Anoma Gunasekara

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. (Cancer Epidemiol Biomarkers Prev 2009;18(6):1754–62)

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. (Cancer Epidemiol Biomarkers Prev 2006;15(4):612–7)

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 2.2β) 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; Pt <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 2.2β method in digitized images. Cancer Epidemiol Biomarkers Prev; 19(2); 418–28

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.

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 twins measure of dense and nondense area was regressed against one or both of the twins and co-twins covariates. The nature of changes to regression estimates with the inclusion of the twin and/or co-twins 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 individuals weight, the co-twin associations with weight were attenuated, consistent with a causal effect of weight on mammographic measures, which in absolute log cm2/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. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3474–81)

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) ≤10%, (b) 11% to 25%, (c) 26% to 50%, and (d) >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 Fishers 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. (Cancer Epidemiol Biomarkers Prev 2008;17(3):706–11)

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.

Abstract B12: The effect of physical activity and body size on mammographic density in high-risk, BRCA mutation-negative women

Purpose: Mammographic density (MD) reflects the proportion of dense tissue in relation to non-dense tissue in the breast and is the strongest biological marker of breast cancer risk. MD is known to be higher among women with a family history compared to women in the general population. We have previously demonstrated that women with a strong family history of breast cancer but no BRCA mutation face an elevated lifetime risk of breast cancer estimated at 40% compared to 11% in the general population. Various lifestyle factors, such as physical activity and body mass index (BMI), have been shown to modify MD in the general population. It is of interest to determine if such an association exists among high-risk women. Objective: To evaluate the relationship between physical activity, BMI and MD in high-risk women. Methods: This study included 100 women enrolled in an on-going prospective study of high-risk women with a strong family history of breast cancer (two first-degree relatives with breast cancer under age 50 or three cases at any age) and no identified BRCA mutations in their families. Current physical activity levels and BMI were collected using self-reported questionnaires. Physical activity was defined as moderate to vigorous physical activity (MVPA). Two dichotomous variables were created to define high vs. low MVPA levels: 1) based on the Canadian Society for Exercise Physiology guideline of 2.5 hours of MVPA per week and 2) the 75th percentile of MVPA in the sample (3.5 hours per week). A BMI of 25 or more was defined as high using the World Health Organization criteria of overweight. Mammograms were assigned a percentage of density (0 - 100%) using a computer-assisted method (Cumulus 6). Multivariate linear regression modelling was used to evaluate the relationships between both MVPA and BMI with MD while adjusting for age, menopausal status, and parity. BMI models also adjusted for MVPA (continuous) and MVPA models adjusted for BMI (continuous). Results: Among all women, those with a high BMI had significantly lower mean percent density compared to women with a low BMI (13% vs. 23%; P = 0.01). This association was stronger for premenopausal (27% vs. 37%; P = 0.06) vs. postmenopausal (12% vs. 20%; P = 0.10) women. Women who engaged in MVPA for 2.5 hours per week or more had significantly greater mean percent density compared to women who were less physically active (29% vs. 22%; P = 0.04). This relationship did not vary by menopausal status (P ≥ 0.15). Based on the 75th percentile of MVPA, women with high MVPA levels had significantly greater mean percent density compared to women with low MVPA levels (31% vs. 22%; P = 0.02). This relationship was significant for postmenopausal (26% vs. 13%; P = 0.04) but not premenopausal (31% vs. 25%; P = 0.27) women. Conclusion: In this cohort of high-risk women, high BMI was associated with lower MD that was suggestively stronger for premenopausal women. Although preliminary, these findings suggest a possible mechanism by which a lifestyle factor may influence MD, and possibly breast cancer risk, in high-risk women. Further evaluation with a larger sample size is needed to elucidate the relationships between physical activity, as well as other modifiable factors, and MD in this cohort of women. This study adds to the growing evidence supporting the inclusion of MD into breast cancer risk prediction models, in order to improve individualized treatments and prevention strategies for women at an increased risk for disease. Citation Format: Olivia M. Moran, Dina Nikitina, Anoma Gunasekara, Martin J. Yaffe, Kelly A. Metcalfe, Steven A. Narod, Joanne Kotsopoulos. The effect of physical activity and body size on mammographic density in high-risk, BRCA mutation-negative women. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr B12.

Diffuse Optical Spectroscopy and Tomography for Monitoring Chemotherapy Efficacy in Locally Advanced Breast Cancer

Tomographic diffuse optical spectroscopy parameters of Hb, HbO2, %water and scattering power can be used as an early detector of final pathologic tumour response in women treated with neoadjuvant therapy for locally advanced breast cancer.

Abstract CN13-02: Breast tissue composition and risk of breast cancer

CN13-02 Background Susceptibility to breast carcinogens is greatest before the age of 20 years. We have used magnetic resonance (MR) to measure the water content of the breast in young women, and have identified factors associated with variations in breast water. Breast water, like mammographic density, reflects fibro-glandular breast tissue, which is strongly associated with breast cancer risk in middle aged and older women. Methods We recruited 400 young women aged 15-30 years and their mothers, measured breast water and fat in daughters using (MR), and obtained anthropometric and other data. Mothers provided mammograms (n=365) and a random sample (n=100) also had breast MR. Results Percent water by MR in daughters (median=44.8%) was greater than in mothers (median=27.8%) (P Conclusions Percent breast water was greatest at ages when susceptibility to breast carcinogens is also greatest. The distribution of breast water according to age was consistent with a model in which mammographic density in mid-life is in part the result of genetic influences and growth and development in early life that determine initial breast tissue composition. Citation Information: Cancer Prev Res 2008;1(7 Suppl):CN13-02.