Breast cancer risk factors in relation to breast density (United States)
This review provides an overview of breast density, specifically by defining breast density, exploring the association between breast density and breast cancer. Breast density is a measure that compares the amount of fatty tissue to the amount of breast tissue on a mammogram. Research has shown that women with . Oct 1, One of the strongest known risk factors for breast cancer is high breast density — that is, relatively little fat in the breast and more connective.
The effects of HRT on breast density persisted for the 2-year duration of the study. In contrast, one observes an increase in apparent mammographic breast density when patients experience significant weight loss, as in individuals following bariatric surgery. Obesity is related to increased cancer incidence in postmenopausal women, creating a paradoxical increase in cancer with decreased breast density. The exact mechanism is unknown but is attributed to an increase in local estradiol levels in breast fat secondary to local adipocyte aromatase activity.
Breast Density as an Independent Risk Factor for Cancer
Models including BMI, dense area and non-dense area, showed statistically significant independent positive correlation with breast cancer risk of the non-dense, or fatty breast. In postmenopausal women, cancer incidence is independent of serum estrogen levels, suggesting that higher local tissue estrogen levels may be more important in cancer development. Leptin promotes proliferation and enhances cancer cell growth, and adiponectin enhances apoptosis, decreases cell proliferation, and also enables the use of insulin.
In obesity, leptin levels are elevated and adiponectin levels are low, possibly explaining the association of higher cancer incidence in this population. DCIS has been associated with mammographically dense tissue,27 but there is little evidence that this is true for invasive cancers.
Most invasive cancers occur in the upper outer quadrant of the breast, the location of the greatest concentration of breast parenchyma.
Dense Breasts: Breast Cancer Risk Factors
Increasing the Accuracy of Quantitative Measurement Measurements of breast density have historically been achieved either by visual inspection, or the application of a computer-assisted threshold method, in which the operator determines the distinction between dense and non-dense areas as described above.
Although there has been considerably high intra-observer and inter-observer concordance reported, visual setting of a threshold is quite subjective. The two dimensional measurements cannot account for the nonuniform thickness of the periphery of the compressed breast, the 3-D non-uniformity of glandular tissue distribution, and the fact that quantification will always be subject to breast positioning Fig.
In addition, published reports use a variety of measures including absolute and percent area density. Newer volumetric methods incorporate the Digital Imaging and Communications in Medicine DICOM data from the full field digital mammography FFDM image to quantify the amount of breast tissue, using both absolute and percent relative density by volume. These methods incorporate the effect of beam energy for the different target-filter combinations, half-value layer HVLkVp, and mAs, as well as compression thickness and degree of compression,30 and are highly reproducible for the data set of each image.
Few studies are currently published to validate this volumetric approach. One comparison of threshold and volumetric methods showed no clear advantage in showing correlation with known breast cancer risk factors in a cohort of screening cases,31 but a larger body of work is emerging.
Although changes in breast density have not been proven to confer protection or increase risk, the use of breast density as a biomarker for risk remains valid. If histologic changes could be matched to the imaging changes in breast density, the possibility of altering risk and preventing cancers becomes even more compelling. Other risk reduction strategies have been evaluated with mixed results. The risk reduction increases with increasing activity.
Raloxifene has been shown to have a lesser effect on breast density Fig. This confirmed the results of prior studies and offered insights into the potential of this tool to eliminate the subjective nature of human measurements. If increased PBD conveys a higher risk for breast cancer, can intervention to diminish breast density be protective?
This, in part, depends on defining what contributes to breast density. Ductal and acinar epithelium is the site of breast cancer development, but abundant research suggests that density is not solely related to the presence of greater volumes of epithelium.
Aromatase is an enzyme responsible for converting androgens to estrogens on a local level. Through the study of core biopsy tissue, it has been shown that the stromal cells have higher levels of aromatase immunoreactivity than the epithelial cells in areas of dense breast tissue.
The contribution of collagen to breast density was studied from random sections of subcutaneous mastectomy specimens at autopsy. Interestingly, the percentage of collagen was decreased with increasing parity and number of live births, commonly cited factors that decrease breast cancer risk.
There is a strong body of evidence that the extracellular milieu of the fibroglandular tissue is as important as the epithelium in carcinogenesis. Following microdissection of epithelium from the surrounding tissues, transcriptional profiling can differentiate the effects related to these epithelial cells verses the stroma, consisting of fibroblasts, myoepithelial cells and extracellular matrix.
Carcinoma-associated fibroblasts CAF are shown to promote tumorigenic conversion of initiated epithelial cells when added to epithelial cell cultures. Fibroblasts and myoepithelial cells from normal tissue are shown to suppress this transition. The transformation of these stromal cells is key in the transition of normal epithelial cells to invasive disease. IGF-1 influences breast development and higher levels are found in women with dense breast tissue.
Interestingly, breast density and IGF-1 decrease with age. Tamoxifen also decreases IGF-1 levels. As an independent marker, it can also be influenced by interventions such as hormone therapy, diet, physical activity, and SERMs. In addition, high breast density decreases the conspicuity of breast lesions, and delay in the diagnosis of breast cancer remains in the top five errors in radiology malpractice claims.
Cyclical hormone changes influence breast density, but effect is conveyed long-term effect is uncertain. The potential to prevent more cancers through intervention is an attractive subject of much research. Commercialization of volumetric technology that provides an objective quantification of breast density is available and its use is becoming wide spread. Incorporation of this information in the breast cancer risk assessment should be studied and its value to population health management determined.
New data derived from technological advances in bioscience and volumetric measurement should further elucidate the important relationship between PBD and cancer. As a result, cost effective strategies for the stratification of risk and the informed application of supplemental breast cancer screening for women in any given population may be possible. Effect of mammographic breast density on breast cancer screening performance: J Epidemol Community Health ; 52 4: Individual and combined effects of age, breast density and hormone replacement therapy use on the accuracy of screening mammography.
Ann Intern Med ; Quantitative classification of mammographic densities and breast cancer risk: J Natl Cancer Inst ; 97 Effects of postmenopausal hormonal replacement therapy on mammographic density and parenchymal pattern. Radiology ; 2: Effect of Tamoxifen on Mammographic Density. Cancer Epidemiol Biomarkers Prev ; 9 9: Breast patterns as an index of risk for developing breast cancer. Am J Roentgenol ; 6: American College of Radiology, Byrne C, Schairer C, Wolfe j, et al.
Mammographic features and Breast Cancer Risk: An early method of categorizing breast patterns divided breasts into four types depending on their predominant tissue composition.
Radiologists adopted these categories, but classification of an individual breast depended on the opinion of the radiologist reading the mammogram. Later, the BI-RADS system of the American Society of Radiologists continued the four-group categorization, with breasts classed as almost entirely fat, having scattered fibroglandular tissue, being heterogeneously dense, or as extremely dense. More recently, scientists have developed methods to quantify dense breast tissue by measuring the area occupied by the entire breast on a mammogram, then measuring the area appearing as dense and calculating the percentage that is dense.
Researchers have attempted to make the measurement process more objective by having computers classify and measure the dense vs. Hormones are known to affect breast density. So far, two patients have shown a reduction in breast density. Experts agree that dense areas on mammograms make cancer detection more difficult. The epidemiological data used in this analysis arose from three sources: The questionnaire collected height, weight, place of birth, ethnicity, marital status, education, insurance coverage, reason for the current visit, past history of clinical breast examinations and mammography, age at menarche, parity, and age at first birth.
The questionnaire also queried women regarding the date of their last menstrual period and history of gynecological surgery. The clinical assessment form obtained the type of exam conducted at current visit, breast density, examination outcomes and recommendation for further work-up or follow-up.
Patient intake and clinical assessment forms are also completed at subsequent mammography visits, and the questionnaire is updated as possible.
Breast density becoming an important predictor of breast cancer risk
Breast density, the outcome variable, estimates the proportion of fibroglandular tissue in the breast, relative to fat. In the event of discordance in the density of the right and left breast, the woman was classified according to the higher density classification.
Breast density readings were available for When data for variables other than HT use were unavailable for the date of the mammogram, we searched forward in the NHMN records to retrieve replacement information corresponding to a subsequent mammography visit. OR were computed using the cutpoints shown in the tables. Tests of trend and the corresponding OR were based on the categorical age at menarche or the continuous form of the variable age, BMI, age at first birth, parityin accordance with the method of data collection.
Model building began with terms representing the main effects, and included interaction terms involving age, BMI, and menopausal status as suggested by visual inspection of the stratified analyses.