A case-control study to assess the impact of mammographic density on breast cancer risk in women aged 40-49 at intermediate familial risk.

Mammographic density is a strong risk factor for breast cancer, but its potential application in risk management is not clear, partly due to uncertainties about its interaction with other breast cancer risk factors. We aimed to quantify the impact of mammographic density on breast cancer risk in women aged 40-49 at intermediate familial risk of breast cancer (average lifetime risk of 23%), in particular in premenopausal women, and to investigate its relationship with other breast cancer risk factors in this population. We present the results from a case-control study nested with the FH01 cohort study of 6,710 women mostly aged 40-49 at intermediate familial risk of breast cancer. One hundred and three cases of breast cancer were age-matched to one or two controls. Density was measured by semiautomated interactive thresholding. Absolute density, but not percent density, was a significant risk factor for breast cancer in this population after adjusting for area of nondense tissue (OR per 10 cm(2) = 1.07, 95% CI 1.00-1.15, p = 0.04). The effect was stronger in premenopausal women, who made up the majority of the study population. Absolute density remained a significant predictor of breast cancer risk after adjusting for age at menarche, age at first live birth, parity, past or present hormone replacement therapy, and the Tyrer-Cuzick 10-year relative risk estimate of breast cancer. Absolute density can improve breast cancer risk stratification and delineation of high-risk groups alongside the Tyrer-Cuzick 10-year relative risk estimate.

Assessing the usefulness of a novel MRI-based breast density estimation algorithm in a cohort of women at high genetic risk of breast cancer: the UK MARIBS study.

INTRODUCTION: Mammographic breast density is one of the strongest known risk factors for breast cancer. We present a novel technique for estimating breast density based on 3D T1-weighted Magnetic Resonance Imaging (MRI) and evaluate its performance, including for breast cancer risk prediction, relative to two standard mammographic density-estimation methods. METHODS: The analyses were based on MRI (n = 655) and mammography (n = 607) images obtained in the course of the UK multicentre magnetic resonance imaging breast screening (MARIBS) study of asymptomatic women aged 31 to 49 years who were at high genetic risk of breast cancer. The MRI percent and absolute dense volumes were estimated using our novel algorithm (MRIBview) while mammographic percent and absolute dense area were estimated using the Cumulus thresholding algorithm and also using a 21-point Visual Assessment scale for one medio-lateral oblique image per woman. We assessed the relationships of the MRI and mammographic measures to one another, to standard anthropometric and hormonal factors, to BRCA1/2 genetic status, and to breast cancer risk (60 cases) using linear and Poisson regression. RESULTS: MRI percent dense volume is well correlated with mammographic percent dense area (R = 0.76) but overall gives estimates 8.1 percentage points lower (P < 0.0001). Both show strong associations with established anthropometric and hormonal factors. Mammographic percent dense area, and to a lesser extent MRI percent dense volume were lower in BRCA1 carriers (P = 0.001, P = 0.010 respectively) but there was no association with BRCA2 carrier status. The study was underpowered to detect expected associations between percent density and breast cancer, but women with absolute MRI dense volume in the upper half of the distribution had double the risk of those in the lower half (P = 0.009). CONCLUSIONS: The MRIBview estimates of volumetric breast density are highly correlated with mammographic dense area but are not equivalent measures; the MRI absolute dense volume shows potential as a predictor of breast cancer risk that merits further investigation.

A pilot study of compositional analysis of the breast and estimation of breast mammographic density using three-dimensional T1-weighted magnetic resonance imaging.

PURPOSE: A method and computer tool to estimate percentage magnetic resonance (MR) imaging (MRI) breast density using three-dimensional T(1)-weighted MRI is introduced, and compared with mammographic percentage density [X-ray mammography (XRM)]. MATERIALS AND METHODS: Ethical approval and informed consent were obtained. A method to assess MRI breast density as percentage volume occupied by water-containing tissue on three-dimensional T(1)-weighted MR images is described and applied in a pilot study to 138 subjects who were imaged by both MRI and XRM during the Magnetic Resonance Imaging in Breast Screening study. For comparison, percentage mammographic density was measured from matching XRMs as a ratio of dense to total projection areas scored visually using a 21-point score and measured by applying a two-dimensional interactive program (CUMULUS). The MRI and XRM percent methods were compared, including assessment of left-right and interreader consistency. RESULTS: Percent MRI density correlated strongly (r = 0.78; P < 0.0001) with percent mammographic density estimated using Cumulus. Comparison with visual assessment also showed a strong correlation. The mammographic methods overestimate density compared with MRI volumetric assessment by a factor approaching 2. DISCUSSION: MRI provides direct three-dimensional measurement of the proportion of water-based tissue in the breast. It correlates well with visual and computerized percent mammographic density measurements. This method may have direct application in women having breast cancer screening by breast MRI and may aid in determination of risk.

Evaluating the effectiveness of using standard mammogram form to predict breast cancer risk: case-control study.

Breast density is a well-known breast cancer risk factor. Most current methods of measuring breast density are area based and subjective. Standard mammogram form (SMF) is a computer program using a volumetric approach to estimate the percent density in the breast. The aim of this study is to evaluate the current implementation of SMF as a predictor of breast cancer risk by comparing it with other widely used density measurement methods. The case-control study comprised 634 cancers with 1,880 age-matched controls combined from the Cambridge and Norwich Breast Screening Programs. Data collection involved assessing the films based both on Wolfe's parenchymal patterns and on visual estimation of percent density and then digitizing the films for computer analysis (interactive threshold technique and SMF). Logistic regression was used to produce odds ratios associated with increasing categories of breast density. Density measures from all four methods were strongly associated with breast cancer risk in the overall population. The stepwise rises in risk associated with increasing density as measured by the threshold method were 1.37 [95% confidence interval (95% CI), 1.03-1.82], 1.80 (95% CI, 1.36-2.37), and 2.45 (95% CI, 1.86-3.23). For each increasing quartile of SMF density measures, the risks were 1.11 (95% CI, 0.85-1.46), 1.31 (95% CI, 1.00-1.71), and 1.92 (95% CI, 1.47-2.51). After the model was adjusted for SMF results, the threshold readings maintained the same strong stepwise increase in density-risk relationship. On the contrary, once the model was adjusted for threshold readings, SMF outcome was no longer related to cancer risk. The available implementation of SMF is not a better cancer risk predictor compared with the thresholding method.

Mammographic density using two computer-based methods in an isoflavone trial.

OBJECTIVES: Mammographic density is a useful biomarker of breast cancer risk. Computer-based methods can provide continuous data suitable for analysis. This study aimed to compare a semi-automated computer-assisted method (Cumulus) and a fully automated volumetric computer method (standard mammogram form (SMF)) for assessing mammographic density using data from a previously conducted randomised placebo-controlled trial of an isoflavone supplement. METHODS: Mammograms were obtained from participants in the intervention study. A total of 177 women completed the study. Baseline and follow-up mammograms were digitised and density was estimated using Cumulus (read by two readers) and SMF. Left-right correlation, changes in density over time, and difference between intervention and control groups were evaluated. Changes of density over time, and changes between intervention group and control group were examined using paired t-test and Student's t-test, respectively. RESULTS: Inter-reader correlation coefficient by Cumulus was 0.90 for dense area, and 0.86 for percentage density. Left-right correlation of percent density was lower in SMF than in Cumulus. Among all women, percentage density by Cumulus decreased significantly over time, but no change was seen for SMF percentage density. The intervention group showed marginally significant greater reduction of percent density by Cumulus compared to controls (p=0.04), but the difference became weak after adjustment for baseline percent density (p=0.06). No other measurement demonstrated significant difference between intervention and control groups. CONCLUSIONS: This comparison suggests that slightly different conclusions could be drawn from different methods used to assess breast density. The development of a more robust fully automated method is awaited.

Does a short cessation of HRT decrease mammographic density?

BACKGROUND: Hormone replacement therapy (HRT) is known to increase breast density, thus decreasing the sensitivity of cancer screening by mammography. Some authors recommend short cessation of HRT before mammography, but evidence showing the effect of such short cessation is limited. The purpose of this study is to examine whether a short cessation of HRT changes mammographic density. METHODS: Forty-eight women taking HRT agreed to have mammograms taken before and after stopping HRT for 4 weeks. Mammographic density was measured by Wolfe's four-point classification, six-categorical visual scale and two different computer methods (interactive-thresholding and SMF). Density values of mammography before and after the cessation of HRT were compared using Wilcoxon signed-rank test for categorical variables and paired t-test for continuous variables. Changes in breast pain and tenderness during mammography, radiation dose, compression force, and breast thickness were also recorded. RESULTS: No significant changes in mammographic density were observed by either visual or computer methods. There were no significant changes in breast pain or in tenderness on mammograms before and after the month's cessation of HRT. Radiographic measurements were not significantly altered by the 4-week cessation of HRT. CONCLUSION: In this screening population, a 4-week cessation of HRT before mammograms did not significantly alter mammographic density.

Mammographic density and breast cancer risk in BRCA1 and BRCA2 mutation carriers.

High breast density as measured on mammograms is a strong risk factor for breast cancer in the general population, but its effect in carriers of germline BRCA1 and BRCA2 mutations is unclear. We obtained mammograms from 206 female carriers of BRCA1 or BRCA2 mutations, 96 of whom were subsequently diagnosed with breast cancer and 136 relatives of carriers who were themselves noncarriers. We compared the mammographic densities of affected carriers (cases) and unaffected carriers (controls), and of mutation carriers and noncarriers, using a computer-assisted method of measurement and visual assessment by two observers. Analyses were adjusted for age, parity, body mass index, menopausal status, and hormone replacement therapy use. There was no difference in the mean percent density between noncarriers and carriers. Among carriers, increasing mammographic density was associated with an increased risk of breast cancer (P(trend) = 0.024). The odds ratio (OR; 95% confidence interval) for breast cancer associated with a density of > or =50% was 2.29 (1.23-4.26; P = 0.009). The OR did not differ between BRCA1 and BRCA2 carriers or between premenopausal and postmenopausal carriers. The results suggest that the distribution of breast density in BRCA1 and BRCA2 carriers is similar to that in non-carriers. High breast density in carriers is associated with an increased risk of breast cancer, with the relative risk being similar to that observed in the general population. Use of mammographic density could improve individual risk prediction in carriers.