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New Insights in Mammographic Density in Breast Cancer Risk, Screening...
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New Insights in Mammographic Density in Breast Cancer Risk, Screening and Detection

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Causes, Screening and Diagnosis".

Deadline for manuscript submissions: closed (28 February 2025) | Viewed by 6942

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,

Breast cancer is a significant health concern in many countries. Therefore, there is a dire need to develop advanced approaches to facilitate its prevention and early detection, thereby improving health outcomes. There is growing awareness of the significance of mammographic density as an independent breast cancer risk factor, which also affects mammographic screening and cancer detection. Together with consumer-led initiatives, multi-disciplinary advancements in mammographic density research are shaping future breast cancer risk reduction strategies as well as screening and detection technologies. This Special Issue invites submissions of papers that provide new insights into mammographic density incorporating biology, epidemiology, clinical medicine, consumer perspective, artificial intelligence, bioengineering, and advanced animal models.

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 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

  • breast cancer
  • mammographic density
  • breast cancer risk
  • breast cancer screening
  • mammography
  • risk reduction
  • consumer-led research
  • multi-disciplinary research

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Published Papers (5 papers)

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Research

27 pages, 5472 KiB  
Article
A Deep Learning Approach for the Classification of Fibroglandular Breast Density in Histology Images of Human Breast Tissue
by Hanieh Heydarlou, Leigh J. Hodson, Mohsen Dorraki, Theresa E. Hickey, Wayne D. Tilley, Eric Smith, Wendy V. Ingman and Ali Farajpour
Cancers 2025, 17(3), 449; https://doi.org/10.3390/cancers17030449 - 28 Jan 2025
Viewed by 613
Abstract
Background: To progress research into the biological mechanisms that link mammographic breast density to breast cancer risk, fibroglandular breast density can be used as a surrogate measure. This study aimed to develop a computational tool to classify fibroglandular breast density in hematoxylin and [...] Read more.
Background: To progress research into the biological mechanisms that link mammographic breast density to breast cancer risk, fibroglandular breast density can be used as a surrogate measure. This study aimed to develop a computational tool to classify fibroglandular breast density in hematoxylin and eosin (H&E)-stained breast tissue sections using deep learning approaches that would assist future mammographic density research. Methods: Four different architectural configurations of transferred MobileNet-v2 convolutional neural networks (CNNs) and four different models of vision transformers were developed and trained on a database of H&E-stained normal human breast tissue sections (965 tissue blocks from 93 patients) that had been manually classified into one of five fibroglandular density classes, with class 1 being very low fibroglandular density and class 5 being very high fibroglandular density. Results: The MobileNet-Arc 1 and ViT model 1 achieved the highest overall F1 scores of 0.93 and 0.94, respectively. Both models exhibited the lowest false positive rate and highest true positive rate in class 5, while the most challenging classification was class 3, where images from classes 2 and 4 were mistakenly classified as class 3. The area under the curves (AUCs) for all classes were higher than 0.98. Conclusions: Both the ViT and MobileNet models showed promising performance in the accurate classification of H&E-stained tissue sections across all five fibroglandular density classes, providing a rapid and easy-to-use computational tool for breast density analysis. Full article
(This article belongs to the Special Issue New Insights in Mammographic Density in Breast Cancer Risk, Screening and Detection)
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11 pages, 1463 KiB  
Article
Vi-PLUS: Pioneering Plane-Wave Ultrasound to Assess Breast Glandular Tissue in Healthy Women—A Pilot Study
by Ioana Bene, Delia Doris Donci, Diana Gherman, Manuela Lavinia Lenghel, Carolina Solomon, Ioana-Teofana Dulgheriu, Diana-Raluca Petea-Balea, Cristiana Augusta Ciortea, Larisa Dorina Ciule, Andrada-Larisa Deac and Anca Ileana Ciurea
Cancers 2025, 17(2), 237; https://doi.org/10.3390/cancers17020237 - 13 Jan 2025
Viewed by 566
Abstract
Background/Objectives: This study pioneers the application of the ViPLUS module, utilizing plane-wave ultrasound to measure breast tissue viscosity and elasticity. The primary goal was to establish normal reference values for viscosity in healthy women. Secondary objectives included exploring correlations between breast tissue viscosity [...] Read more.
Background/Objectives: This study pioneers the application of the ViPLUS module, utilizing plane-wave ultrasound to measure breast tissue viscosity and elasticity. The primary goal was to establish normal reference values for viscosity in healthy women. Secondary objectives included exploring correlations between breast tissue viscosity and breast density categories, hormonal influences, and menstrual cycle phases. Methods: A prospective study was conducted on 245 asymptomatic women. Viscosity and elasticity measurements were obtained using the ViPLUS module, ensuring high reliability with stringent quality control measures. Data were statistically analyzed to evaluate correlations and group differences. Results: The median viscosity value for normal breast parenchyma was 1.7 Pa.s, with no significant variations based on breast density, menopausal status, or menstrual cycle phase. A strong correlation (rho = 0.866, p < 0.001) was observed between elasticity and viscosity values. Conclusions: The findings suggest that breast viscosity is consistent across diverse physiological states, indicating its potential as an independent diagnostic marker. This parameter could be pivotal in future breast cancer screening strategies, especially for younger women and those with dense breasts. Full article
(This article belongs to the Special Issue New Insights in Mammographic Density in Breast Cancer Risk, Screening and Detection)
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16 pages, 815 KiB  
Article
The Prospective Association between Early Life Growth and Breast Density in Young Adult Women
by Rachel Lloyd, Sarah Pirikahu, Jane Walter, Gemma Cadby, Nicole Warrington, Dilukshi Perera, Martha Hickey, Christobel Saunders, Michael Hackmann, David D. Sampson, John Shepherd, Lothar Lilge and Jennifer Stone
Cancers 2024, 16(13), 2418; https://doi.org/10.3390/cancers16132418 - 30 Jun 2024
Viewed by 1384
Abstract
Breast density is a strong intermediate endpoint to investigate the association between early-life exposures and breast cancer risk. This study investigates the association between early-life growth and breast density in young adult women measured using Optical Breast Spectroscopy (OBS) and Dual X-ray Absorptiometry [...] Read more.
Breast density is a strong intermediate endpoint to investigate the association between early-life exposures and breast cancer risk. This study investigates the association between early-life growth and breast density in young adult women measured using Optical Breast Spectroscopy (OBS) and Dual X-ray Absorptiometry (DXA). OBS measurements were obtained for 536 female Raine Cohort Study participants at ages 27–28, with 268 completing DXA measurements. Participants with three or more height and weight measurements from ages 8 to 22 were used to generate linear growth curves for height, weight and body mass index (BMI) using SITAR modelling. Three growth parameters (size, velocity and timing) were examined for association with breast density measures, adjusting for potential confounders. Women who reached their peak height rapidly (velocity) and later in adolescence (timing) had lower OBS-breast density. Overall, women who were taller (size) had higher OBS-breast density. For weight, women who grew quickly (velocity) and later in adolescence (timing) had higher absolute DXA-breast density. Overall, weight (size) was also inversely associated with absolute DXA-breast density, as was BMI. These findings provide new evidence that adolescent growth is associated with breast density measures in young adult women, suggesting potential mediation pathways for breast cancer risk in later life. Full article
(This article belongs to the Special Issue New Insights in Mammographic Density in Breast Cancer Risk, Screening and Detection)
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11 pages, 258 KiB  
Article
Factors Associated with Increased Knowledge about Breast Density in South Australian Women Undergoing Breast Cancer Screening
by Avisak Bhattacharjee, David Walsh, Pallave Dasari, Leigh J. Hodson, Suzanne Edwards, Sarah J. White, Deborah Turnbull and Wendy V. Ingman
Cancers 2024, 16(5), 893; https://doi.org/10.3390/cancers16050893 - 23 Feb 2024
Viewed by 1897
Abstract
Background: There is growing awareness of breast density in women attending breast cancer screening; however, it is unclear whether this awareness is associated with increased knowledge. This study aims to evaluate breast density knowledge among Australian women attending breast cancer screening. Method: This [...] Read more.
Background: There is growing awareness of breast density in women attending breast cancer screening; however, it is unclear whether this awareness is associated with increased knowledge. This study aims to evaluate breast density knowledge among Australian women attending breast cancer screening. Method: This cross-sectional study was conducted on women undergoing breast cancer screening at The Queen Elizabeth Hospital Breast/Endocrine outpatient department. Participants were provided with a questionnaire to assess knowledge, awareness, and desire to know their own breast density. Result: Of the 350 women who participated, 61% were familiar with ‘breast density’ and 57% had ‘some knowledge’. Prior breast density notification (OR = 4.99, 95% CI = 2.76, 9.03; p = 0.004), awareness (OR = 4.05, 95% CI = 2.57, 6.39; p = 0.004), younger age (OR = 0.97, 95% CI = 0.96, 0.99; p = 0.02), and English as the language spoken at home (OR = 3.29, 95% CI = 1.23, 8.77; p = 0.02) were independent predictors of ‘some knowledge’ of breast density. A significant proportion of participants (82%) expressed desire to ascertain their individual breast density. Conclusions: While knowledge of breast density in this Australian cohort is generally quite low, we have identified factors associated with increased knowledge. Further research is required to determine optimal interventions to increase breast density knowledge. Full article
(This article belongs to the Special Issue New Insights in Mammographic Density in Breast Cancer Risk, Screening and Detection)
13 pages, 2202 KiB  
Article
Suspicious Ultrasound-Occult Non-Calcified Mammographic Masses, Asymmetries, and Architectural Distortions Are Moderate Probability for Malignancy
by Ethan O. Cohen, Rachel E. Perry, Ravinder S. Legha, Hilda H. Tso, Kyungmin Shin, Megan E. Speer, Kanchan A. Phalak, Jia Sun and Jessica W. T. Leung
Cancers 2024, 16(3), 655; https://doi.org/10.3390/cancers16030655 - 3 Feb 2024
Cited by 1 | Viewed by 1530
Abstract
Suspicious non-calcified mammographic findings have not been evaluated with modern mammographic technique, and the purpose of this work is to compare the likelihood of malignancy for those findings. To do this, 5018 consecutive mammographically guided biopsies performed during 2016–2019 at a large metropolitan, [...] Read more.
Suspicious non-calcified mammographic findings have not been evaluated with modern mammographic technique, and the purpose of this work is to compare the likelihood of malignancy for those findings. To do this, 5018 consecutive mammographically guided biopsies performed during 2016–2019 at a large metropolitan, community-based hospital system were retrospectively reviewed. In total, 4396 were excluded for targeting calcifications, insufficient follow-up, or missing data. Thirty-seven of 126 masses (29.4%) were malignant, 44 of 194 asymmetries (22.7%) were malignant, and 77 of 302 architectural distortions (AD, 25.5%) were malignant. The combined likelihood of malignancy was 25.4%. Older age was associated with a higher likelihood of malignancy for each imaging finding type (all p ≤ 0.006), and a possible ultrasound correlation was associated with a higher likelihood of malignancy when all findings were considered together (p = 0.012). Two-view asymmetries were more frequently malignant than one-view asymmetries (p = 0.03). There were two false-negative biopsies (98.7% sensitivity and 100% specificity). In conclusion, the 25.4% likelihood of malignancy confirms the recommendation for biopsy of suspicious, ultrasound-occult, mammographic findings. Mammographically guided biopsies were highly sensitive and specific in this study. Older patient age and a possible ultrasound correlation should raise concern given the increased likelihood of malignancy in those scenarios. Full article
(This article belongs to the Special Issue New Insights in Mammographic Density in Breast Cancer Risk, Screening and Detection)
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