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Melanoma in the Blink of an Eye: Pathologists’ Rapid Detection, Classification, and Localization of Skin Abnormalities

Authors :
David E. Elder
Annie C. Lee
Trafton Drew
Caitlin May
Tad T. Brunyé
Megan M. Eguchi
Kathleen F. Kerr
Manob Jyoti Saikia
Joann G. Elmore
Source :
Vis cogn
Publication Year :
2021

Abstract

Expert radiologists can quickly extract a basic "gist" understanding of a medical image following less than a second exposure, leading to above-chance diagnostic classification of images. Most of this work has focused on radiology tasks (such as screening mammography), and it is currently unclear whether this pattern of results and the nature of visual expertise underlying this ability are applicable to pathology, another medical imaging domain demanding visual diagnostic interpretation. To further characterize the detection, localization, and diagnosis of medical images, this study examined eye movements and diagnostic decision-making when pathologists were briefly exposed to digital whole slide images of melanocytic skin biopsies. Twelve resident (N = 5), fellow (N = 5), and attending pathologists (N = 2) with experience interpreting dermatopathology briefly viewed 48 cases presented for 500 ms each, and we tracked their eye movements towards histological abnormalities, their ability to classify images as containing or not containing invasive melanoma, and their ability to localize critical image regions. Results demonstrated rapid shifts of the eyes towards critical abnormalities during image viewing, high diagnostic sensitivity and specificity, and a surprisingly accurate ability to localize critical diagnostic image regions. Furthermore, when pathologists fixated critical regions with their eyes, they were subsequently much more likely to successfully localize that region on an outline of the image. Results are discussed relative to models of medical image interpretation and innovative methods for monitoring and assessing expertise development during medical education and training.

Details

Language :
English
Database :
OpenAIRE
Journal :
Vis cogn
Accession number :
edsair.doi.dedup.....0bd7a029d6aee72404cd423008fea725