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22 May 2003 Computer-aided detection of lung cancer on chest radiographs: differences in the interpretation time of radiologist's showing vs. not showing improvement with CAD
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Abstract
Using data from a clinical trial of a commercial CAD system for lung cancer detection, we are comparing the time used for interpreting chest radiographs between the radiologists showing improvement in detecting lung cancer with computer assistance to those not showing improvement. While measurement showed that the 15 radiologists as a group showed improvement (the Az was 0.8288 in independent reading, and 0.8654 in sequential reading with CAD, improvement has a P-value of 0.0058), there were 9 radiologists who showed improvement and 6 who did not. The behavior of the radiologists differed between the cases that contained cancer and those that were cancer-free. For the cases that contained a cancer, there was no statistically significant difference in time between the two groups (P-value 0.26). For the cancer-free cases, we found a statistically significant greater interpretation time for the radiologists whose performance in cancer detection was better with computer assistance compared to those without improvement (P-value 0.02). This work shows that radiologists who increased their detection of lung cancer using CAD, compared to those who showed no improvement, significantly increased their reading time when they determined that true negative cases for cancer were indeed true negative cases, but did not increase reading time for true positive decision on cancer cases.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Teresa Osicka, Matthew T. Freedman M.D., Shih-Chung Benedict Lo, Fleming Lure, Xin-Wei Xu, Jesse Lin, Hui Zhao, and Ron Zhang "Computer-aided detection of lung cancer on chest radiographs: differences in the interpretation time of radiologist's showing vs. not showing improvement with CAD", Proc. SPIE 5034, Medical Imaging 2003: Image Perception, Observer Performance, and Technology Assessment, (22 May 2003); https://doi.org/10.1117/12.480347
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