing; artificial intelligence

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Guest Editor
Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, 1649-004 Lisboa, Portugal
Interests: breast cancer diagnosis and intervention; medical imaging; magnetic resonance imaging; data analytics; artificial intelligence; virtual and augmented reality; digital health

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Guest Editor
Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências da Universidade de Lisboa, 1649-004 Lisboa, Portugal
Interests: breast cancer imaging; digital breast tomosynthesis; positron emission mammography; image reconstruction; image processing

Special Issue Information

Dear Colleagues,

According to the World Health Organization, in 2020, there were over 2 million women newly diagnosed with breast cancer worldwide, and almost 8 million women alive who were diagnosed in the previous 5 years. Breast cancer is not only the most prevalent cancer of all, but it is also the one with the highest societal and economic burden, as accounted for in lost disability-adjusted life years.

Despite all screening programs and technological advances, still over half a million women died worldwide in 2020 from breast cancer. These numbers alone hide a disparate reality between high-, middle- and low-income countries, as the 5-year survival rate after diagnosis in the former is over 90% down to 66% in India and 40% in South Africa, for instance. This means that the successful diagnostic and treatment approaches used in high-income countries should be applied elsewhere. Some of the main barriers to such applications are the limited resources and human expertise in middle- and low-income countries.

We believe that recent technological advances, such as artificial intelligence, can become game changers in this context, providing optimized accessible solutions, upscaling existing medical devices, and empowering healthcare professionals. Therefore, this Special Issue on “Advances in Breast Cancer Imaging” will focus on original research papers and comprehensive reviews, dealing with the specific needs and cutting-edge imaging solutions for breast cancer screening, diagnosis, and therapeutic intervention in middle- and low-income countries, or other work that can be adapted to inspire the development of solutions for this context.

Topics of interest for this Special Issue include, but are not limited to, the following:

  • Risk assessment, screening, and diagnosis;
  • Treatment planning and prognosis;
  • Breast density classification;
  • Optimized visualization methods;
  • Image interpretation;
  • Dose assessment;
  • Image-guided assessment, biopsy, and intervention;
  • User training;
  • Artificial intelligence;
  • Virtual and augmented reality;
  • Digital health;
  • Economics and social impact.

Dr. Ana Isabel Rodrigues Gouveia
Dr. Hugo Alexandre Ferreira
Dr. Nuno Matela
Guest Editors

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 imaging
  • diagnosis
  • mammography
  • ultrasound
  • magnetic resonance imaging
  • positron emission tomography
  • positron emission mammography
  • microwave imaging
  • image-guided intervention
  • artificial intelligence
  • virtual reality
  • augmented reality
  • digital health

Published Papers (2 papers)

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Review

19 pages, 6789 KiB  
Review
New Frontiers in Breast Cancer Imaging: The Rise of AI
by Stephanie B. Shamir, Arielle L. Sasson, Laurie R. Margolies and David S. Mendelson
Bioengineering 2024, 11(5), 451; https://doi.org/10.3390/bioengineering11050451 - 2 May 2024
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Abstract
Artificial intelligence (AI) has been implemented in multiple fields of medicine to assist in the diagnosis and treatment of patients. AI implementation in radiology, more specifically for breast imaging, has advanced considerably. Breast cancer is one of the most important causes of cancer [...] Read more.
Artificial intelligence (AI) has been implemented in multiple fields of medicine to assist in the diagnosis and treatment of patients. AI implementation in radiology, more specifically for breast imaging, has advanced considerably. Breast cancer is one of the most important causes of cancer mortality among women, and there has been increased attention towards creating more efficacious methods for breast cancer detection utilizing AI to improve radiologist accuracy and efficiency to meet the increasing demand of our patients. AI can be applied to imaging studies to improve image quality, increase interpretation accuracy, and improve time efficiency and cost efficiency. AI applied to mammography, ultrasound, and MRI allows for improved cancer detection and diagnosis while decreasing intra- and interobserver variability. The synergistic effect between a radiologist and AI has the potential to improve patient care in underserved populations with the intention of providing quality and equitable care for all. Additionally, AI has allowed for improved risk stratification. Further, AI application can have treatment implications as well by identifying upstage risk of ductal carcinoma in situ (DCIS) to invasive carcinoma and by better predicting individualized patient response to neoadjuvant chemotherapy. AI has potential for advancement in pre-operative 3-dimensional models of the breast as well as improved viability of reconstructive grafts. Full article
(This article belongs to the Special Issue Advances in Breast Cancer Imaging)
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21 pages, 2643 KiB  
Review
Evaluating the Role of Breast Ultrasound in Early Detection of Breast Cancer in Low- and Middle-Income Countries: A Comprehensive Narrative Review
by Roxana Iacob, Emil Radu Iacob, Emil Robert Stoicescu, Delius Mario Ghenciu, Daiana Marina Cocolea, Amalia Constantinescu, Laura Andreea Ghenciu and Diana Luminita Manolescu
Bioengineering 2024, 11(3), 262; https://doi.org/10.3390/bioengineering11030262 - 7 Mar 2024
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Abstract
Breast cancer, affecting both genders, but mostly females, exhibits shifting demographic patterns, with an increasing incidence in younger age groups. Early identification through mammography, clinical examinations, and breast self-exams enhances treatment efficacy, but challenges persist in low- and medium-income countries due to limited [...] Read more.
Breast cancer, affecting both genders, but mostly females, exhibits shifting demographic patterns, with an increasing incidence in younger age groups. Early identification through mammography, clinical examinations, and breast self-exams enhances treatment efficacy, but challenges persist in low- and medium-income countries due to limited imaging resources. This review assesses the feasibility of employing breast ultrasound as the primary breast cancer screening method, particularly in resource-constrained regions. Following the PRISMA guidelines, this study examines 52 publications from the last five years. Breast ultrasound, distinct from mammography, offers advantages like radiation-free imaging, suitability for repeated screenings, and preference for younger populations. Real-time imaging and dense breast tissue evaluation enhance sensitivity, accessibility, and cost-effectiveness. However, limitations include reduced specificity, operator dependence, and challenges in detecting microcalcifications. Automatic breast ultrasound (ABUS) addresses some issues but faces constraints like potential inaccuracies and limited microcalcification detection. The analysis underscores the need for a comprehensive approach to breast cancer screening, emphasizing international collaboration and addressing limitations, especially in resource-constrained settings. Despite advancements, notably with ABUS, the primary goal is to contribute insights for optimizing breast cancer screening globally, improving outcomes, and mitigating the impact of this debilitating disease. Full article
(This article belongs to the Special Issue Advances in Breast Cancer Imaging)
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