Abstract
PURPOSE: We aim to investigate the performance of dedicated breast computed tomography (CT) for the detection of soft-tissue lesions and compare it to the detection of microcalcification clusters using cascaded systems analysis, with the intent of identifying which lesion type should be used for system optimization. APPROACH: Signal and noise were propagated through the imaging chain using a cascaded systems model to obtain the modulation transfer function and noise power spectrum. Two imaging tasks were considered: a soft-tissue mass lesion modeled as a disk of 4 mm diameter and a cluster of microcalcifications modeled as calcium carbonate spheres of 220 μm diameter. Detectability indices using three numerical observer models were obtained for various scintillator thicknesses and acquisition conditions at a fixed 4.5 mGy mean glandular dose. RESULTS: Detectability index trends are reversed between soft-tissue lesion and microcalcification cluster for the range of X-ray tube voltages and filtrations studied, indicating a potential need for compromise. However, for each of the 150 combinations studied (6 kV settings × 5 Cu filter thicknesses × 5 CsI:Tl scintillator thicknesses) and for each of the three numerical observer models, the detectability index for soft-tissue lesions always exceeded the microcalcification cluster. CONCLUSION: When the lesion type is unknown, such as during breast cancer screening, it is more appropriate to optimize the system parameters for the task of detecting a microcalcification cluster, as the detectability index for the soft-tissue lesion exceeded that for the microcalcification cluster for all conditions investigated.