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Mammographic Density: Detection and Prevention of Breast Cancer
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Mammographic Density: Detection and Prevention of Breast Cancer

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Oncology".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 5134

Special Issue Editor

Dr. Wendy Ingman

E-Mail Website
Guest Editor
1. Discipline of Surgical Specialties, Adelaide Medical School, University of Adelaide, The Queen Elizabeth Hospital, Woodville South, SA 5011, Australia
2. Robinson Research Institute, University of Adelaide, Adelaide, SA 5006, Australia
Interests: breast cancer; breast development; mammary gland biology; mammographic density; lactation; menstrual cycle; predictive biomarkers; mastitis; breast cancer imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Past research has clearly shown that high mammographic density is both an independent risk factor for breast cancer and masks tumors on a mammogram. However, knowledge regarding how to use this knowledge to improve breast cancer detection and how we could reduce breast cancer risk associated with high mammographic density has been elusive.

In this Special Issue, we are calling for manuscripts that will help to advance our understanding of mammographic density to improve the detection and prevention of breast cancer. We invite original research articles, reviews, and current opinions on all aspects of mammographic density including biology, epidemiology, and clinical medicine.

Dr. Wendy Ingman 
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. Journal of Clinical Medicine 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 2600 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

  • Mammographic density
  • Breast cancer
  • Cancer detection
  • Breast cancer prevention

Published Papers (2 papers)

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Research

21 pages, 3905 KiB  
Article
Immune Regulation of Mammary Fibroblasts and the Impact of Mammographic Density
by Maddison Archer, Pallave Dasari, David Walsh, Kara L. Britt, Andreas Evdokiou and Wendy V. Ingman
J. Clin. Med. 2022, 11(3), 799; https://doi.org/10.3390/jcm11030799 - 02 Feb 2022
Cited by 4 | Viewed by 2361
Abstract
Mammographic density is associated with a 4–6-fold increase in breast cancer risk independent of age and BMI. High mammographic density is characterized by breast tissue with high proportions of stroma comprised of fibroblasts, collagen, and immune cells. This study sought to investigate whether [...] Read more.
Mammographic density is associated with a 4–6-fold increase in breast cancer risk independent of age and BMI. High mammographic density is characterized by breast tissue with high proportions of stroma comprised of fibroblasts, collagen, and immune cells. This study sought to investigate whether stromal fibroblasts from high mammographic density breast tissue contributes to increased extracellular matrix deposition and pro-tumorigenic signaling. Mammary fibroblasts were isolated from women with high and low mammographic density and exposed to immune factors myeloperoxidase (MPO), eosinophil peroxidase (EPO), transforming growth factor beta 1 (TGFB1) and tumour necrosis factor alpha (TNFA) for 72 h and profiled for expression of cancer-associated fibroblast and extracellular matrix regulation markers. No differences in gene expression profiles or collagen production were observed between fibroblasts with high or low mammographic density, and they did not have a differential response to immune mediators. MPO and EPO significantly increased the production of collagen 1. TGFB and TNFA induced variable changes in gene expression. Fibroblasts cultured in vitro from women with high mammographic density do not appear to be inherently different to those from women with low mammographic density. The function of fibroblasts in mammographic density-associated breast cancer risk is likely to be regulated by immune signals from surrounding cells in the microenvironment. Full article
(This article belongs to the Special Issue Mammographic Density: Detection and Prevention of Breast Cancer)
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14 pages, 12982 KiB  
Article
Quantitative Breast Density in Contrast-Enhanced Mammography
by Gisella Gennaro, Melissa L. Hill, Elisabetta Bezzon and Francesca Caumo
J. Clin. Med. 2021, 10(15), 3309; https://doi.org/10.3390/jcm10153309 - 27 Jul 2021
Cited by 2 | Viewed by 1979
Abstract
Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) [...] Read more.
Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the paired datasets were compared by Wilcoxon tests. A multivariate regression model was applied to analyze the relationship between VBD differences and multiple independent variables certainly or potentially affecting VBD. Median VBD was comparable for LE-CEM and DM/DBT (12.73% vs. 12.39%), not evidencing any statistically significant difference (p = 0.5855). VBD differences between LE-CEM and DM were associated with significant differences of glandular volume, breast thickness, compression force and pressure, contact area, and nipple-to-posterior-edge distance, i.e., variables reflecting differences in breast positioning (coefficient of determination 0.6023; multiple correlation coefficient 0.7761). Volumetric breast density was obtained from low-energy contrast-enhanced spectral mammography and was not significantly different from volumetric breast density measured from standard mammograms. Full article
(This article belongs to the Special Issue Mammographic Density: Detection and Prevention of Breast Cancer)
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