Spatial dependency of lesion detectability in digital breast tomosynthesis.

X-ray imaging results in inhomogeneous irradiation of the detector and distortion of structures in the periphery of the image; yet the spatial dependency of tomosynthesis image-quality metrics has not been extensively investigated. In this study, we use virtual clinical trials to quantify the spatial dependency of lesion detectability in our lab's next-generation tomosynthesis (NGT) system. Two geometries were analyzed: a conventional geometry with mediolateral source motion, and a NGT geometry with T-shaped motion. Breast parenchymal texture was simulated using an open-source library with Perlin noise using 400 random seeds and three breast densities. Spherical mass lesions were inserted in the central slice of the phantoms using the voxel additive method. Image acquisition was simulated using in-house ray-tracing software and simple backprojection was performed using commercial reconstruction software. Lesion detectability with Channelized Hotelling Observers (CHOs) was analyzed using receiver operating characteristic curves to measure the detectability index (d') at 154 unique locations for the lesions. We also divided images into three non-overlapping regions (differing in terms of distance from the chest wall). At the 0.05 level of significance, there was a statistically significant difference between the geometries in terms of d' in one of the three regions, with the T geometry offering superior detectability. Examining all 154 lesion locations, the T geometry was found to offer lower spread (standard deviation) in d' values throughout the image area, and superior d' at 83 of 154 locations (53.9%). In summary, the T geometry enables superior lesion detection and mitigates anisotropies.