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Tracking with virtual slides: a tool to study diagnostic error in histopathology
Author(s) -
Treanor Darren,
Lim Chee Hooi,
Magee Derek,
Bulpitt Andy,
Quirke Phil
Publication year - 2009
Publication title -
histopathology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.626
H-Index - 124
eISSN - 1365-2559
pISSN - 0309-0167
DOI - 10.1111/j.1365-2559.2009.03325.x
Subject(s) - medical diagnosis , zoom , diagnostic accuracy , medicine , medical physics , computer science , biopsy , histopathology , radiology , artificial intelligence , pathology , petroleum engineering , engineering , lens (geology)
Aims: To determine the reasons for diagnostic error by virtual slides which allow unsupervised study of diagnosis and error. Methods and results: Software was developed to produce visualizations of the diagnostic track followed by pathologists as they viewed virtual slides. These showed the diagnostic path in four dimensions (x, y, time and zoom), areas studied for >1000 ms, and included pathologists’ comments about the areas viewed. The system was used to study two trainee and two expert pathologists diagnosing 60 Barrett’s oesophageal biopsy specimens. Comparisons of the diagnostic tracks showed the reason for errors. Forty‐six cases had an expert consensus diagnosis. The trainees made errors in 21 and 15 cases, respectively, of which 11 and nine were clinically significant. Errors were made across the whole spectrum of diagnoses from negative to intramucosal carcinoma. Detailed examination of the tracks showed that in all errors there was incorrect interpretation of information; in three errors there was an additional failure to identify diagnostic features. Conclusions: Tracking with virtual slides is a useful tool in studying diagnosis and error, which has the potential for use in training and assessment.