Mammograms represent data that can inform future risk of breast cancer. Data from two case-control study populations were analyzed. Population 1 included women (N  =  180 age matched case-control pairs) with mammograms acquired with one indirect x-ray conversion mammography unit. Population 2 included women (N  =  319 age matched case-control pairs) with mammograms acquired from 6 direct x-ray conversion units. The Fourier domain was decomposed into n concentric rings (radial spatial frequency bands). The power in each ring was summarized giving a set of measures. We investigated images in raw, for presentation (processed) and calibrated representations and made comparison with the percentage of breast density (BD) determined with the operator assisted Cumulus method. Breast cancer associations were evaluated with conditional logistic regression, adjusted for body mass index and ethnicity. Odds ratios (ORs), per standard deviation increase derived from the respective breast density distributions and 95% confidence intervals (CIs) were estimated. A measure from a lower radial frequency ring, corresponding 0.083–0.166 cycles mm−1 and BD had significant associations with risk in both populations. In Population 1, the Fourier measure produced significant associations in each representation: OR  =  1.76 (1.33, 2.32) for raw; OR  =  1.43 (1.09, 1.87) for processed; and OR  =  1.68 (1.26, 2.25) for calibrated. BD also provided significant associations in Population 1: OR  =  1.72 (1.27, 2.33). In Population 2, the Fourier measure produced significant associations for each representation as well: OR  =  1.47 (1.19, 1.80) for raw; OR  =  1.38 (1.15, 1.67) for processed; and OR  =  1.42 (1.15, 1.75) for calibrated. BD provided significant associations in Population 2: OR  =  1.43 (1.17, 1.76). Other coincident spectral regions were also predictive of case-control status. In sum, generalized breast density measures were significantly associated with breast cancer in both FFDM technologies.

Purpose: The authors are developing a system for calibrated breast density measurements using full field digital mammography (FFDM). Breast tissue equivalent (BTE) phantom images are used to establish baseline (BL) calibration curves at time zero. For a given FFDM unit, the full BL dataset is comprised of approximately 160 phantom images, acquired prior to calibrating prospective patient mammograms. BL curves are monitored serially to ensure they produce accurate calibration and require updating when calibration accuracy degrades beyond an acceptable tolerance, rather than acquiring full BL datasets repeatedly. BL updating is a special case of generalizing calibration datasets across FFDM units, referred to as cross-calibration. Serial monitoring, BL updating, and cross-calibration techniques were developed and evaluated. Methods: BL curves were established for three Hologic Selenia FFDM units at time zero. In addition, one set of serial phantom images, comprised of equal proportions of adipose and fibroglandular BTE materials (50/50 compositions) of a fixed height, was acquired biweekly and monitored with the cumulative sum (Cusum) technique. These 50/50 composition images were used to update the BL curves when the calibration accuracy degraded beyond a preset tolerance of ±4 standardized units. A second set of serial images, comprised of a wide-range of BTE compositions, was acquired biweekly to evaluate serial monitoring, BL updating, and cross-calibration techniques.

Purpose We are developing a calibration methodology for full‐field digital mammography ( FFDM ). Calibration compensates for image acquisition technique influences on the pixel representation, ideally producing improved inter‐image breast density estimates. This approach relies on establishing references with rigid breast tissue‐equivalent phantoms ( BTE s) and requires an accurate estimate of the compressed breast thickness because the system readout is nominal. There is also an attenuation mismatch between adipose breast tissue and the adipose BTE that was noted in our previous work. It is referred to as the “attenuation anomaly” and addressed in this report. The objectives are to evaluate methods to correct for the compressed breast thickness and compensate for the attenuation anomaly. Methods Thickness correction surfaces were established with a deformable phantom ( DP ) using both image and physical measurements for three direct x‐ray conversion FFDM units. The Cumulative Sum serial quality control procedure was established to ensure the thickness correction measurements were stable over time by imaging and calibrating DP s biweekly in lieu of physical measurements. The attenuation anomaly was addressed by evaluating adipose image regions coupled with an optimization technique to adjust the adipose calibration data. We compared calibration consistency across matched left and right cranial caudal ( CC ) mammographic views (n = 199) with and without corrections using Bland–Altman plots. These plots were complemented by comparing the right and left breast calibrated average (μ a ) and population distribution mean (m a ) with 95% confidence intervals and difference distribution variances with the F‐test for uncorrected and corrected data. Results Thickness correction surfaces were well approximated as tilted planes and were dependent upon compression force. A correction was developed for the attenuation anomaly. All paddles (large and small paddles for all units) exhibited similar tilt as a function of force. Without correction, m a = 0.92 (−1.77, 3.62) was not significantly different from zero with many negative μ a samples. The thickness correction produced a significant shift in the μ a distribution in the positive direction with m a = 13.99 (11.17, 16.80) and reduced the difference distribution variance significantly ( P < 0.0001). Applying both corrections in tandem gave m a = 22.83 (20.32, 25.34), representing another significant positive shift in comparison with the thickness correction in isolation. Thickness correctio...

Ag silver Az area under the receiver operating characteristic curve BI-RADS Breast Imaging Reporting and Data System (American College of Radiology) BMI body mass index BTE breast tissue equivalent CI(s) confidence interval(s) D unit DBT unit DBT digital breast tomosynthesis FAST automated self-adjusting Tilt Compression Paddle (Hologic, Inc., Bedford, MA) FFDM full-field digital mammography H unit 2D unit HRT hormone replacement therapy 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 caseÀcontrol 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.