Presentation + Paper
15 February 2021 Effect of time awake and hours slept at night on radiologists’ interpretations of mammogram images
Author Affiliations +
Abstract
This study aimed to investigate the effect on reading performance of how long radiologists have been awake (“time awake”) and the number of hours they slept at night (“hours slept at night”) before a reading session. Data from 133 mammographic reading assessments were extracted from the Breast Screen Reader Assessment Strategy database. Analysis of covariance was performed to determine whether sensitivity, specificity, lesion sensitivity, ROC, and JAFROC were influenced by the time awake and the hours slept at night. The results showed that less experienced radiologists’ performance varied significantly according to the time awake: lesion sensitivity was significantly lower among radiologists who performed readings after being awake for less than 2 h (44.6%) than among those who had been awake for 8 to <10 h (71.03%; p = 0.013); likewise, the same metric was significantly lower among those who had been awake for 4 to <6 h (47.7%) than among those who had been awake for 8 to <10 h (71.03%; p = 0.002) and for 10 to <12 h (63.46%; p = 0.026). The ROC values of the less experienced radiologists also seemed to depend on the hours slept at night: values for those who had slept ≤6 h (0.72) were significantly lower than for those who had slept >6 h (0.77) (p = 0.029). The results indicate that inexperienced radiologists’ performance may be affected by the time awake and hours slept the night before a reading session.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Abdulaziz S. Alshabibi, Moayyad E. Suleiman, Kriscia A. Tapia, Robert Heard, and Patrick C. Brennan "Effect of time awake and hours slept at night on radiologists’ interpretations of mammogram images", Proc. SPIE 11599, Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment, 115990R (15 February 2021); https://doi.org/10.1117/12.2580835
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CITATIONS
Cited by 1 scholarly publication.
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KEYWORDS
Mammography

Breast

Databases

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