Purpose

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.

Methods

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_H) and NPWE (PC_NPWE) experiments was calculated and the correlation between the two was analyzed using a mixed-effect regression model. Correlation results including the goodness of fit (r²) of PC_H and PC_NPWE for all different parameters investigated were evaluated to determine whether NPWE MO can be used to predict human observer performance.

Results

PC_H and PC_NPWE 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, r² between PC_H with PC_NPWE was 0.81. For system B, r² was 0.93. In case of the 0.25 mm discs, r² in system A was 0.79 and for system B, r² 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 r² 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_H(pred) by the MO and the PC_H for all different conditions.

Conclusions

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.