Does computer-aided diagnosis for lung tumors change satisfaction of search in chest radiography?

Computer-aided diagnosis (CAD) has been developed to ensure that the radiologist considers suspect focal opacities that may represent cancer in chest radiography. Although CAD was not developed to counteract the satisfaction of search (SOS) effect, it may be an effective intervention to do so. The objective of this study is to determine whether an idealized CAD can reduce SOS effects in chest radiography.

Fifty-seven chest radiographs, half of which demonstrated diverse, native abnormalities were read twice by 16 observers, once with and once without the addition of a simulated pulmonary nodule. Simulated CAD prompts were provided during the interpretation, which unerringly pointed to the added simulated nodule. Area under the ROC curve for detecting the native abnormalities was estimated for each observer in each treatment condition. In addition to testing for the SOS effect in the presence of CAD prompts, results were compared to those of a previous SOS study.

Significantly more nodules were reported in the SOS with CAD experiment than in the original SOS experiment (49 versus 43, P < .01). An SOS effect was found even when CAD prompts were provided; ROC areas for detecting native abnormalities were reduced with added nodules [0.68 versus 0.65, P (one-tailed) < .05]. Comparison of the current experiment with CAD and the previous SOS experiments failed to show a significant difference of the magnitude of the SOS effect (P = .52). The threshold for reporting was more conservative with CAD prompts than in SOS studies (P = .052).

Our results indicate that the CAD prompts, even those that always point to their target lesion without false-positive error, fail to counteract SOS in chest radiography. The stricter decision thresholds with CAD prompts may indicate less visual search for native abnormalities.