Breast density measurements with ultrasound tomography: A comparison with film and digital mammography

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134902/1/mp2057.pd

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 features associated with interval breast cancers in screening programs

Abstract Introduction Percent mammographic density (PMD) is associated with an increased risk of interval breast cancer in screening programs, as are younger age, pre-menopausal status, lower body mass index and hormone therapy. These factors are also associated with variations in PMD. We have examined whether these variables influence the relative frequency of interval and screen-detected breast cancer, independently or through their associations with PMD. We also examined the association of tumor size with PMD and dense and non-dense areas in screen-detected and interval breast cancers. Methods We used data from three case-control studies nested in screened populations. Interval breast cancer was defined as invasive breast cancer detected within 12 months of a negative mammogram. We used a computer-assisted method of measuring the dense and total areas of breast tissue in the first (baseline) mammogram taken at entry to screening programs and calculated the non-dense area and PMD. We compared these mammographic features, and other risk factors at baseline, in women with screen-detected (n?=?718) and interval breast cancer (n?=?125). Results In multi-variable analysis, the baseline characteristics of younger age, greater dense area and smaller non-dense mammographic area were significantly associated with interval breast cancer compared to screen-detected breast cancer. Compared to screen-detected breast cancers, interval cancers had a larger maximum tumor diameter within each mammographic measure. Conclusions Age and the dense and non-dense areas in the baseline mammogram were independently associated with interval breast cancers in screening programs. These results suggest that decreased detection of cancers caused by the area of dense tissue, and more rapid growth associated with a smaller non-dense area, may both contribute to risk of interval breast cancer. Tailoring screening to individual mammographic characteristics at baseline may reduce the number of interval cancers

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

Risk factors by case-control status.

a<p><i>P</i> is a p-value from a two-sided two-sample t-test for symmetrically distributed continuous variables or Wilcoxon rank-sum test for non-symmetrically distributed continuous variables and chi-square test for categorical variables.</p>b<p>Hormone replacement therapy.</p>c<p>First degree relatives with breast cancer.</p

Estimation of breast stiffness.

<p>A. Estimation of radius (R1) from measure of breast volume B. Estimation of radius (R2) from measure of compressed breast area C. Calculation of breast stiffness from R1, R2 and compression force.</p

Histograms of the distributions of the stiffness measures in cases and controls.

<p>The stiffness measures were natural logarithm transformed. In each plot, the thin vertical line represents the mean of the distribution.</p

Breast measurements by case-control status.

a<p><i>P</i> is a p-value from a two-sided two-sample t-test, based on transformed variables. Area breast measurements were square root transformed and volume breast measurements were cubic root transformed for the analysis. Mean and standard deviation were calculated using untransformed data.</p>b<p>14 subjects with compression force under minimum detectable threshold was imputed as half of the minimum detectable value. Mean and standard deviation were calculated based on imputed variable.</p>c<p>P-value from Wilcoxon rank-sum test.</p

Least square means of stiffness in cases and controls, adjusted for risk factors.

<p>Risk factors include: age at mammogram (linear and quadratic terms), age at birth of first child, weight (kg), height (cm), menopausal status (pre/post) and parity (parous/nonparous). Stiffness (N/cm) was natural logarithm transformed in the analysis. The least square means shown are back transformed to the original scale. Bars show 95% confidence interval. P is the p-value for the significance of case control difference. When adjusted for percent dense area, square root transformation was used and model includes linear and quadratic terms. When adjusted for percent dense volume, cubic root transformation was used and model includes linear and quadratic terms.</p