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OBJECTIVE: We aimed to identify the effect of computer-aided detection (CAD) on visual search and performance in CT Colonography (CTC) of inexperienced and experienced readers. METHODS: Fifteen endoluminal CTC examinations were recorded, each with one polyp, and two videos were generated, one with and one without a CAD mark. Forty-two readers (17 experienced, 25 inexperienced) interpreted the videos during infrared visual search recording. CAD markers and polyps were treated as regions of interest in data processing. This multi-reader, multi-case study was analysed using multilevel modelling. RESULTS: CAD drew readers' attention to polyps faster, accelerating identification times: median 'time to first pursuit' was 0.48 s (IQR 0.27 to 0.87 s) with CAD, versus 0.58 s (IQR 0.35 to 1.06 s) without. For inexperienced readers, CAD also held visual attention for longer. All visual search metrics used to assess visual gaze behaviour demonstrated statistically significant differences when "with" and "without" CAD were compared. A significant increase in the number of correct polyp identifications across all readers was seen with CAD (74 % without CAD, 87 % with CAD; p < 0.001). CONCLUSIONS: CAD significantly alters visual search and polyp identification in readers viewing three-dimensional endoluminal CTC. For polyp and CAD marker pursuit times, CAD generally exerted a larger effect on inexperienced readers. KEY POINTS: • Visual gaze is attracted by computer-assisted detection (CAD) marks on polyps • Inexperienced readers' gaze is affected more by CAD than experienced readers. • CAD marks could mean that the unannotated endoluminal surface is relatively neglected. • Correct polyp identification is increased significantly by CAD.

Original publication

DOI

10.1007/s00330-014-3569-z

Type

Journal article

Journal

Eur Radiol

Publication Date

06/2015

Volume

25

Pages

1570 - 1578

Keywords

Adult, Biomarkers, Clinical Competence, Colonic Polyps, Colonography, Computed Tomographic, Female, Humans, Male, Observer Variation, Radiographic Image Interpretation, Computer-Assisted, Reproducibility of Results