PURPOSE: To evaluate the influence of monochrome LCDs with different resolutions on the detection performance of pulmonary nodules. MATERIALS AND METHODS: 187 chest DR images were selected from our hospital's picture archiving and communication system (PACS), including 111 normal cases and 76 cases with solitary pulmonary nodules. Those positive images were divided into two groups, A and B, according to the diameter of nodules. Three high-, three mid-, and three low-experienced radiologists interpreted those images with a 2 megapixel (MP), a 3 MP and a 5 MP monochrome LCD independently. Regarding the presence of the nodule, five-point confidence level rating scale was used: definite absence, probable absence, indetermination, probable presence and definite presence. The observers were requested to rank each image on the given display according to the presence of pulmonary nodule. Receiver operation characteristic (ROC) analysis was used to interpret the data. RESULTS: When detecting the pulmonary nodules of Group A on 2 MP-, 3 MP- and 5 MP-LCD, the areas under ROC curves (AUCs) were 0.641, 0.683 and 0.732 for high-experienced radiologists, 0.633, 0.679 and 0.716 for mid-experienced radiologists, 0.620, 0.652 and 0.719 for low-experienced radiologists, respectively; when detecting the pulmonary nodules of Group B, the AUCs were 0.811, 0.830 and 0.842 for high-experienced radiologists, 0.771, 0.821 and 0.837 for mid-experienced radiologists, 0.759, 0.770 and 0.829 for low-experienced radiologists, respectively. However, there were no significant differences among different reading modalities. CONCLUSION: For detecting pulmonary nodules, it is equivalent of observer performance among 2 MP-, 3 MP- and 5 MP-LCD.
PURPOSE: To evaluate the influence of monochrome LCDs with different resolutions on the detection performance of pulmonary nodules. MATERIALS AND METHODS: 187 chest DR images were selected from our hospital's picture archiving and communication system (PACS), including 111 normal cases and 76 cases with solitary pulmonary nodules. Those positive images were divided into two groups, A and B, according to the diameter of nodules. Three high-, three mid-, and three low-experienced radiologists interpreted those images with a 2 megapixel (MP), a 3 MP and a 5 MP monochrome LCD independently. Regarding the presence of the nodule, five-point confidence level rating scale was used: definite absence, probable absence, indetermination, probable presence and definite presence. The observers were requested to rank each image on the given display according to the presence of pulmonary nodule. Receiver operation characteristic (ROC) analysis was used to interpret the data. RESULTS: When detecting the pulmonary nodules of Group A on 2 MP-, 3 MP- and 5 MP-LCD, the areas under ROC curves (AUCs) were 0.641, 0.683 and 0.732 for high-experienced radiologists, 0.633, 0.679 and 0.716 for mid-experienced radiologists, 0.620, 0.652 and 0.719 for low-experienced radiologists, respectively; when detecting the pulmonary nodules of Group B, the AUCs were 0.811, 0.830 and 0.842 for high-experienced radiologists, 0.771, 0.821 and 0.837 for mid-experienced radiologists, 0.759, 0.770 and 0.829 for low-experienced radiologists, respectively. However, there were no significant differences among different reading modalities. CONCLUSION: For detecting pulmonary nodules, it is equivalent of observer performance among 2 MP-, 3 MP- and 5 MP-LCD.