Related Experiment Video
Updated: Jul 21, 2026
Detection of Architectural Distortion in Prior Mammograms via Analysis of Oriented Patterns
Published on: August 30, 2013
Clinical performance of computer-assisted detection (CAD system in detecting carcinoma in breasts of different
1Department of Radiology, Queen Mary Hospital, Pokfulam, Hong Kong. hwtlee@netvigator.com
Objectives:
To determine the clinical performance of a computer-assisted detection (CAD) system in detecting carcinoma in breasts of different densities.
Materials And Methods:
A total of 264 sets of bilateral screening mammograms taken in craniocaudal and medial-lateral oblique projections during the year 1997 were divided into four groups according to the BI-RADS density classification: fatty (pattern 1), scattered fibroglandular (pattern 2), heterogeneously dense (pattern 3) and extremely dense (pattern 4). Each group contained about 60% normal and 40% biopsy-proven cancer cases. Of the malignant cases, there were a mixture of mammographic findings including focal masses (<2.5 cm), asymmetrical density, architectural distortion or microcalcifications. Films with artefacts and obvious masses>2.5 cm were not included. The chosen cases were then digitized and analysed by the CAD system. Sensitivity was calculated as detection of cancer by at least one marker in at least one view. Specificity was calculated as the number of false-positive marks per image on normal cases. Statistical tests of significance were performed by using contingency tables and Chi square test.
Results:
The CAD system detected 14 out of the total 15 cancer cases in totally fatty breasts with a sensitivity of 93.3% at a specificity of 1.3 false-positive marks per image. In breasts with scattered fibroglandular pattern, the sensitivity was 93.9% (31/33) and the specificity was 1.6 false-positive marks per image while in heterogeneously dense breasts, the sensitivity of the CAD system fell to 84.8% at a specificity of 1.6 false-positive marks per image. The sensitivity of the CAD system further dropped to 64.3% in markedly dense breasts while maintaining a specificity of 1.2 false-positive marks per image. The decrease in sensitivity in dense breast was found to be significant (p=0.046).
Conclusion:
The sensitivity of the CAD system deteriorated significantly as the density of the breast increased while the specificity of the system remained relatively constant.
