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

Eye tracking diagnostic accuracy digital pathology interpretive behavior visual search

Journal

Visual cognition
ISSN: 1350-6285
Titre abrégé: Vis cogn
Pays: England
ID NLM: 9442139

Informations de publication

Date de publication:
2021
Historique:
entrez: 24 2 2022
pubmed: 25 2 2022
medline: 25 2 2022
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 35197796
doi: 10.1080/13506285.2021.1943093
pmc: PMC8863358
mid: NIHMS1718863
doi:

Types de publication

Journal Article

Langues

eng

Pagination

386-400

Subventions

Organisme : NCI NIH HHS
ID : R01 CA201376
Pays : United States

Déclaration de conflit d'intérêts

Declaration of Interests Statement: The authors have no conflicts of interest to declare.

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Auteurs

Tad T Brunyé (TT)

Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, USA.

Trafton Drew (T)

Department of Psychology, University of Utah, Salt Lake City, UT, USA.

Manob Jyoti Saikia (MJ)

Center for Applied Brain and Cognitive Sciences, Tufts University, Medford, MA, USA.

Kathleen F Kerr (KF)

Department of Biostatistics, University of Washington, Seattle, WA, USA.

Megan M Eguchi (MM)

Department of Biostatistics, University of Washington, Seattle, WA, USA.

Annie C Lee (AC)

Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, CA, USA.

Caitlin May (C)

Dermatopathology Northwest, Bellevue, WA, USA.

David E Elder (DE)

Division of Anatomic Pathology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA.

Joann G Elmore (JG)

Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, CA, USA.

Classifications MeSH