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What eye tracking can tell us about how radiologists use automated breast ultrasound

What eye tracking can tell us about how radiologists use automated breast ultrasound Abstract.Purpose: Automated breast ultrasound (ABUS) presents three-dimensional (3D) representations of the breast in the form of stacks of coronal and transverse plane images. ABUS is especially useful for the assessment of dense breasts. Here, we present the first eye tracking data showing how radiologists search and evaluate ABUS cases.Approach: Twelve readers evaluated single-breast cases in 20-min sessions. Positive findings were present in 56% of the evaluated cases. Eye position and the currently visible coronal and transverse slice were tracked, allowing for reconstruction of 3D “scanpaths.”Results: Individual readers had consistent search strategies. Most readers had strategies that involved examination of all available images. Overall accuracy was 0.74 (sensitivity = 0.66 and specificity = 0.84). The 20 false negative errors across all readers can be classified using Kundel’s (1978) taxonomy: 17 are “decision” errors (readers found the target but misclassified it as normal or benign). There was one recognition error and two “search” errors. This is an unusually high proportion of decision errors. Readers spent essentially the same proportion of time viewing coronal and transverse images, regardless of whether the case was positive or negative, correct or incorrect. Readers tended to use a “scanner” strategy when viewing coronal images and a “driller” strategy when viewing transverse images.Conclusions: These results suggest that ABUS errors are more likely to be errors of interpretation than of search. Further research could determine if readers’ exploration of all images is useful or if, in some negative cases, search of transverse images is redundant following a search of coronal images. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Medical Imaging SPIE

What eye tracking can tell us about how radiologists use automated breast ultrasound

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Publisher
SPIE
Copyright
© 2022 Society of Photo-Optical Instrumentation Engineers (SPIE)
ISSN
2329-4302
eISSN
2329-4310
DOI
10.1117/1.jmi.9.4.045502
Publisher site
See Article on Publisher Site

Abstract

Abstract.Purpose: Automated breast ultrasound (ABUS) presents three-dimensional (3D) representations of the breast in the form of stacks of coronal and transverse plane images. ABUS is especially useful for the assessment of dense breasts. Here, we present the first eye tracking data showing how radiologists search and evaluate ABUS cases.Approach: Twelve readers evaluated single-breast cases in 20-min sessions. Positive findings were present in 56% of the evaluated cases. Eye position and the currently visible coronal and transverse slice were tracked, allowing for reconstruction of 3D “scanpaths.”Results: Individual readers had consistent search strategies. Most readers had strategies that involved examination of all available images. Overall accuracy was 0.74 (sensitivity = 0.66 and specificity = 0.84). The 20 false negative errors across all readers can be classified using Kundel’s (1978) taxonomy: 17 are “decision” errors (readers found the target but misclassified it as normal or benign). There was one recognition error and two “search” errors. This is an unusually high proportion of decision errors. Readers spent essentially the same proportion of time viewing coronal and transverse images, regardless of whether the case was positive or negative, correct or incorrect. Readers tended to use a “scanner” strategy when viewing coronal images and a “driller” strategy when viewing transverse images.Conclusions: These results suggest that ABUS errors are more likely to be errors of interpretation than of search. Further research could determine if readers’ exploration of all images is useful or if, in some negative cases, search of transverse images is redundant following a search of coronal images.

Journal

Journal of Medical ImagingSPIE

Published: Jul 1, 2022

Keywords: breast ultrasound; eye tracking; medical error; visual search; mammography

References