Computer-aided detection for mammography: improved algorithm performance with operator determined points characterized by new metrics

Abstract

Recent prospective studies have suggested that user's confidence in computer-aided detection (CAD) marks and their tolerance of false positive (FP) marks play a role in the benefit gained from a CAD device. In this paper, we propose to (1) introduce new metrics to improve the characterization of the latest generation of CAD algorithms and (2) to describe the algorithm performance tradeoffs with user adjustable operating points. The performance of the CAD algorithm (V8.0, R2 Technology, Sunnyvale, CA) with user adjustable operating points was assessed on a multi-institutional database of 832 consecutive, biopsy-proven cancers detected by screening mammography and 345 clinically confirmed normal (four view) cases. The standard measurements of CAD performance were made—case sensitivity for microcalcifications and masses, and false positive (FP) marker rate on normal cases. In addition, new measurements of case specificity (the percentage of normal cases with no CAD marks) and two-view sensitivity (the percentage of cancer cases with a cancer visible ( n=628) and marked on both views) were used. It is likely that the case specificity measure reflects the impact of the CAD algorithm on the workflow of the radiologist. Further, a high value for the two-view sensitivity is likely to increase the radiologist's confidence in the CAD tool. This new CAD system allows the user to choose an operating point to best fit their clinical requirements.