Performance evaluation of an information-theoretic CAD scheme for the detection of mammographic architectural distortion

Previously, we presented an information-theoretic image retrieval scheme for computer-assisted detection (CAD) of masses in screening mammograms. The purpose of this study is to evaluate the performance of the CAD scheme in the detection of architectural distortion (AD) in mammograms of breasts with different parenchymal densities. The study was based on the Digital Database for Screening Mammography (DDSM). Initially, a databank of 1,337 mammographic regions with confirmed pathology was created. They were all 512x512 pixel regions of interest (ROIs) depicting a mixture of mass findings such as masses (599), asymmetric densities (30), and architectural distortion (52). In addition, there were 656 ROIs depicting normal parenchyma. The CAD scheme was applied as follows. When a suspicious mammographic region was presented to the CAD system for evaluation, the system searched the databank of mammographic regions with known pathology. A decision index was calculated based on the query's similarity with the stored cases. Mutual information was used as the similarity metric. ROC analysis was performed to determine how well the CAD scheme detected the architectural distortion cases. Based on a leave-one out sampling scheme, the overall ROC performance of the CAD system was 0.82±0.03 for the detection of AD in screening mammograms. Specifically, the CAD system achieved perfect performance in fatty breasts (Az=1.0), Az=0.89±0.03 in fibroglandular breasts, Az=0.78±0.05 in heterogeneous breasts, and Az=0.55±0.09 in dense breasts. The CAD scheme performed well in the detection of architectural distortion in screening mammograms. The performance of the CAD scheme deteriorated significantly as breast density increased.