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Proceedings Paper

Characteristics of the group of radiologists that benefits the most using Breast Screen Reader Assessment Strategy (BREAST)
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Paper Abstract

Purpose: To determine the impact of Breast Screen Reader Assessment Strategy (BREAST) over time in improving radiologists’ breast cancer detection performance, and to identify the group of radiologists that benefit the most by using BREAST as a training tool. Materials and Methods: Thirty-six radiologists who completed three case-sets offered by BREAST were included in this study. The case-sets were arranged in radiologists’ chronological order of completion and five performance measures (sensitivity, specificity, location sensitivity, receiver operating characteristics area under the curve (ROC AUC) and jackknife alternative free-response receiver operating characteristic (JAFROC) figure–of-merit (FOM)), available from BREAST, were compared between case-sets to determine the level of improvement achieved. The radiologists were then grouped based on their characteristics and the above performance measures between the case-sets were compared. Paired t-tests or Wilcoxon signed-rank tests with statistical significance set at p < 0.05 were used to compare the performance measures. Results: Significant improvement was demonstrated in radiologists’ case-set performance in terms of location sensitivity and JAFROC FOM over the years, and radiologists’ location sensitivity and JAFROC FOM showed significant improvement irrespective of their characteristics. In terms of ROC AUC, significant improvement was shown for radiologists who were reading screen mammograms for more than 7 years and spent more than 9 hours per week reading mammograms. Conclusion: Engaging with case-sets appears to enhance radiologists’ performance suggesting the important value of initiatives such as BREAST. However, such performance enhancement was not shown for everyone, highlighting the need to tailor the BREAST platform to benefit all radiologists.

Paper Details

Date Published: 7 March 2018
PDF: 7 pages
Proc. SPIE 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, 1057718 (7 March 2018); doi: 10.1117/12.2293511
Show Author Affiliations
A. Ganesan, Univ. of Sydney (Australia)
M. Alakhras, Univ. of Sydney (Australia)
Jordan Univ. of Science and Technology (Jordan)
P. C. Brennan, Univ. of Sydney (Australia)
W. Lee, Univ. of Sydney (Australia)
BreastScreen NSW (Australia)
K. Tapia, Univ. of Sydney (Australia)
C. Mello-Thoms, Univ. of Sydney (Australia)

Published in SPIE Proceedings Vol. 10577:
Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)

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