PURPOSE: The purpose of this study was to assess the diagnostic accuracy of the temporal subtraction technique in the detection of primary lung cancers by readers with different levels of experience. METHODS: Previous and current chest radiographs from 40 patients with histologically proven lung cancer and 40 controls were studied. Temporal subtraction images were produced using an automated digital subtraction technique. We evaluated the effect of temporal subtraction images in the diagnosis of lung cancer with chest radiographs via an observer performance study with the use of receiver operating characteristic analysis. Six experienced radiologists and six residents participated as observers. RESULTS: Observer performance for all observers was superior when temporal subtraction images were used (mean Az value increased from 0.764 to 0.836, p=0.0006). Although the average Az value for residents increased significantly, from 0.707 to 0.795 (p=0.0038), the average Az value for experienced radiologists increased only from 0.821 to 0.878 (n.s.). CONCLUSION: In conclusion, the temporal subtraction technique clearly improves diagnostic accuracy for the detection of primary lung cancer. The results indicated that the use of temporal subtraction images was more beneficial for the residents than for the experienced radiologists. This method would compensate to some extent for experience-dependent diagnostic accuracy in the detection of lung cancer.
PURPOSE: The purpose of this study was to assess the diagnostic accuracy of the temporal subtraction technique in the detection of primary lung cancers by readers with different levels of experience. METHODS: Previous and current chest radiographs from 40 patients with histologically proven lung cancer and 40 controls were studied. Temporal subtraction images were produced using an automated digital subtraction technique. We evaluated the effect of temporal subtraction images in the diagnosis of lung cancer with chest radiographs via an observer performance study with the use of receiver operating characteristic analysis. Six experienced radiologists and six residents participated as observers. RESULTS: Observer performance for all observers was superior when temporal subtraction images were used (mean Az value increased from 0.764 to 0.836, p=0.0006). Although the average Az value for residents increased significantly, from 0.707 to 0.795 (p=0.0038), the average Az value for experienced radiologists increased only from 0.821 to 0.878 (n.s.). CONCLUSION: In conclusion, the temporal subtraction technique clearly improves diagnostic accuracy for the detection of primary lung cancer. The results indicated that the use of temporal subtraction images was more beneficial for the residents than for the experienced radiologists. This method would compensate to some extent for experience-dependent diagnostic accuracy in the detection of lung cancer.