Evidence that breast tissue stiffness is associated with risk of breast cancer.

BACKGROUND: Evidence from animal models shows that tissue stiffness increases the invasion and progression of cancers, including mammary cancer. We here use measurements of the volume and the projected area of the compressed breast during mammography to derive estimates of breast tissue stiffness and examine the relationship of stiffness to risk of breast cancer. METHODS: Mammograms were used to measure the volume and projected areas of total and radiologically dense breast tissue in the unaffected breasts of 362 women with newly diagnosed breast cancer (cases) and 656 women of the same age who did not have breast cancer (controls). Measures of breast tissue volume and the projected area of the compressed breast during mammography were used to calculate the deformation of the breast during compression and, with the recorded compression force, to estimate the stiffness of breast tissue. Stiffness was compared in cases and controls, and associations with breast cancer risk examined after adjustment for other risk factors. RESULTS: After adjustment for percent mammographic density by area measurements, and other risk factors, our estimate of breast tissue stiffness was significantly associated with breast cancer (odds ratio = 1.21, 95% confidence interval = 1.03, 1.43, p = 0.02) and improved breast cancer risk prediction in models with percent mammographic density, by both area and volume measurements. CONCLUSION: An estimate of breast tissue stiffness was associated with breast cancer risk and improved risk prediction based on mammographic measures and other risk factors. Stiffness may provide an additional mechanism by which breast tissue composition is associated with risk of breast cancer and merits examination using more direct methods of measurement.

Is mammographic breast density a breast cancer risk factor in women with BRCA mutations?

PURPOSE: Increased mammographic breast density is well recognized as a breast cancer risk factor in the general population. However, it is unclear whether it is a risk factor in women with BRCA mutations. We present the results of a nested case-control screening study investigating the relationship between breast density and breast cancer incidence in this population. PATIENTS AND METHODS: Women ages 25 to 65 years with known BRCA mutations were enrolled onto a single-center, high-risk breast cancer screening program. Using a computer-aided technique (Cumulus), quantitative percentage density (PD) was measured for each participant on her baseline mammogram by a single, blinded observer. RESULTS: Between November 1997 and March 2008, 462 women (mean age, 44 years; 245 BRCA1 and 217 BRCA2) were screened and 50 breast cancers were diagnosed (38 invasive, 12 ductal carcinoma in situ [DCIS]). Density was not measured in 40 women of whom four developed cancer (three invasive, one DCIS). Mean PD (+/- standard deviation [SD]) for 376 women who did not develop breast cancer was 34% (23) compared with 31% (21) for 46 women with cancer (P = .51). Logistic regression model of breast cancer incidence and PD revealed an odds ratio of 0.99 (+/- 0.01 SD) for a one-unit increase in PD (P = .44). Results remained nonsignificant in multivariate analysis, as well as when women with pure DCIS were excluded. CONCLUSION: Increased mammographic breast density is not associated with higher breast cancer incidence in women with BRCA mutations. On the basis of these findings, density should not be considered a factor for these women in decision making regarding prophylactic surgery or chemoprevention.

Functional imaging using diffuse optical spectroscopy of neoadjuvant chemotherapy response in women with locally advanced breast cancer.

PURPOSE: Functional imaging with tomographic near-infrared diffuse optical spectroscopy (DOS) can measure tissue concentration of deoxyhemoglobin (Hb), oxyhemoglobin (HbO2), percent water (%water), and scattering power (SP). In this study, we evaluated tumor DOS parameters and described their relationship to clinical and pathologic outcome in patients undergoing neoadjuvant therapy for locally advanced breast cancer. EXPERIMENTAL DESIGN: Ten patients were enrolled and intended to undergo five scans each. Scans were taken up to 3 days before treatment and at 1, 4, and 8 weeks after neoadjuvant treatment before surgery. Changes in volume of interest weighted tissue Hb, HbO2, %water, and SP corresponding to the tumor were compared with clinical and pathologic response. RESULTS: All patients' tumor volumes of interest were significantly different compared with background tissue for all parameters. Five patients had a good pathologic response. Four patients were considered nonresponders. One patient initially did not respond to chemotherapy but, after a change in chemotherapy, had a good response. In the five patients with a good response, the mean drop in Hb, HbO2, %water, and SP from baseline to the 4-week scan was 67.6% (SD = 20.8), 58.9% (SD = 20.3), 51.2% (SD = 28.3), and 52.6% (SD = 26.4), respectively. In contrast, the four nonresponders had a mean drop of 17.7% (SD = 9.8), 18.0% (SD = 20.8), 15.4% (SD = 11.7), and 12.6% (SD = 10.2) for Hb, HbO2, %water, and SP, respectively. CONCLUSIONS: Responders and nonresponders were significantly different for all functional parameters at the 4-week scan, except for %water, which approached significance. Thus, DOS could be used as an early detector of tumor response.

Screen-film mammographic density and breast cancer risk: a comparison of the volumetric standard mammogram form and the interactive threshold measurement methods.

BACKGROUND: Mammographic density is a strong risk factor for breast cancer, usually measured by an area-based threshold method that dichotomizes the breast area on a mammogram into dense and nondense regions. Volumetric methods of breast density measurement, such as the fully automated standard mammogram form (SMF) method that estimates the volume of dense and total breast tissue, may provide a more accurate density measurement and improve risk prediction. METHODS: In 2000-2003, a case-control study was conducted of 367 newly confirmed breast cancer cases and 661 age-matched breast cancer-free controls who underwent screen-film mammography at several centers in Toronto, Canada. Conditional logistic regression was used to estimate odds ratios of breast cancer associated with categories of mammographic density, measured with both the threshold and the SMF (version 2.2beta) methods, adjusting for breast cancer risk factors. RESULTS: Median percent density was higher in cases than in controls for the threshold method (31% versus 27%) but not for the SMF method. Higher correlations were observed between SMF and threshold measurements for breast volume/area (Spearman correlation coefficient = 0.95) than for percent density (0.68) or for absolute density (0.36). After adjustment for breast cancer risk factors, odds ratios of breast cancer in the highest compared with the lowest quintile of percent density were 2.19 (95% confidence interval, 1.28-3.72; P(t) <0.01) for the threshold method and 1.27 (95% confidence interval, 0.79-2.04; Pt = 0.32) for the SMF method. CONCLUSION: Threshold percent density is a stronger predictor of breast cancer risk than the SMF version 2.2beta method in digitized images.

Mammographic density and breast cancer risk: evaluation of a novel method of measuring breast tissue volumes.

BACKGROUND: Mammographic density has been found to be strongly associated with risk of breast cancer. We have assessed a novel method of assessing breast tissue that is fully automated, does not require an observer, and measures the volume, rather than the projected area, of the relevant tissues in digitized screen-film mammogram. METHODS: Sixteen mammography machines in seven locations in Toronto were calibrated to allow the estimation of the proportion of radiologically dense (stromal and epithelial tissue) and nondense (fatty) tissue represented in each pixel of the mammographic image. This information was combined with a measurement of breast thickness to calculate the volumes of these tissues. Women with newly diagnosed breast cancer (cases) identified on these mammography machines during the years 2000 to 2003 were compared with other women of the same age who did not have breast cancer (controls). RESULTS: Three hundred sixty-four cases and 656 controls were recruited, epidemiologic data were collected, screen-film mammograms were digitized and measured using both a computer-assisted thresholding method, and the new measure of the volume of density. After adjustment for other risk factors, the odds ratio for those in the 5th quintile compared with the 1st quintile was 1.98 (95% confidence interval, 1.3-3.1) for the volume measure and 1.86 (95% CI, 1.1-3.0) for the area measurement. After inclusion of the volume and area measures in a predictive model, the volume measure lost significance, whereas the area measure remained significant. CONCLUSIONS: Contrary to our expectations, measurement of the volume of breast tissue did not improve prediction of breast cancer risk.

Breast-tissue composition and other risk factors for breast cancer in young women: a cross-sectional study.

BACKGROUND: Mammographic density is a heritable quantitative trait and is a strong risk factor for breast cancer in middle-aged and older women. However, little is known about the development of mammographic density in early life. We used MRI to measure the water content of the breast, which provides a measurement of the fibro-glandular content of breast tissue with similar accuracy to mammography, but without the attendant exposure to radiation. METHODS: Between December, 2003, and December, 2007, we recruited 400 young women, aged 15-30 years, and their mothers. We used MRI scans to measure daughters' breast water and fat, and on the same day obtained blood for hormone assays in the follicular phase of the menstrual cycle for each young woman. Mothers underwent mammography (n=356), and a random sample (n=100) also consented to have a breast MRI scan. FINDINGS: In mothers, per cent water-as measured by MRI-was strongly correlated with per cent mammographic density (r=0.85). Per cent water in daughters (median 44.8%) was significantly higher than in mothers (median 27.8%; p<0.0001), and was independently inversely associated with both their age (p=0.04) and weight (p<0.0001), and positively associated with their height (p<0.0001) and their mothers' per cent mammographic density (p<0.0001). Serum growth hormone concentrations, adjusted for covariates, were positively associated with per cent breast water (p=0.001) in a subgroup of young women (n=280) who had not used oral contraceptives within 6 months. INTERPRETATION: Per cent breast water was greatest during the ages when women are most susceptible to breast carcinogens, and was associated with weight, height, and mother's breast-tissue characteristics, and with serum concentrations of growth hormone: a breast mitogen that also mediates postnatal somatic growth. Mammographic density in middle age might partly be the result of genetic factors that affect growth and development in early life. FUNDING: Canadian Breast Cancer Research Alliance.

Predictors of mammographic density: insights gained from a novel regression analysis of a twin study.

Understanding which factors influence mammographically dense and nondense areas is important because percent mammographic density adjusted for age is a strong, continuously distributed risk factor for breast cancer, especially when adjusted for weight or body mass index. Using computer-assisted methods, we measured mammographically dense areas for 571 monozygotic and 380 dizygotic Australian and North American twin pairs ages 40 to 70 years. We used a novel regression modeling approach in which each twin's measure of dense and nondense area was regressed against one or both of the twin's and co-twin's covariates. The nature of changes to regression estimates with the inclusion of the twin and/or co-twin's covariates can be evaluated for consistency with causal and/or other models. By causal, we mean that if it were possible to vary a covariate experimentally then the expected value of the outcome measure would change. After adjusting for the individual's weight, the co-twin associations with weight were attenuated, consistent with a causal effect of weight on mammographic measures, which in absolute log cm(2)/kg was thrice stronger for nondense than dense area. After adjusting for weight, later age at menarche, and greater height were associated with greater dense and lesser nondense areas in a manner inconsistent with causality. The associations of dense and nondense areas with parity are consistent with a causal effect and/or within-person confounding. The associations between mammographic density measures and height are consistent with shared early life environmental factors that predispose to both height and percent mammographic density and possibly breast cancer risk.

Is mammography adequate for screening women with inherited BRCA mutations and low breast density?

BACKGROUND: Several observational studies have shown that magnetic resonance imaging (MRI) is significantly more sensitive than mammography for screening women over age 25 at high risk for hereditary breast cancer; however, MRI is more costly and less specific than mammography. We sought to determine the extent to which the low sensitivity of mammography is due to greater breast density. METHODS: Breast density was evaluated for all patients on a high-risk screening study who were diagnosed with breast cancer between November 1997 and July 2006. Density was measured in two ways: qualitatively using the four categories characterized by the Breast Imaging Reporting and Data System and quantitatively using a computer-aided technique and classified as (a) 50% density. Comparison of sensitivity of mammography (and MRI) for each individual density category and after combining the highest two and lowest two density categories was done using Fisher's exact test. RESULTS: A total of 46 breast cancers [15 ductal carcinoma in situ (DCIS) and 31 invasive] were diagnosed in 45 women (42 with BRCA mutations). Mean age was 48.3 (range, 32-68) years. Overall, sensitivity of mammography versus MRI was 20% versus 87% for DCIS and 26% versus 90% for invasive cancer. There was a trend towards greater mammographic sensitivity for invasive cancer in women with fattier breasts compared with those with greater breast density (37-43% versus 8-12%; P = 0.1), but this trend was not seen for DCIS. CONCLUSION: It is necessary to add MRI to mammography for screening women with BRCA mutations even if their breast density is low.

The heritability of mammographically dense and nondense breast tissue.

BACKGROUND: Percent mammographic density (PMD) is a risk factor for breast cancer. Our previous twin study showed that the heritability of PMD was 63%. This study determined the heritabilities of the components of PMD, the areas of dense and nondense tissue in the mammogram. METHODS: We combined two twin studies comprising 571 monozygous and 380 dizygous twin pairs recruited from Australia and North America. Dense and nondense areas were measured using a computer-assisted method, and information about potential determinants was obtained by questionnaire. Under the assumptions of the classic twin model, we estimated the heritability of the log dense area and log nondense area and the genetic and environmental contributions to the covariance between the two traits, using maximum likelihood theory and the statistical package FISHER. RESULTS: After adjusting for measured determinants, for each of the log dense area and the log nondense area, the monozygous correlations were greater than the dizygous correlations. Heritability was estimated to be 65% (95% confidence interval, 60-70%) for dense area and 66% (95% confidence interval, 61-71%) for nondense area. The correlations (SE) between the two adjusted traits were -0.35 (0.023) in the same individual, -0.26 (0.026) across monozygous pairs, and -0.14 (0.034) across dizygous pairs. CONCLUSION: Genetic factors may play a large role in explaining variation in the mammographic areas of both dense and nondense tissue. About two thirds of the negative correlation between dense and nondense area is explained by the same genetic factors influencing both traits, but in opposite directions.

Heritability of mammographic density, a risk factor for breast cancer.

BACKGROUND: Women with extensive dense breast tissue visible on a mammogram have a risk of breast cancer that is 1.8 to 6.0 times that of women of the same age with little or no density. Menopausal status, weight, and parity account for 20 to 30 percent of the age-adjusted variation in the percentage of dense tissue. METHODS: We undertook two studies of twins to determine the proportion of the residual variation in the percentage of density measured by mammography that can be explained by unmeasured additive genetic factors (heritability). A total of 353 pairs of monozygotic twins and 246 pairs of dizygotic twins were recruited from the Australian Twin Registry, and 218 pairs of monozygotic twins and 134 pairs of dizygotic twins were recruited in Canada and the United States. Information on putative determinants of breast density was obtained by questionnaire. Mammograms were digitized, randomly ordered, and read by a blinded investigator. RESULTS: After adjustment for age and measured covariates, the correlation coefficient for the percentage of dense tissue was 0.61 for monozygotic pairs in Australia, 0.67 for monozygotic pairs in North America, 0.25 for dizygotic pairs in Australia, and 0.27 for dizygotic pairs in North America. According to the classic twin model, heritability (the proportion of variants attributable to additive genetic factors) accounted for 60 percent of the variation in density (95 percent confidence interval, 54 to 66) in Australian twins, 67 percent (95 percent confidence interval, 59 to 75) in North American twins, and 63 percent (95 percent confidence interval, 59 to 67) in all twins studied. CONCLUSIONS: These results show that the population variation in the percentage of dense tissue on mammography at a given age has high heritability. Because mammographic density is associated with an increased risk of breast cancer, finding the genes responsible for this phenotype could be important for understanding the causes of the disease.