Radiology image perception and observer performance: how does expertise and clinical information alter interpretation? Stroke detection explored through eye-tracking
conference contributionposted on 2010-06-03, 08:27 authored by Lindsey Cooper, Alastair Gale, Iain T. Darker, Andoni Toms, Janak Saada
Historically, radiology research has been dominated by chest and breast screening. Few studies have examined complex interpretative tasks such as the reading of multidimensional brain CT or MRI scans. Additionally, no studies at the time of writing have explored the interpretation of stroke images; from novices through to experienced practitioners using eye movement analysis. Finally, there appears a lack of evidence on the clinical effects of radiology reports and their influence on image appraisal and clinical diagnosis. A computer-based, eye-tracking study was designed to assess diagnostic accuracy and interpretation in stroke CT and MR imagery. Eight predetermined clinical cases, five images per case, were presented to participants (novices, trainee, and radiologists; n=8). The presence or absence of abnormalities was rated on a five-point Likert scale and their locations reported. Half cases of the cases were accompanied by clinical information; half were not, to assess the impact of information on observer performance. Results highlight differences in visual search patterns amongst novice, trainee and expert observers; the most marked differences occurred between novice readers and experts. Experts spent more time in challenging areas of interest (AOI) than novices and trainee, and were more confident unless a lesion was large and obvious. The time to first AOI fixation differed by size, shape and clarity of lesion. ‘Time to lesion’ dropped significantly when recognition appeared to occur between slices. The influence of clinical information was minimal.
- Computer Science
CitationCOOPER, L. ... et al., 2009. Radiology image perception and observer performance: how does expertise and clinical information alter interpretation? Stroke detection explored through eye-tracking. IN: Sahiner, B. and Manning, D.J. (eds.). Medical Imaging 2009: Image Perception, Observer Performance, and Technology Assessment. Proceedings of SPIE, Vol. 7263, 72630K, 12 pp.
Publisher© 2009 Society of Photo-Optical Instrumentation Engineers
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NotesCopyright 2009 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. This paper can also be found at: http://dx.doi.org/10.1117/12.811098