Abstract
Background: Although mammography remains the mainstay for breast cancer screening, it is an imperfect examination with a sensitivity of 75–92% for breast cancer. Computer-aided detection (CAD) has been developed to improve mammographic detection of breast cancer.
Purpose: To retrospectively estimate CAD sensitivity and false-positive rate with full-field digital mammograms (FFDMs).
Material and Methods: CAD was used to evaluate 151 cases of ductal carcinoma in situ (DCIS) (n=48) and invasive breast cancer (n=103) detected with FFDM. Retrospectively, CAD sensitivity was estimated based on breast density, mammographic presentation, histopathology type, and lesion size. CAD false-positive rate was estimated with screening FFDMs from 200 women.
Results: CAD detected 93% (141/151) of cancer cases: 97% (28/29) in fatty breasts, 94% (81/86) in breasts containing scattered fibroglandular densities, 90% (28/31) in heterogeneously dense breasts, and 80% (4/5) in extremely dense breasts. CAD detected 98% (54/55) of cancers manifesting as calcifications, 89% (74/83) as masses, and 100% (13/13) as mixed masses and calcifications. CAD detected 92% (73/79) of invasive ductal carcinomas, 89% (8/9) of invasive lobular carcinomas, 93% (14/15) of other invasive carcinomas, and 96% (46/48) of DCIS. CAD sensitivity for cancers 1–10 mm was 87% (47/54); 11–20 mm, 99% (70/71); 21–30 mm, 86% (12/14); and larger than 30 mm, 100% (12/12). The CAD false-positive rate was 2.5 marks per case.
Conclusion: CAD with FFDM showed a high sensitivity in identifying cancers manifesting as calcifications or masses. CAD sensitivity was maintained in small lesions (1–20 mm) and invasive lobular carcinomas, which have lower mammographic sensitivity.
Acknowledgment
This study was supported by the Fundación Marqués de Valdecilla – IFIMAV.
Declaration of interest: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.