Lesion detection in digital breast tomosynthesis: human reader experiments indicate no benefit from the integration of information from multiple planes

Abstract

In digital breast tomosynthesis (DBT), radiologists need to review a stack of 20 to 80 tomosynthesis images, depending upon breast size. This causes a significant increase in reading time. However, it is currently unknown whether there is a perceptual benefit to viewing a mass in the 3D tomosynthesis volume. To answer this question, this study investigated whether adjacent lesion-containing planes provide additional information that aids lesion detection for DBT-like and breast CT-like (bCT) images.Method: Human reader detection performance was determined for low-contrast targets shown in a single tomosynthesis image at the center of the target (2D) or shown in the entire tomosynthesis image stack (3D). Using simulations, targets embedded in simulated breast backgrounds, and images were generated using a DBT-like (50 deg angular range) and a bCT-like (180 deg angular range) imaging geometry. Experiments were conducted with spherical and capsule-shaped targets. Eleven readers reviewed 1600 images in two-alternative forced-choice experiments. The area under the receiver operating characteristic curve (AUC) and reading time were computed for the 2D and 3D reading modes for the DBT and bCT imaging geometries and for both target shapes.Results: Spherical lesion detection was higher in 2D mode than in 3D, for both DBT-and bCT-like images (DBT: AUC 2D ¼ 0.790, AUC 3D ¼ 0.735, P ¼ 0.03; bCT: AUC 2D ¼ 0.869, AUC 3D ¼ 0.716, P < 0.05), but equivalent for capsule-shaped signals (DBT: AUC 2D ¼ 0.891, AUC 3D ¼ 0.915, P ¼ 0.19; bCT: AUC 2D ¼ 0.854, AUC 3D ¼ 0.847, P ¼ 0.88). Average reading time was up to 134% higher for 3D viewing (P < 0.05).Conclusions: For the detection of low-contrast lesions, there is no inherent visual perception benefit to reviewing the entire DBT or bCT stack. The findings of this study could have implications for the development of 2D synthetic mammograms: a single synthesized 2D image designed to include all lesions present in the volume might allow readers to maintain detection performance at a significantly reduced reading time.