Calibrated Breast Density Measurements

Abstract

Rationale and objectives: Mammographic density is an important risk factor for breast cancer, but translation to the clinic requires assurance that prior work based on mammography is applicable to current technologies. The purpose of this work is to evaluate whether a calibration methodology developed previously produces breast density metrics predictive of breast cancer risk when applied to a case-control study.

Materials and methods: A matched case control study (n = 319 pairs) was used to evaluate two calibrated measures of breast density. Two-dimensional mammograms were acquired from six Hologic mammography units: three conventional Selenia two-dimensional full-field digital mammography systems and three Dimensions digital breast tomosynthesis systems. We evaluated the capability of two calibrated breast density measures to quantify breast cancer risk: the mean (PG_m) and standard deviation (PG_sd) of the calibrated pixels. Matching variables included age, hormone replacement therapy usage/duration, screening history, and mammography unit. Calibrated measures were compared to the percentage of breast density (PD) determined with the operator-assisted Cumulus method. Conditional logistic regression was used to generate odds ratios (ORs) from continuous and quartile (Q) models with 95% confidence intervals. The area under the receiver operating characteristic curve (Az) was also used as a comparison metric. Both univariate models and models adjusted for body mass index and ethnicity were evaluated.

Results: In adjusted models, both PG_sd and PD were statistically significantly associated with breast cancer with similar Az of 0.61-0.62. The corresponding ORs and confidence intervals were also similar. For PG_sd, the OR was 1.34 (1.09, 1.66) for the continuous measure and 1.83 (1.11, 3.02), 2.19 (1.28, 3.73), and 2.20 (1.26, 3.85) for Q2-Q4. For PD, the OR was 1.43 (1.16, 1.76) for the continuous measure and 0.84 (0.52, 1.38), 1.96 (1.19, 3.23), and 2.27 (1.29, 4.00) for Q2-Q4. The results for PG_m were slightly attenuated and not statistically significant. The OR was 1.22 (0.99, 1.51) with Az = 0.60 for the continuous measure and 1.24 (0.78, 1.97), 0.98 (0.60, 1.61), and 1.26, (0.77, 2.07) for Q2-Q4 with Az = 0.60.

Conclusion: The calibrated PG_sd measure provided significant associations with breast cancer comparable to those given by PD. The calibrated PG_m performed slightly worse. These findings indicate that the calibration approach developed previously replicates under more general conditions.

Keywords: Calibration; breast cancer risk; breast density; mammography.

Figure 1.

PG_sd Illustration: The top row shows 4 mammograms in the processed (for presentation) representation used for viewing purposes. The bottom row shows the corresponding calibrated images after erosion. The ordering of the images corresponds with PG_sd quartiles (QRTs) with QRT 1 on the left and QRT 4 on the on the right. The PG_sd values from left to right are provided: 4.1 (PG_m = 20.3); 5.5(PG_m= 17.2); 8.0 (PG_m= 21.0); and 12.3 (PG_m= 52.10). For reference, the corresponding PD values are also provided: 31.4 (quartile 4); 13.2 (quartile 1); 35.0 (quartile 4); and 38.2 (quartile 4).

Figure 2.

Correlation Analyses: This shows the scatter plots for PD (vertical axis) with PG_m (left pane) and PG_sd (right pane) plotted with solid points. The respective regression lines (solid) are given by: PD = 0.47×PG_m + 12.0 (left); and PD = 1.39× PG_sd + 11.2 (right) with R = 0.67 and 0.60 respectively. The 95% confidence intervals for each slope are superposed on respective regression lines (dashed lines): (0.44, 0.50) PD vs. PG_m and (1.25, 1.54) for PD vs. PG_sd.