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Mammographic Density: Biology and Clinical Applications

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

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 36155

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Special Issue Editors

Dr. Wendy Ingman

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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

Dr. Kara Britt

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Guest Editor

Peter MacCallum Cancer Centre, Melbourne, Australia
Interests: breast cancer; breast cancer risk; mammographic density; parity; stem cells

Dr. Pallave Dasari

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Guest Editor

The University of Adelaide, Adelaide, Australia
Interests: breast cancer; immunology; health policy

Special Issue Information

Dear Colleagues,

Mammographic density refers to the white and bright regions of a mammogram and reflects the architecture and composition of breast tissue. The last 40 years of research has clearly demonstrated that high mammographic density is both an independent risk factor for breast cancer and masks tumours on a mammogram. There is growing awareness amongst governments, health professionals, and consumers that incorporating mammographic density into patient care can improve the early detection of breast cancer.

Mammographic density is on the cusp of becoming a widespread health assessment tool used to identify the women most at risk of breast cancer in order to intervene early and reduce that risk. Recent advances have explored novel measurement approaches and risk assessment tools and identified new therapeutic targets. However, the underlying biological mechanisms that lead to high mammographic density, the casual factors behind its association with breast cancer risk, and how we can apply this knowledge to improving patient outcomes is still being uncovered.

In this Special Issue, we are calling for manuscripts that will help 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.

Assoc. Prof. Wendy Ingman
Dr. Kara Britt
Dr. Pallave Dasari
Guest Editors

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Keywords

Mammographic density
Breast cancer risk
Mammography
Epithelial cells
Stroma
Adipocytes
Breast imaging
Prevention
Early detection
Epidemiology

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Published Papers (8 papers)

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Research

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12 pages, 1095 KiB

Open AccessArticle

Confusion and Anxiety Following Breast Density Notification: Fact or Fiction?

by Evenda K. Dench, Ellie C. Darcey, Louise Keogh, Kirsty McLean, Sarah Pirikahu, Christobel Saunders, Sandra Thompson, Catherine Woulfe, Elizabeth Wylie and Jennifer Stone

J. Clin. Med. 2020, 9(4), 955; https://doi.org/10.3390/jcm9040955 - 30 Mar 2020

Cited by 14 | Viewed by 3162

Abstract

In the absence of evidence-based screening recommendations for women with dense breasts, it is important to know if breast density notification increases women’s anxiety. This study describes psychological reactions and future screening intentions of women attending a public mammographic screening program in Western Australia. Two-thirds of notified women indicated that knowing their breast density made them feel informed, 21% described feeling anxious, and 23% confused. Of the notified women who reported anxiety, 96% intended to re-screen when due (compared to 91% of all notified women and 93% of controls; p = 0.007 and p < 0.001, respectively). In summary, reported anxiety (following breast density notification) appears to increase women’s intentions for future screening, not the reverse. Full article

(This article belongs to the Special Issue Mammographic Density: Biology and Clinical Applications)

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12 pages, 858 KiB

Open AccessArticle

Using Whole Breast Ultrasound Tomography to Improve Breast Cancer Risk Assessment: A Novel Risk Factor Based on the Quantitative Tissue Property of Sound Speed

by Neb Duric, Mark Sak, Shaoqi Fan, Ruth M. Pfeiffer, Peter J. Littrup, Michael S. Simon, David H. Gorski, Haythem Ali, Kristen S. Purrington, Rachel F. Brem, Mark E. Sherman and Gretchen L. Gierach

J. Clin. Med. 2020, 9(2), 367; https://doi.org/10.3390/jcm9020367 - 29 Jan 2020

Cited by 31 | Viewed by 5431

Abstract

Mammographic percent density (MPD) is an independent risk factor for developing breast cancer, but its inclusion in clinical risk models provides only modest improvements in individualized risk prediction, and MPD is not typically assessed in younger women because of ionizing radiation concerns. Previous studies have shown that tissue sound speed, derived from whole breast ultrasound tomography (UST), a non-ionizing modality, is a potential surrogate marker of breast density, but prior to this study, sound speed has not been directly linked to breast cancer risk. To that end, we explored the relation of sound speed and MPD with breast cancer risk in a case-control study, including 61 cases with recent breast cancer diagnoses and a comparison group of 165 women, frequency matched to cases on age, race, and menopausal status, and with a recent negative mammogram and no personal history of breast cancer. Multivariable odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for the relation of quartiles of MPD and sound speed with breast cancer risk adjusted for matching factors. Elevated MPD was associated with increased breast cancer risk, although the trend did not reach statistical significance (OR per quartile = 1.27, 95% CI: 0.95, 1.70; p_trend = 0.10). In contrast, elevated sound speed was significantly associated with breast cancer risk in a dose–response fashion (OR per quartile = 1.83, 95% CI: 1.32, 2.54; p_trend = 0.0003). The OR trend for sound speed was statistically significantly different from that observed for MPD (p = 0.005). These findings suggest that whole breast sound speed may be more strongly associated with breast cancer risk than MPD and offer future opportunities for refining the magnitude and precision of risk associations in larger, population-based studies, including women younger than usual screening ages. Full article

(This article belongs to the Special Issue Mammographic Density: Biology and Clinical Applications)

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20 pages, 843 KiB

Open AccessArticle

Relationship of Serum Progesterone and Progesterone Metabolites with Mammographic Breast Density and Terminal Ductal Lobular Unit Involution among Women Undergoing Diagnostic Breast Biopsy

by Manila Hada, Hannah Oh, Shaoqi Fan, Roni T. Falk, Berta Geller, Pamela Vacek, Donald Weaver, John Shepherd, Jeff Wang, Bo Fan, Sally Herschorn, Louise A. Brinton, Xia Xu, Mark E. Sherman, Britton Trabert and Gretchen L. Gierach

J. Clin. Med. 2020, 9(1), 245; https://doi.org/10.3390/jcm9010245 - 17 Jan 2020

Cited by 8 | Viewed by 3375

Abstract

The association of progesterone/progesterone metabolites with elevated mammographic breast density (MBD) and delayed age-related terminal duct lobular unit (TDLU) involution, strong breast cancer risk factors, has received limited attention. Using a reliable liquid chromatography-tandem mass-spectrometry assay, we quantified serum progesterone/progesterone metabolites and explored cross-sectional relationships with MBD and TDLU involution among women, ages 40–65, undergoing diagnostic breast biopsy. Quantitative MBD measures were estimated in pre-biopsy digital mammograms. TDLU involution was quantified in diagnostic biopsies. Adjusted partial correlations and trends across MBD/TDLU categories were calculated. Pregnenolone was positively associated with percent MBD-area (MBD-A, rho: 0.30; p-trend = 0.01) among premenopausal luteal phase women. Progesterone tended to be positively associated with percent MBD-A among luteal phase (rho: 0.26; p-trend = 0.07) and postmenopausal (rho: 0.17; p-trend = 0.04) women. Consistent with experimental data, implicating an elevated 5α-pregnanes/3α-dihydroprogesterone (5αP/3αHP) metabolite ratio in breast cancer, higher 5αP/3αHP was associated with elevated percent MBD-A among luteal phase (rho: 0.29; p-trend = 0.08), but not postmenopausal women. This exploratory analysis provided some evidence that endogenous progesterone and progesterone metabolites might be correlated with MBD, a strong breast cancer risk factor, in both pre- and postmenopausal women undergoing breast biopsy. Additional studies are needed to understand the role of progesterone/progesterone metabolites in breast tissue composition and breast cancer risk. Full article

(This article belongs to the Special Issue Mammographic Density: Biology and Clinical Applications)

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11 pages, 764 KiB

Open AccessArticle

Mammographic Density and Screening Sensitivity, Breast Cancer Incidence and Associated Risk Factors in Danish Breast Cancer Screening

by Elsebeth Lynge, Ilse Vejborg, Zorana Andersen, My von Euler-Chelpin and George Napolitano

J. Clin. Med. 2019, 8(11), 2021; https://doi.org/10.3390/jcm8112021 - 19 Nov 2019

Cited by 26 | Viewed by 4454

Abstract

Background: Attention in the 2000s on the importance of mammographic density led us to study screening sensitivity, breast cancer incidence, and associations with risk factors by mammographic density in Danish breast cancer screening programs. Here, we summarise our approaches and findings. Methods: Dichotomized density codes: fatty, equal to BI-RADS density code 1 and part of 2, and other mixed/dense data from the 1990s—were available from two counties, and BI-RADS density codes from one region were available from 2012/13. Density data were linked with data on vital status, incident breast cancer, and potential risk factors. We calculated screening sensitivity by combining data on screen-detected and interval cancers. We used cohorts to study high density as a predictor of breast cancer risk; cross-sectional data to study the association between life style factors and density, adjusting for age and body mass index (BMI); and time trends to study the prevalence of high density across birth cohorts. Results: Sensitivity decreased with increasing density from 78% in women with BI-RADS 1 to 47% in those with BI-RADS 4. For women with mixed/dense compared with those with fatty breasts, the rate ratio of incident breast cancer was 2.45 (95% CI 2.14–2.81). The percentage of women with mixed/dense breasts decreased with age, but at a higher rate the later the women were born. Among users of postmenopausal hormone therapy, the percentage of women with mixed/dense breasts was higher than in non-users, but the patterns across birth cohorts were similar. The occurrence of mixed/dense breast at screening age decreased by a z-score unit of BMI at age 13—odds ratio (OR) 0.56 (95% CI 0.53–0.58)—and so did breast cancer risk and hazard ratio (HR) 0.92 (95% CI 0.84–1.00), but it changed to HR 1.01 (95% CI 0.93–1.11) when controlled for density. Age and BMI adjusted associations between life style factors and density were largely close to unity; physical activity OR 1.06 (95% CI 0.93–1.21); alcohol consumption OR 1.01 (95% CI 0.81–1.27); air pollution OR 0.96 (95% 0.93–1.01) per 20 μg/m³; and traffic noise OR 0.94 (95% CI 0.86–1.03) per 10 dB. Weak negative associations were seen for diabetes OR 0.61 (95% CI 0.40–0.92) and cigarette smoking OR 0.86 (95% CI 0.75–0.99), and a positive association was found with hormone therapy OR 1.24 (95% 1.14–1.35). Conclusion: Our data indicate that breast tissue in middle-aged women is highly dependent on childhood body constitution while adult life-style plays a modest role, underlying the need for a long-term perspective in primary prevention of breast cancer. Full article

(This article belongs to the Special Issue Mammographic Density: Biology and Clinical Applications)

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15 pages, 669 KiB

Open AccessArticle

Involution of Breast Lobules, Mammographic Breast Density and Prognosis Among Tamoxifen-Treated Estrogen Receptor-Positive Breast Cancer Patients

by Maeve Mullooly, Sarah J. Nyante, Ruth M. Pfeiffer, Renata Cora, Donna Butcher, Lawrence Sternberg, Erin J. Aiello Bowles, Shaoqi Fan, Jonine D. Figueroa, Sheila Weinmann, Robert N. Hoover, Louise A. Brinton, Amy Berrington de Gonzalez, Andrew Glass, Mark E. Sherman and Gretchen L. Gierach

J. Clin. Med. 2019, 8(11), 1868; https://doi.org/10.3390/jcm8111868 - 4 Nov 2019

Cited by 10 | Viewed by 3800

Abstract

Mammographic breast density (MD) reflects breast fibroglandular content. Its decline following adjuvant tamoxifen treated, estrogen receptor (ER)-positive breast cancer has been associated with improved outcomes. Breast cancers arise from structures termed lobules, and lower MD is associated with increased age-related lobule involution. We assessed whether pre-treatment involution influenced associations between MD decline and risk of breast cancer-specific death. ER-positive tamoxifen treated patients diagnosed at Kaiser Permanente Northwest (1990–2008) were defined as cases who died of breast cancer (n = 54) and matched controls (remained alive over similar follow-up; n = 180). Lobule involution was assessed by examining terminal duct lobular units (TDLUs) in benign tissues surrounding cancers as TDLU count/mm², median span and acini count/TDLU. MD (%) was measured in the unaffected breast at baseline (median 6-months before) and follow-up (median 12-months after tamoxifen initiation). TDLU measures and baseline MD were positively associated among controls (p < 0.05). In multivariable regression models, MD decline (≥10%) was associated with reduced risk of breast cancer-specific death before (odds ratio (OR): 0.41, 95% CI: 0.18–0.92) and after (OR: 0.41, 95% CI: 0.18–0.94) adjustment for TDLU count/mm², TDLU span (OR: 0.34, 95% CI: 0.14–0.84), and acini count/TDLU (OR: 0.33, 95% CI: 0.13–0.81). MD decline following adjuvant tamoxifen is associated with reduced risk of breast cancer-specific death, irrespective of pre-treatment lobule involution. Full article

(This article belongs to the Special Issue Mammographic Density: Biology and Clinical Applications)

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Review

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14 pages, 1529 KiB

Open AccessReview

Breast Mammographic Density: Stromal Implications on Breast Cancer Detection and Therapy

by Patricia Fernández-Nogueira, Mario Mancino, Gemma Fuster, Paloma Bragado, Miquel Prats de Puig, Pere Gascón, Francisco Javier Casado and Neus Carbó

J. Clin. Med. 2020, 9(3), 776; https://doi.org/10.3390/jcm9030776 - 12 Mar 2020

Cited by 7 | Viewed by 7155

Abstract

Current evidences state clear that both normal development of breast tissue as well as its malignant progression need many-sided local and systemic communications between epithelial cells and stromal components. During development, the stroma, through remarkably regulated contextual signals, affects the fate of the different mammary cells regarding their specification and differentiation. Likewise, the stroma can generate tumour environments that facilitate the neoplastic growth of the breast carcinoma. Mammographic density has been described as a risk factor in the development of breast cancer and is ascribed to modifications in the composition of breast tissue, including both stromal and glandular compartments. Thus, stroma composition can dramatically affect the progression of breast cancer but also its early detection since it is mainly responsible for the differences in mammographic density among individuals. This review highlights both the pathological and biological evidences for a pivotal role of the breast stroma in mammographic density, with particular emphasis on dense and malignant stromas, their clinical meaning and potential therapeutic implications for breast cancer patients. Full article

(This article belongs to the Special Issue Mammographic Density: Biology and Clinical Applications)

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Other

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8 pages, 614 KiB

Open AccessPerspective

Breast Density Notification: An Australian Perspective

by Wendy V. Ingman, Bernadette Richards, Jacqueline M. Street, Drew Carter, Mary Rickard, Jennifer Stone and Pallave Dasari

J. Clin. Med. 2020, 9(3), 681; https://doi.org/10.3390/jcm9030681 - 3 Mar 2020

Cited by 12 | Viewed by 4196

Abstract

Breast density, also known as mammographic density, refers to white and bright regions on a mammogram. Breast density can only be assessed by mammogram and is not related to how breasts look or feel. Therefore, women will only know their breast density if they are notified by the radiologist when they have a mammogram. Breast density affects a woman’s breast cancer risk and the sensitivity of a screening mammogram to detect cancer. Currently, the position of BreastScreen Australia and the Royal Australian and New Zealand College of Radiologists is to not notify women if they have dense breasts. However, patient advocacy organisations are lobbying for policy change. Whether or not to notify women of their breast density is a complex issue and can be framed within the context of both public health ethics and clinical ethics. Central ethical themes associated with breast density notification are equitable care, patient autonomy in decision-making, trust in health professionals, duty of care by the physician, and uncertainties around evidence relating to measurement and clinical management pathways for women with dense breasts. Legal guidance on this issue must be gained from broad legal principles found in the law of negligence and the test of materiality. We conclude a rigid legal framework for breast density notification in Australia would not be appropriate. Instead, a policy framework should be developed through engagement with all stakeholders to understand and take account of multiple perspectives and the values at stake. Full article

(This article belongs to the Special Issue Mammographic Density: Biology and Clinical Applications)

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13 pages, 740 KiB

Open AccessCommentary

Going Beyond Conventional Mammographic Density to Discover Novel Mammogram-Based Predictors of Breast Cancer Risk

by John L Hopper, Tuong L Nguyen, Daniel F Schmidt, Enes Makalic, Yun-Mi Song, Joohon Sung, Gillian S Dite, James G Dowty and Shuai Li

J. Clin. Med. 2020, 9(3), 627; https://doi.org/10.3390/jcm9030627 - 26 Feb 2020

Cited by 22 | Viewed by 3762

Abstract

This commentary is about predicting a woman’s breast cancer risk from her mammogram, building on the work of Wolfe, Boyd and Yaffe on mammographic density. We summarise our efforts at finding new mammogram-based risk predictors, and how they combine with the conventional mammographic density, in predicting risk for interval cancers and screen-detected breast cancers across different ages at diagnosis and for both Caucasian and Asian women. Using the OPERA (odds ratio per adjusted standard deviation) concept, in which the risk gradient is measured on an appropriate scale that takes into account other factors adjusted for by design or analysis, we show that our new mammogram-based measures are the strongest of all currently known breast cancer risk factors in terms of risk discrimination on a population-basis. We summarise our findings graphically using a path diagram in which conventional mammographic density predicts interval cancer due to its role in masking, while the new mammogram-based risk measures could have a causal effect on both interval and screen-detected breast cancer. We discuss attempts by others to pursue this line of investigation, the measurement challenge that allows different measures to be compared in an open and transparent manner on the same datasets, as well as the biological and public health consequences. Full article

(This article belongs to the Special Issue Mammographic Density: Biology and Clinical Applications)

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