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

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...

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Publicado en:Journal of Digital Imaging Vol. 31; no. 1; pp. 32 - 42
Autores principales: Mercan, Ezgi, Shapiro, Linda G., Brunyé, Tad T., Weaver, Donald L., Elmore, Joann G.
Formato: research tables/charts Journal Article
Publicado: Springer Nature Feb2018
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Springer Nature
      place: New York, New York
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        atl: Characterizing Diagnostic Search Patterns in Digital Breast Pathology: Scanners and Drillers.
      aug:
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          Mercan, Ezgi
          Shapiro, Linda G.
          Brunyé, Tad T.
          Weaver, Donald L.
          Elmore, Joann G.
        affil: Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
      sug:
        subj:
          Decision Making, Clinical
          Breast Neoplasms Diagnosis
          Pathologists
          Human
          Biopsy
          Repeated Measures
          Analysis of Variance
          Adult
          Middle Age
          Aged
          Female
          Male
          T-Tests
          P-Value
          Funding Source
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Female
          Male
      ab: 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: <italic>scanning</italic> is characterized by panning at a constant zoom level, while <italic>drilling</italic> 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.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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