How quickly do breast screeners learn their skills?

Hossein Nevisi; Leng Dong; Yan Chen; Alastair G. Gale

doi:10.1117/12.2255918

10 March 2017 How quickly do breast screeners learn their skills?

Hossein Nevisi, Leng Dong, Yan Chen, Alastair G. Gale

Proceedings Volume 10136, Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment; 101360D (2017) https://doi.org/10.1117/12.2255918
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

The UK’s Breast Screening Programme is 27 years old and many experienced breast radiologists are now retiring, coupled with an influx of new screening personnel. It is important to the ongoing Programme that new mammography readers are quickly up to the skill level of experienced readers. This raises the question of how quickly the necessary cancer detection skills are learnt. All breast screening radiologists in the UK read educational training sets of challenging FFDM images (the PERFORMS® scheme) yearly to maintain and improve their performance in real life screening. Data were examined from the PERFORMS® annual scheme for 54 new screeners, 55 screeners who have been screening for one year and also for more experienced screeners (597 screeners). Not surprisingly, significant differences in cancer detection rate were found between new readers and both of the other groups. Additionally, the performance of 48 new readers who have now been screening for about a year and have taken part twice in the PERFORMS® scheme were further examined where again a significant difference in cancer detection was found. These data imply that cancer detection skills are learnt quickly in the first year of screening. Information was also examined concerning the volume of cases participants read and other factors.

Conference Presentation

Citation Download Citation

Hossein Nevisi, Leng Dong, Yan Chen, and Alastair G. Gale "How quickly do breast screeners learn their skills?", Proc. SPIE 10136, Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment, 101360D (10 March 2017); https://doi.org/10.1117/12.2255918

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