Breast density: comparison of chest CT with mammography.

PURPOSE: To (a) perform a pilot study comparing radiologists' reading of breast density at computed tomography (CT) of the chest with breast density readings from mammography performed in the same patient and (b) compare a subset of these with computer-derived measurements of breast density at CT. MATERIALS AND METHODS: The institutional review board waived informed consent for this HIPAA-compliant retrospective review of mammograms and chest CT scans from 206 women obtained within 1 year of each other. Two radiologists with expertise in interpreting mammographic and CT findings independently reviewed the mammograms and CT scans and classified each case into one of the four breast density types defined by the Breast Imaging Reporting and Data System of the American College of Radiology. Interreader agreements for the mammographic density types and CT density grades were determined by using the Cohen weighted κ statistic. The intrareader correlation coefficient was determined in a subset of CT images. In another subset of 40 cases, the agreement of the semiautomated computer-derived measurements of breast density with the consensus of the two radiologists was assessed. RESULTS: Interreader agreement was higher for the CT density grades than for the mammographic density types, with 0.79 (95% confidence interval [CI]: 0.73, 0.85) versus 0.62 (95% CI: 0.54, 0.70). The intrareader reliability of breast density grades on CT images was 0.88. The computer-derived breast density measurements agreed with those of the radiologists in 36 (90%) cases. When four cases were manually adjusted for the complex anatomy, there was agreement for all cases. CONCLUSION: Preliminary results suggest that on further validation, breast density readings at CT may provide important additional risk information on CT of the chest and that computer-derived measurements may be helpful in such assessment.

Digital Mammography and Screening for Coronary Artery Disease.

OBJECTIVES: This study sought to determine if breast arterial calcification (BAC) on digital mammography predicts coronary artery calcification (CAC). BACKGROUND: BAC is frequently noted but the quantitative relationships to CAC and risk factors are unknown. METHODS: A total of 292 women with digital mammography and nongated computed tomography was evaluated. BAC was quantitatively evaluated (0 to 12) and CAC was measured on computed tomography using a 0 to 12 score; they were correlated with each other and the Framingham Risk Score (FRS) and the 2013 Cholesterol Guidelines Pooled Cohort Equations (PCE). RESULTS: BAC was noted in 42.5% and was associated with increasing age (p < 0.0001), hypertension (p = 0.0007), and chronic kidney disease (p < 0.0001). The sensitivity, specificity, positive and negative predictive values, and accuracy of BAC >0 for CAC >0 were 63%, 76%, 70%, 69%, and 70%, respectively. All BAC variables were predictive of the CAC score (p < 0.0001). The multivariable odds ratio for CAC >0 was 3.2 for BAC 4 to 12, 2.0 for age, and 2.2 for hypertension. The agreements of FRS risk categories with CAC and BAC risk categories were 57% for CAC and 55% for BAC; the agreement was 47% for PCE risk categories for CAC and 54% by BAC. BAC >0 had area under the curve of 0.73 for identification of women with CAC >0, equivalent to both FRS (0.72) and PCE (0.71). BAC >0 increased the area under the curve curves for FRS (0.72 to 0.77; p = 0.15) and PCE (0.71 to 0.76; p = 0.11) for the identification of high-risk (4 to 12) CAC. With the inclusion of 33 women with established CAD, BAC >0 was significantly additive to both FRS (p = 0.02) and PCE (p = 0.04) for high-risk CAC. CONCLUSIONS: There is a strong quantitative association of BAC with CAC. BAC is superior to standard cardiovascular risk factors. BAC is equivalent to both the FRS and PCE for the identification of high-risk women and is additive when women with established CAD are included.