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26 December 2019 Is there a safety-net effect with computer-aided detection?
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Computer-aided detection (CAD) systems are used to aid readers interpreting screening mammograms. An expert reader searches the image initially unaided and then once again with the aid of CAD, which prompts automatically detected suspicious regions. This could lead to a “safety-net” effect, where the initial unaided search of the image is adversely affected by the fact that it is preliminary to an additional search with CAD and may, therefore, be less thorough. To investigate the existence of such an effect, we created a visual search experiment for nonexpert observers mirroring breast screening with CAD. Each observer searched 100 images for microcalcification clusters within synthetic images in both prompted (CAD) and unprompted (no-CAD) conditions. Fifty-two participants were recruited for the study, 48 of whom had their eye movements tracked in real-time; the other 4 participants could not be accurately calibrated, so only behavioral data were collected. In the CAD condition, before prompts were displayed, image coverage was significantly lower than coverage in the no-CAD condition (t47  =  5.29, p  <  0.0001). Observer sensitivity was significantly greater for targets marked by CAD than the same targets in the no-CAD condition (t51  =  6.56, p  <  0.001). For targets not marked by CAD, there was no significant difference in observer sensitivity in the CAD condition compared with the same targets in the no-CAD condition (t51  =  0.54, p  =  0.59). These results suggest that the initial search may be influenced by the subsequent availability of CAD; if so, cross-sectional CAD efficacy studies should account for the effect when estimating benefit.

© 2019 Society of Photo-Optical Instrumentation Engineers (SPIE) 2329-4302/2019/$28.00 © 2019 SPIE
Ethan Du-Crow, Susan M. Astley, and Johan Hulleman "Is there a safety-net effect with computer-aided detection?," Journal of Medical Imaging 7(2), 022405 (26 December 2019).
Received: 18 September 2019; Accepted: 5 December 2019; Published: 26 December 2019

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