title: Accuracy is in the eyes of the pathologist: The visual interpretive process and diagnostic accuracy with digital whole slide images.
abstract: Digital whole slide imaging is an increasingly common medium in pathology, with application to education, telemedicine, and rendering second opinions. It has also made it possible to use eye tracking devices to explore the dynamic visual inspection and interpretation of histopathological features of tissue while pathologists review cases. Using whole slide images, the present study examined how a pathologist's diagnosis is influenced by fixed case-level factors, their prior clinical experience, and their patterns of visual inspection. Participating pathologists interpreted one of two test sets, each containing 12 digital whole slide images of breast biopsy specimens. Cases represented four diagnostic categories as determined via expert consensus: benign without atypia, atypia, ductal carcinoma in situ (DCIS), and invasive cancer. Each case included one or more regions of interest (ROIs) previously determined as of critical diagnostic importance. During pathologist interpretation we tracked eye movements, viewer tool behavior (zooming, panning), and interpretation time. Models were built using logistic and linear regression with generalized estimating equations, testing whether variables at the level of the pathologists, cases, and visual interpretive behavior would independently and/or interactively predict diagnostic accuracy and efficiency. Diagnostic accuracy varied as a function of case consensus diagnosis, replicating earlier research. As would be expected, benign cases tended to elicit false positives, and atypia, DCIS, and invasive cases tended to elicit false negatives. Pathologist experience levels, case consensus diagnosis, case difficulty, eye fixation durations, and the extent to which pathologists' eyes fixated within versus outside of diagnostic ROIs, all independently or interactively predicted diagnostic accuracy. Higher zooming behavior predicted a tendency to over-interpret benign and atypia cases, but not DCIS cases. Efficiency was not predicted by pathologist- or visual search-level variables. Results provide new insights into the medical interpretive process and demonstrate the complex interactions between pathologists and cases that guide diagnostic decision-making. Implications for training, clinical practice, and computer-aided decision aids are considered.
authors.affiliation: Center for Applied Brain & Cognitive Sciences, Tufts University, Medford, MA, United States. Electronic address: tbruny01@tufts.edu.
authors.forename: Tad T
authors.initials: TT
authors.lastname: Brunyé
authors.affiliation: Department of Computer Science and Engineering, University of Washington, Seattle, WA, United States.
authors.forename: Ezgi
authors.initials: E
authors.lastname: Mercan
authors.affiliation: Department of Pathology and UVM Cancer Center, University of Vermont, Burlington, VT, United States.
authors.forename: Donald L
authors.initials: DL
authors.lastname: Weaver
authors.affiliation: Department of Medicine, University of Washington School of Medicine, Seattle, WA, United States.
authors.forename: Joann G
authors.initials: JG
authors.lastname: Elmore
mesh_terms: D001706:Biopsy; D001940:Breast; D001943:Breast Neoplasms / Q000000981:diagnostic imaging*; D002983:Clinical Competence; D006801:Humans; D015588:Observer Variation; D000072142:Pathologists; D017216:Telemedicine
keywords: Breast cancer; Cognitive informatics; Decision making; Pathology; Whole slide imaging