Dataset Information

Characterizing Diagnostic Search Patterns in Digital Breast Pathology: Scanners and Drillers.

ABSTRACT: Following a baseline demographic survey, 87 pathologists interpreted 240 digital whole slide images of breast biopsy specimens representing a range of diagnostic categories from benign to atypia, ductal carcinoma in situ, and invasive cancer. A web-based viewer recorded pathologists' behaviors while interpreting a subset of 60 randomly selected and randomly ordered slides. To characterize diagnostic search patterns, we used the viewport location, time stamp, and zoom level data to calculate four variables: average zoom level, maximum zoom level, zoom level variance, and scanning percentage. Two distinct search strategies were confirmed: scanning is characterized by panning at a constant zoom level, while drilling involves zooming in and out at various locations. Statistical analysis was applied to examine the associations of different visual interpretive strategies with pathologist characteristics, diagnostic accuracy, and efficiency. We found that females scanned more than males, and age was positively correlated with scanning percentage, while the facility size was negatively correlated. Throughout 60 cases, the scanning percentage and total interpretation time per slide decreased, and these two variables were positively correlated. The scanning percentage was not predictive of diagnostic accuracy. Increasing average zoom level, maximum zoom level, and zoom variance were correlated with over-interpretation.

SUBMITTER: Mercan E

PROVIDER: S-EPMC5788829 | biostudies-other | 2018 Feb

REPOSITORIES: biostudies-other

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Characterizing Diagnostic Search Patterns in Digital Breast Pathology: Scanners and Drillers.

Mercan Ezgi E Shapiro Linda G LG Brunyé Tad T TT Weaver Donald L DL Elmore Joann G JG

Journal of digital imaging 20180201 1

Following a baseline demographic survey, 87 pathologists interpreted 240 digital whole slide images of breast biopsy specimens representing a range of diagnostic categories from benign to atypia, ductal carcinoma in situ, and invasive cancer. A web-based viewer recorded pathologists' behaviors while interpreting a subset of 60 randomly selected and randomly ordered slides. To characterize diagnostic search patterns, we used the viewport location, time stamp, and zoom level data to calculate four ...[more]

PMID: 28681097

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Dataset Information

Characterizing Diagnostic Search Patterns in Digital Breast Pathology: Scanners and Drillers.

Publications

Characterizing Diagnostic Search Patterns in Digital Breast Pathology: Scanners and Drillers.

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