Evans et al. (2016) showed that radiologists can classify the mammograms as normal or abnormal at above-chance levels after a 250-ms exposure. Our study documents a similar gist signal in digital breast tomosynthesis (DBT) images. DBT is a relatively new technology that creates a three-dimensional image set of slices through the volume of the breast. It improves performance over two-dimensional (2-D) mammography but at a cost in reading time. In the experiment presented, radiologists (N = 16) viewed “movies” of DBT images from single breasts for an average of 1.5 s per case. Observers then marked the most likely lesion position on a blank outline and rated each case on a six-point scale from (1) certainly normal to (6) certainly recall. Results show that radiologists can discriminate normal from abnormal DBT cases at above-chance levels as in 2-D mammography. Ability was correlated with experience reading DBT. Observers performed at above-chance levels, even on those images where they could not localize the target, suggesting that this is a global signal that could prove valuable in the clinic.
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