A model observer study using acquired mammographic images of an anthropomorphic breast phantom

To study the feasibility of a task-based framework composed of an anthropomorphic breast phantom and mathematical model observers (MOs) for the evaluation of system-processed mammographic images. A prototype anthropomorphic breast phantom with inserted gold discs of 0.1 mm and 0.25 mm diameter was imaged with two digital mammography systems (system A and B) at four different dose levels. From the acquired processed and unprocessed images, signal-present and signal-absent regions of interest (ROIs) were extracted. The ROIs were evaluated by a non-pre-whitening MO with eye filter (NPWE) and by three human observers in a two-alternative forced-choice experiment. We compared the human and the MO performance on a simple detection task of the calcification-like discs in ROIs with and without postprocessing. Proportion of correct responses of the human (PC ) and NPWE (PC ) experiments was calculated and the correlation between the two was analyzed using a mixed-effect regression model. Correlation results including the goodness of fit (r ) of PC and PC for all different parameters investigated were evaluated to determine whether NPWE MO can be used to predict human observer performance. PC and PC increased with dose for all conditions investigated (signal size, processing status, and different system). In case of the 0.1 mm discs, for system A, r between PC with PC was 0.81. For system B, r was 0.93. In case of the 0.25 mm discs, r in system A was 0.79 and for system B, r was 0.82. For the combined parameters investigated, and after excluding the 0.1 mm discs on system A because the results were influenced by aliasing, the overall r was 0.81. Image processing did not affect the detectability of calcification-like signals. No significant difference (P > 0.05) was found between the predicted PC by the MO and the PC for all different conditions. The framework seems promising to be used in objective image quality assessment. It was found to be relatively robust for the range of parameters investigated. However, further optimization of the anthropomorphic breast phantom and investigation of other MOs for a broader range of image quality assessment tasks is needed.