Impact of breast density on computer-aided detection for breast cancer.
OBJECTIVE
Our aim was to determine whether breast density affects the performance of a computer-aided detection (CAD) system for the detection of breast cancer.


METHODS
Nine hundred six sequential mammographically detected breast cancers and 147 normal screening mammograms from 18 facilities were classified by mammographic density. BI-RADS 1 and 2 density cases were classified as nondense breasts; BI-RADS 3 and 4 density cases were classified as dense breasts. Cancers were classified as either masses or microcalcifications. All mammograms from the cancer and normal cases were evaluated by the CAD system. The sensitivity and false-positive rates from CAD in dense and nondense breasts were evaluated and compared.


RESULTS
Overall, 809 (89%) of 906 cancer cases were detected by CAD; 455/505 (90%) cancers in nondense breasts and 354/401 (88%) cancers in dense breasts were detected. CAD sensitivity was not affected by breast density (p=0.38). Across both breast density categories, 280/296 (95%) microcalcification cases and 529/610 (87%) mass cases were detected. One hundred fourteen (93%) of the 122 microcalcifications in nondense breasts and 166 (95%) of 174 microcalcifications in dense breasts were detected, showing that CAD sensitivity to microcalcifications is not dependent on breast density (p=0.46). Three hundred forty-one (89%) of 383 masses in nondense breasts, and 188 (83%) of 227 masses in dense breasts were detected-that is, CAD sensitivity to masses is affected by breast density (p=0.03). There were more false-positive marks on dense versus nondense mammograms (p=0.04).


CONCLUSIONS
Breast density does not impact overall CAD detection of breast cancer. There is no statistically significant difference in breast cancer detection in dense and nondense breasts. However, the detection of breast cancer manifesting as masses is impacted by breast density. The false-positive rate is lower in nondense versus dense breasts. CAD may be particularly advantageous in patients with dense breasts, in which mammography is most challenging.
Brem
Rachel F
RF
Department of Radiology, The George Washington University, 2150 Pennsylvania Ave. NW, Washington, DC 21117, USA. rbrem@mfa.gwu.edu
Hoffmeister
Jeffrey W
JW
Rapelyea
Jocelyn A
JA
Zisman
Gilat
G
Mohtashemi
Kevin
K
Jindal
Guarav
G
Disimio
Martin P
MP
Rogers
Steven K
SK
D000328:Adult; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D005189:False Positive Reactions; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods; D008403:Mass Screening / Q000379:methods / Q000592:standards*; D008875:Middle Aged; D011857:Radiographic Image Interpretation, Computer-Assisted; D012680:Sensitivity and Specificity