Dense breast stromal tissue shows greatly increased concentration of breast epithelium but no increase in its proliferative activity

INTRODUCTION: Increased mammographic density is a strong risk factor for breast cancer. The reasons for this are not clear; two obvious possibilities are increased epithelial cell proliferation in mammographically dense areas and increased breast epithelium in women with mammographically dense breasts. We addressed this question by studying the number of epithelial cells in terminal duct lobular units (TDLUs) and in ducts, and their proliferation rates, as they related to local breast densities defined histologically within individual women. METHOD: We studied deep breast tissue away from subcutaneous fat obtained from 12 healthy women undergoing reduction mammoplasty. A slide from each specimen was stained with the cell-proliferation marker MIB1. Each slide was divided into (sets of) areas of low, medium and high density of connective tissue (CT; highly correlated with mammographic densities). Within each of the areas, the numbers of epithelial cells in TDLUs and ducts, and the numbers MIB1 positive, were counted. RESULTS: The relative concentration (RC) of epithelial cells in high compared with low CT density areas was 12.3 (95% confidence interval (CI) 10.9 to 13.8) in TDLUs and 34.1 (95% CI 26.9 to 43.2) in ducts. There was a much smaller difference between medium and low CT density areas: RC = 1.4 (95% CI 1.2 to 1.6) in TDLUs and 1.9 (95% CI 1.5 to 2.3) in ducts. The relative mitotic rate (RMR; MIB1 positive) of epithelial cells in high compared with low CT density areas was 0.59 (95% CI 0.53 to 0.66) in TDLUs and 0.65 (95% CI 0.53 to 0.79) in ducts; the figures for the comparison of medium with low CT density areas were 0.58 (95% CI 0.48 to 0.70) in TDLUs and 0.66 (95% CI 0.44 to 0.97) in ducts. CONCLUSION: Breast epithelial cells are overwhelmingly concentrated in high CT density areas. Their proliferation rate in areas of high and medium CT density is lower than that in low CT density areas. The increased breast cancer risk associated with increased mammographic densities may simply be a reflection of increased epithelial cell numbers. Why epithelium is concentrated in high CT density areas remains to be explained

Future possibilities in the prevention of breast cancer: Luteinizing hormone-releasing hormone agonists

The cyclic production of estrogen and progesterone by the premenopausal ovary accounts for the steep rise in breast cancer risk in premenopausal women. These hormones are breast cell mitogens. By reducing exposure to these ovarian hormones, agonists of luteinizing hormone-releasing hormone (LHRH) given to suppress ovarian function may prove useful in cancer prevention. To prevent deleterious effects of hypoestrogenemia, the addition of low-dose hormone replacement to the LHRH agonist appears necessary. Pilot data with such an approach indicates it is feasible and reduces mammographic densities

Mammographic density. Measurement of mammographic density

Mammographic density has been strongly associated with increased risk of breast cancer. Furthermore, density is inversely correlated with the accuracy of mammography and, therefore, a measurement of density conveys information about the difficulty of detecting cancer in a mammogram. Initial methods for assessing mammographic density were entirely subjective and qualitative; however, in the past few years methods have been developed to provide more objective and quantitative density measurements. Research is now underway to create and validate techniques for volumetric measurement of density. It is also possible to measure breast density with other imaging modalities, such as ultrasound and MRI, which do not require the use of ionizing radiation and may, therefore, be more suitable for use in young women or where it is desirable to perform measurements more frequently. In this article, the techniques for measurement of density are reviewed and some consideration is given to their strengths and limitations

Greatly increased occurrence of breast cancers in areas of mammographically dense tissue

INTRODUCTION: Mammographic density is a strong, independent risk factor for breast cancer. A critical unanswered question is whether cancers tend to arise in mammographically dense tissue (i.e. are densities directly related to risk or are they simply a marker of risk). This question cannot be addressed by studying invasive tumors because they manifest as densities and cannot be confidently differentiated from the densities representing fibrous and glandular tissue. We addressed this question by studying ductal carcinoma in situ (DCIS), as revealed by microcalcifications. METHOD: We studied the cranio-caudal and the mediolateral-oblique mammograms of 28 breasts with a solitary DCIS lesion. Two experienced radiologists independently judged whether the DCIS occurred in a mammographically dense area, and determined the density of different areas of the mammograms. RESULTS: It was not possible to determine whether the DCIS was or was not in a dense area for six of the tumors. Of the remaining 22 lesions, 21 occurred in dense tissue (test for difference from expected taken as the percentage of density of the 'mammographic quadrant' containing DCIS; P < 0.0001). A preponderance of DCIS (17 out of 28) occurred in the mammographic quadrant with the highest percentage density. CONCLUSION: DCIS occurs overwhelmingly in the mammographically dense areas of the breast, and pre-DCIS mammograms showed that this relationship was not brought about by the presence of the DCIS. This strongly suggests that some aspect of stromal tissue comprising the mammographically dense tissue directly influences the carcinogenic process in the local breast glandular tissue

High-risk mammographic parenchymal patterns and anthropometric measures: a case–control study

Mammographic parenchymal patterns are related to breast cancer risk and are also affected by anthropometric measure. We carried out a case–control study comprising 200 cases with high-risk (P2 and DY) mammographic parenchymal pattern and 200 controls with low-risk (N1 and P1) patterns in order to investigate the effect of body size and shape and breast size on mammographic patterns. Women in the highest quartile of body mass index (BMI) distribution were significantly less likely to have a high-risk pattern (odds ratio (OR) = 0.21, 95% confidence interval (CI) 0.08–0.52, P-value for trend = 0.001) compared to those in the lowest quartile. Relative to women with a waist to hip ratio (WHR) of less than 0.75, the OR of having a high-risk pattern in women with a WHR greater than 0.80 was 0.30 (95% CI 0.14–0.63). Breast size as measured by cup size was significantly and negatively related to high-risk pattern. Our study indicates that both BMI and WHR are negatively associated with high-risk patterns. However, both phenomena are associated with increased risk of breast cancer in post-menopausal women. This negative confounding of two positive risk factors means that the effect of parenchymal patterns on risk will tend to be underestimated when not adjusted for BMI and WHR and vice versa. Thus we may have underestimated the importance of BMI and mammographic parenchymal patterns in the past. Further studies are needed to determine a measure of parenchymal density that is independent of anthropometric measures and breast size. © 1999 Cancer Research Campaig

Experimental manipulation of radiographic density in mouse mammary gland

INTRODUCTION: Extensive mammographic density in women is associated with increased risk for breast cancer. Mouse models provide a powerful approach to the study of human diseases, but there is currently no model that is suited to the study of mammographic density. METHODS: We performed individual manipulations of the stromal, epithelial and matrix components of the mouse mammary gland and examined the alterations using in vivo and ex vivo radiology, whole mount staining and histology. RESULTS: Areas of density were generated that resembled densities in mammographic images of the human breast, and the nature of the imposed changes was confirmed at the cellular level. Furthermore, two genetic models, one deficient in epithelial structure (Pten conditional tissue specific knockout) and one with hyperplastic epithelium and mammary tumors (MMTV-PyMT), were used to examine radiographic density. CONCLUSION: Our data show the feasibility of altering and imaging mouse mammary gland radiographic density by experimental and genetic means, providing the first step toward modelling the biological processes that are responsible for mammographic density in the mouse

The association of mammographic density with ductal carcinoma in situ of the breast: the Multiethnic Cohort

INTRODUCTION: It is well established that women with high mammographic density are at greater risk for breast cancer than are women with low breast density. However, little research has been done on mammographic density and ductal carcinoma in situ (DCIS) of the breast, which is thought to be a precursor lesion to some invasive breast cancers. METHOD: We conducted a nested case-control study within the Multiethnic Cohort, and compared the mammographic densities of 482 patients with invasive breast cancer and 119 with breast DCIS cases versus those of 667 cancer-free control subjects. A reader blinded to disease status performed computer-assisted density assessment. For women with more than one mammogram, mean density values were computed. Polytomous logistic regression models were used to compute adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for two measurements of mammographic density: percentage density and dense area. RESULTS: Mammographic density was associated with invasive breast cancer and breast DCIS. For the highest category of percentage breast density (≥50%) as compared with the lowest (<10%), the OR was 3.58 (95% CI 2.26–5.66) for invasive breast cancer and 2.86 (1.38–5.94) for breast DCIS. Similarly, for the highest category of dense area (≥45 cm(2)) as compared with the lowest (<15 cm(2)), the OR was 2.92 (95% CI 2.01–4.25) for invasive breast cancer and 2.59 (1.39–4.82) for breast DCIS. Trend tests were significant for invasive breast cancer (P for trend < 0.0001) and breast DCIS (P for trend < 0.001) for both percentage density and dense area. CONCLUSION: The similar strength of association for mammographic density with breast DCIS and invasive breast cancer supports the hypothesis that both diseases may have a common etiology

Mammographic density, lobular involution, and risk of breast cancer

In this review, we propose that age-related changes in mammographic density and breast tissue involution are closely related phenomena, and consider their potential relevance to the aetiology of breast cancer. We propose that the reduction in mammographic density that occurs with increasing age, parity and menopause reflects the involution of breast tissue. We further propose that age-related changes in both mammographic density and breast tissue composition are observable and measurable phenomena that resemble Pike's theoretical construct of ‘breast tissue ageing'. Extensive mammographic density and delayed breast involution are both associated with an increased risk of breast cancer and are consistent with the hypothesis of the Pike model that cumulative exposure of breast tissue to hormones and growth factors that stimulate cell division, as well as the accumulation of genetic damage in breast cells, are major determinants of breast cancer incidence

Positive association between mammographic breast density and bone mineral density in the Postmenopausal Estrogen/Progestin Interventions Study

INTRODUCTION: Mammographic breast density is a strong independent risk factor for breast cancer. We hypothesized that demonstration of an association between mammographic breast density and bone mineral density (BMD) would suggest a unifying underlying mechanism influencing both breast density and BMD. METHODS: In a cross-sectional analysis of baseline data from the Postmenopausal Estrogen/Progestin Interventions Study (PEPI), participants were aged 45 to 64 years and were at least 1 year postmenopausal. Mammographic breast density (percentage of the breast composed of dense tissue), the outcome, was assessed with a computer-assisted percentage-density method. BMD, the primary predictor, was measured with dual-energy X-ray absorptiometry. Women quitting menopausal hormone therapy to join PEPI were designated recent hormone users. RESULTS: The mean age of the 594 women was 56 years. The average time since menopause was 5.6 years. After adjustment for age, body mass index, and cigarette smoking, in women who were not recent hormone users before trial enrollment (n = 415), mammographic density was positively associated with total hip (P = 0.04) and lumbar (P = 0.08) BMD. Mammographic density of recent hormone users (n = 171) was not significantly related to either total hip (P = 0.51) or lumbar (P = 0.44) BMD. In participants who were not recent hormone users, mammographic density was 4% greater in the highest quartile of total hip BMD than in the lowest. In participants who were not recent hormone users, mammographic density was 5% greater in the highest quartile of lumbar spine BMD than in the lowest. CONCLUSION: Mammographic density and BMD are positively associated in women who have not recently used postmenopausal hormones. A unifying biological mechanism may link mammographic density and BMD. Recent exogenous postmenopausal hormone use may obscure the association between mammographic density and BMD by having a persistent effect on breast tissue