Effects of lesion conspicuity on visual search in mammogram reading.

RATIONALE AND OBJECTIVES: The goal of mammography screening is to detect breast cancer at early stages, but because of the complexity of the breast parenchyma and the variability of signs of the disease, many cancers go unreported when initially visible on the mammogram. We compared the visual search strategy used by experienced mammographers in a case set where they examined both the mammogram in which a malignant mass was discovered at screening mammography and the most recent prior mammogram. MATERIALS AND METHODS: Four experienced mammographers participated in this experiment. They read a case set of 20 two-view mammograms, of which 15 contained a malignant mass and 5 were lesion-free, in two trials. For each of the cancer cases, two versions were shown to the observers: the one in which the cancer was reported in the clinical practice, called the "current" mammograms, and the most recent prior. Each trial had a balanced mix of current and prior mammograms. In addition, the same set of lesion-free cases was shown to the observers in both trials. The eye movements of the observers were tracked, and visual search parameters such as time to hit the location of the malignant mass, dwell, and mean pupil size in the location of the cancer were collected. Statistical analyses were used to determine whether there were differences between the current and prior mammograms. RESULTS: A total of 66% of the malignant masses in the current mammograms and 57% in the priors attracted some amount of visual attention. From these, 71% yielded a report on the current mammograms, but only 40% on the priors. In the cases where the observer saw the malignant mass, they did so within 2 seconds of image display, regardless of whether the mammogram was current or prior. CONCLUSION: Most unreported malignant masses attracted some amount of visual attention, but it was in the processing of the information extracted in the location of the lesion that most errors occurred. In our experiment, approximately 70% of the total time used by the observers for visual scan of the cases was spent gathering information to corroborate the hypothesis already formed by the radiologist.

Computer-aided detection performance in mammographic examination of masses: assessment.

PURPOSE: To compare performance of two computer-aided detection (CAD) systems and an in-house scheme applied to five groups of sequentially acquired screening mammograms. MATERIALS AND METHODS: Two hundred nineteen film-based mammographic examinations, classified into five groups, were included in this study. Group 1 included 58 examinations in which verified malignant masses were detected during screening; group 2, 39 in which all available latest examinations were performed prior to diagnosis of these malignant masses (subset of 39 women from group 1); group 3, 22 in which findings were interpreted as negative but were verified as cancer within 1 year from the negative interpretation (missed cancers); group 4, 50 in which findings were negative and patients were not recalled for additional procedures; and group 5, 50 in which patients were recalled for additional procedures and findings were negative for cancer. In all examinations, images were processed with two Food and Drug Administration-approved commercially available CAD systems and an in-house scheme. Performance levels in terms of true-positive detection rates and number of false-positive identifications per image and per examination were compared. RESULTS: Mass detection rates in positive examinations (group 1) were 67%-72%. Detection rates among three systems were not significantly different (P > .05). In 50 negative screening examinations (group 4), false-positive rates ranged from 1.08 to 1.68 per four-view examination. Performance level differences among systems were significant for false-positive rates (P = .008). Performance of all systems was at levels lower than publicly suggested in some retrospective studies. False-positive CAD cueing rates were significantly higher for negative examinations in which patients were recalled (group 5) than they were for those in which patients were not recalled (group 4) (P < or = .002). CONCLUSION: Performance of CAD systems for mass detection at mammography varies significantly, depending on examination and system used. Actual performance of all systems in clinical environment can be improved.