Mammography with Computer-aided Detection: Reproducibility Assessment—Initial Experience

PURPOSE: To examine the performance and reproducibility of a commercially available computer-aided detection (CAD) system with a set of mammograms obtained in 100 patients who had undergone biopsy after positive findings at mammography. MATERIALS AND METHODS: One hundred positive mammographic examinations (four views each), depicting 96 masses and 50 microcalcification clusters, were scanned and analyzed three times by the CAD system. Reproducibility of detection sensitivity and the individual CAD-generated cues in the three images were examined. Both abnormality- and region-based detection sensitivities were compared. RESULTS: Forty-eight (96.0%) of 50 microcalcification clusters were marked on all three images in the abnormality-based analysis. Of the remaining two clusters, one was marked in two images and one was marked in only one. The abnormality-based sensitivity for mass detection ranged from 66.7% (64 of 96) to 70.8% (68 of 96). The system generated identical patterns (including images with and those without cues) for all three images in 53.3% (213 of 400) of images. For true-positive cluster regions, 88.9% (80 of 90) were marked at the same location in all images. For true-positive mass regions, 69.5% (82 of 118) were marked at the same locations in all images. In false-positive detections, only 44.0% (81 of 184) of false-positive mass regions and 31.9% (38 of 119) of false-positive cluster regions were marked at the same locations on all three images. CONCLUSION: Reproducibility of marked regions generated by the CAD system is improved from that reported previously, largely as a result of the substantial reduction in the false-positive detection rates. Reproducibility of true-positive identification of masses remains an important issue that may have methodologic and clinical practice implications.