Rationale and Objectives: To identify parameters linked to higher levels of performance in screening mammography. In particular we explored whether experience in reading digital cases enhances radiologists’ performance.

Methods: A total of 60 cases were presented to the readers, of which 20 contained cancers and 40 showed no abnormality. Each case comprised of four images and 129 breast readers participated in the study. Each reader was asked to identify and locate any malignancies using a 1-5 confidence scale. All images were displayed using 5MP monitors, supported by radiology workstations with full image manipulation capabilities. A jack-knife free-response receiver operating characteristic, figure of merit (JAFROC, FOM) methodology was employed to assess reader performance. Details were obtained from each reader regarding their experience, qualifications and breast reading activities. Spearman and Mann Whitney U techniques were used for statistical analysis.

Results: Higher performance was positively related to numbers of years professionally qualified (r= 0.18; P<0.05), number of years reading breast images (r= 0.24; P<0.01), number of mammography images read per year (r= 0.28; P<0.001) and number of hours reading mammographic images per week (r= 0.19; P<0.04). Unexpectedly, higher performance was inversely linked to previous experience with digital images (r= - 0.17; p<0.05) and further analysis, demonstrated that this finding was due to changes in specificity.

Conclusion: This study suggests suggestion that readers with experience in digital images reporting may exhibit a reduced ability to correctly identify normal appearances requires further investigation. Higher performance is linked to number of cases read per year.

Date Published: 17 March 2015
PDF: 8 pages
Proc. SPIE 9416, Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment, 94161L (17 March 2015); doi: 10.1117/12.2081749

Published in SPIE Proceedings Vol. 9416:
Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment
Claudia R. Mello-Thoms; Matthew A. Kupinski, Editor(s)