[Impact of breast density on computer-aided detection (CAD) of breast cancer].

Objective To evaluate the impact of breast density on computer-aided detection （CAD） for breast cancer and the CAD false-positive rate of normal controls. Methods Two hundred and seventy-one histologically proven breast malignant lesions （ from Feb. 2008 to Dec. 2009 ） and 238 randomly selected normal cases were classified by mammographic density according to the American College of Radiology breast imaging reporting and data system （BI-RADS）. Mammograms of BI-RADS I or BI-RADS 2 density were categorized as non-dense breasts, and those of BI-RADS 3 or BI-RADS 4 density were categorized as dense breasts. Full-field digital mammography （ GEMS Senographe） were performed in all patients and controls with craniocaudal （CC） and mediolateral oblique （MLO） views. Then the image data were transferred to review workstation （SenoAdvantage） , and the lesions were marked by Second Look Digital CAD system （version 7.2, iCAD ）. The differences of sensitivity and false-positive rate between dense and non-dense breasts were compared. Results Overall, the sensitivity of CAD in detection of cancers was 84.1% （228/271） , there was a statistically significant difference in CAD of cancers in dense versus non-dense breasts （P = 0. 015 ）. The sensitivity of CAD in detection of mass cancers was 76.5% （186/243）, in detection of calcification cancers was 79.1% （125/158）, there was no statistically significant difference in CAD performance for the detection of mass cancers versus calcification cancers （ P = 0.547 ）. There was a significant difference in the CAD performance for the detection of mass cancer cases in non-dense versus dense breasts （P = 0. 001 ） , but no significant difference in the CAD for the detection of calcification cancers in non-dense versus dense breasts （P = 0. 216）. In the controls, the distribution of mass false-positive marks did not differ significantly between non-dense and dense breast tissue eases （ P = 0. 207） ,but the distribution of calcification false-positive marks differed signifieantly between non-dense and dense breast tissue cases （P = 0. 001 ）. There was a statistically significant difference of false-positive marks in non-dense versus dense breasts （P = 0. 043）. Conclusions The sensitivity of CAD in the detection of breast cancers is impacted by breast density. There is a statistically significant difference in the CAD performance for the detection of cancer cases in non-dense versus dense breasts. The false-positive rate of CAD is lower in dense versus non-dense breasts. It appears difficult for CAD in the early detection of breast cancer in the absence of microcalcifications, particularly in dense breasts. Key words: Mammography;  Numerical analysis, computer-assisted;  Breast neoplasms