Using Volumetric Breast Density to Quantify the Potential Masking Risk of Mammographic Density.
OBJECTIVE
The purposes of this study were to compare BI-RADS density categories with quantitative volumetric breast density (VBD) for the reporting of mammographic sensitivity and to identify which patient factors are most predictive of a diagnosis of interval cancer of the breast versus screen-detected cancer.


METHODS
This retrospective study included screen-detected cancers (n = 652) and interval cancers (n = 119) identified between January 2009 and December 2012. Multivariate logistic regression analysis was used to determine which patient factors are predictive of a diagnosis of interval cancer. Sensitivity (screen-detected cancer / [screen-detected cancer + interval cancer]) was determined with the BI-RADS 4th edition density categories and an automated equivalent density grade obtained with a proprietary tool. Sensitivity changes within automated density grade categories were investigated by use of quantitative thresholds at the midpoints of each category.


RESULTS
In univariate analysis, age, menopausal status, and breast density were associated with a diagnosis of interval cancer. Of these risk factors, breast density was the only independent factor whether it was assessed by visual BI-RADS category (odds ratio, 3.54; 95% CI, 1.55-8.10), automated density grade (odds ratio, 4.68; 95% CI, 2.26-9.67), or VBD (odds ratio, 4.51; 95% CI, 1.92-10.61). Sensitivity decreased consistently across increasing automated density grade categories from fatty to extremely dense (95%, 89%, 83%, 65%) and less so for visual BI-RADS (82%, 90%, 84%, 66%). Further dichotomization with VBD cutoffs showed a striking linear relation between VBD and sensitivity (R2= 0.959).


CONCLUSIONS
In this study, breast density was the only risk factor significantly associated with a diagnosis of interval cancer versus screen-detected cancer. Quantitative VBD captures the potential masking risk of breast density more precisely than does the widely used visual BI-RADS density classification system.
1 Department of Breast Imaging, Elizabeth Wende Breast Care, 170 Sawgrass Dr, Rochester, NY 14620.
Stamatia
S
Destounis
2 Volpara Solutions, Ltd, Wellington, New Zealand.
Lisa
L
Johnston
2 Volpara Solutions, Ltd, Wellington, New Zealand.
Ralph
R
Highnam
1 Department of Breast Imaging, Elizabeth Wende Breast Care, 170 Sawgrass Dr, Rochester, NY 14620.
Andrea
A
Arieno
1 Department of Breast Imaging, Elizabeth Wende Breast Care, 170 Sawgrass Dr, Rochester, NY 14620.
Renee
R
Morgan
2 Volpara Solutions, Ltd, Wellington, New Zealand.
Ariane
A
Chan
D015502:Absorptiometry, Photon / Q000592:standards* / Q000706:statistics & numerical data; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology* / Q000473:pathology; D055088:Early Detection of Cancer / Q000592:standards* / Q000706:statistics & numerical data; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000592:standards* / Q000706:statistics & numerical data; D008327:Mammography / Q000592:standards* / Q000706:statistics & numerical data; D008875:Middle Aged; D009518:New York / Q000453:epidemiology; D017410:Practice Guidelines as Topic; D015995:Prevalence; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000592:standards; D012680:Sensitivity and Specificity; D047368:Tumor Burden; D014481:United States
breast cancer risk; breast density; interval cancer; mammography