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Proceedings Paper

How much is enough? Factors affecting the optimal interpretation of breast screening mammograms
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Paper Abstract

PERFORMS (Personal Performance in Mammographic Screening), a self-assessment scheme for film-readers is undertaken as an educational tool by mammographers reading breast-screening films in the UK. The scheme has been running as a bi-annual exercise since its inception in 1991. In addition to completing the scheme each year the majority of film-readers also choose to complete a questionnaire, administered as part of the scheme, indicating key aspects of their every-day reading practice. These key aspects include, volume of cases read per week, time-on-task reading screening films, incidence and time of break periods as well as typical number of film-reading sessions per week. Previous recommendations on best screening practice (significantly the optimum time on task) were considered in the light of these film-readers' self-reports on a current PERFORMS case set. In addition we looked at performance accuracy of over 450 film-readers reading PERFORMS cases (60 difficult mammographic cases). Performance on measures akin to True Positive (Correct Recall Percentages) and True Negative (Correct Return to Screen Percentages) decisions were investigated. Data presented demonstrate that individual behaviours in real life screening, for the interpretation of mammographic cases, affect film-reading accuracy on a test set of mammograms for specificity and sensitivity (namely volume of cases read per week and film-reading experience). The consequences for best screening practice, in real life, are considered.

Paper Details

Date Published: 20 March 2007
PDF: 10 pages
Proc. SPIE 6515, Medical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment, 65150F (20 March 2007); doi: 10.1117/12.708159
Show Author Affiliations
Hazel J. Scott, Loughborough Univ. (United Kingdom)
Alastair G. Gale, Loughborough Univ. (United Kingdom)


Published in SPIE Proceedings Vol. 6515:
Medical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment
Yulei Jiang; Berkman Sahiner, Editor(s)

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