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Is there a safety-net effect with computer-aided detection (CAD)?
Author(s): Ethan Du-Crow; Lucy Warren; Susan M. Astley; Johan Hulleman
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Paper Abstract

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 non-expert observers mirroring breast screening with CAD. Each observer searched 100 images for microcalcification clusters within synthetic images in both prompted and unprompted (no-CAD) conditions. Fifty-two participants were recruited for the study, 48 of whom had their eye movements tracked in real-time; four participants could not be accurately calibrated so only behavioural data was collected. In the CAD condition, before prompts were displayed, image coverage was significantly lower than coverage in the no-CAD condition (t(47)=5.48, p<0.001). Observer sensitivity was significantly greater for targets marked by CAD than the same targets in the no-CAD condition (t(51)=11.67, p<0.001). For targets not marked by CAD, there was no significant difference in observer sensitivity in the CAD condition compared to the same targets in the no-CAD condition (t(51)=0.88, p=0.382). These results suggest that the initial search may be influenced by the subsequent availability of CAD; if so, CAD efficacy studies should account for the effect when estimating benefit.

Paper Details

Date Published: 4 March 2019
PDF: 9 pages
Proc. SPIE 10952, Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment, 109520J (4 March 2019); doi: 10.1117/12.2512720
Show Author Affiliations
Ethan Du-Crow, Univ. of Manchester (United Kingdom)
Lucy Warren, Royal Surrey County Hospital (United Kingdom)
Susan M. Astley, Univ. of Manchester (United Kingdom)
Johan Hulleman, Univ. of Manchester (United Kingdom)

Published in SPIE Proceedings Vol. 10952:
Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)

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