The purpose of this study is comparing the detection performance in 2D full field digital mammography (FFDM) and digital breast tomosynthesis (DBT) using a structured phantom with inserted target objects. The phantom consists of a semi-cylindrical PMMA container, filled with water and PMMA spheres of different diameters. Microcalcifications and 3D printed masses (spiculated and non-spiculated) were inserted. The phantom was imaged ten times in both modes of five systems, using automatic exposure control (AEC) and at half and double the AEC dose. Five readers evaluated target detectability in a four-alternative forced-choice study. The percentage of correct responses (PC) was assessed based on 10 trials of each reader for each object type, size, imaging modality and dose level. Additionally, detection threshold diameters at 62.5 PC were assessed via non-linear regression fitting of the psychometric curve. Evaluation of target detection in FFDM showed that spiculated masses were better detected compared to non-spiculated masses. In DBT, detection of both mass types increased significantly (p=0.0001) compared to FFDM. Microcalcification detection thresholds ranged between 110 and 118 μm and were similar for the five systems in FFDM while larger variations (106-158 μm) were found in DBT. Mass detection was independent of dose in FFDM while weak dependence was seen for DBT. Microcalcification detection increased with increasing dose for both modalities. The phantom was able to show detectability differences between FFDM and DBT mode for five commercial systems in line with the findings from clinical trials. We suggest to use the phantom for task-based assessment methods for acceptance and commissioning testing of DBT systems.
Digital breast tomosynthesis (DBT) is a relatively new 3D mammography technique that promises better detection of low contrast masses than conventional 2D mammography. The parameter space for DBT is large however and finding an optimal balance between dose and image quality remains challenging. Given the large number of conditions and images required in optimization studies, the use of human observers (HO) is time consuming and certainly not feasible for the tuning of all degrees of freedom. Our goal was to develop a model observer (MO) that could predict human detectability for clinically relevant details embedded within a newly developed structured phantom for DBT applications. DBT series were acquired on GE SenoClaire 3D, Giotto Class, Fujifilm AMULET Innovality and Philips MicroDose systems at different dose levels, Siemens Inspiration DBT acquisitions were reconstructed with different algorithms, while a larger set of DBT series was acquired on Hologic Dimensions system for first reproducibility testing. A channelized Hotelling observer (CHO) with Gabor channels was developed The parameters of the Gabor channels were tuned on all systems at standard scanning conditions and the candidate that produced the best fit for all systems was chosen. After tuning, the MO was applied to all systems and conditions. Linear regression lines between MO and HO scores were calculated, giving correlation coefficients between 0.87 and 0.99 for all tested conditions.