RATIONALE AND OBJECTIVES: The aim of this study was to evaluate the usefulness of a novel computerized method for lung nodule detection on digital chest radiographs using temporal subtraction images. MATERIALS AND METHODS: To significantly reduce the number of false-positive results while maintaining high sensitivity, temporal subtraction images, which can enhance interval changes on sequential chest radiographs, were used. Fifty-one cases with lung nodules <3 cm and 51 cases without lung nodules were selected for an observer performance test. Twelve radiologists participated in this observer performance test. The radiologists' performance was evaluated using receiver-operating characteristic analysis, on a continuous rating scale. To estimate the numbers of cases affected beneficially and those affected detrimentally using this computerized method, the computer output was assumed to have an effect on an observer's diagnosis when there was a difference in rating score of ≥30% between the first and second ratings. RESULTS: The average area under the curve for all radiologists increased significantly from 0.849 to 0.950 with the computerized method (P < .001). The mean number of cases affected beneficially was significantly higher than that of cases affected detrimentally (8.92 vs 1.25, P < .001). CONCLUSIONS: The novel computerized method using temporal subtraction images would be useful in detecting lung nodules on digital chest radiographs.
RATIONALE AND OBJECTIVES: The aim of this study was to evaluate the usefulness of a novel computerized method for lung nodule detection on digital chest radiographs using temporal subtraction images. MATERIALS AND METHODS: To significantly reduce the number of false-positive results while maintaining high sensitivity, temporal subtraction images, which can enhance interval changes on sequential chest radiographs, were used. Fifty-one cases with lung nodules <3 cm and 51 cases without lung nodules were selected for an observer performance test. Twelve radiologists participated in this observer performance test. The radiologists' performance was evaluated using receiver-operating characteristic analysis, on a continuous rating scale. To estimate the numbers of cases affected beneficially and those affected detrimentally using this computerized method, the computer output was assumed to have an effect on an observer's diagnosis when there was a difference in rating score of ≥30% between the first and second ratings. RESULTS: The average area under the curve for all radiologists increased significantly from 0.849 to 0.950 with the computerized method (P < .001). The mean number of cases affected beneficially was significantly higher than that of cases affected detrimentally (8.92 vs 1.25, P < .001). CONCLUSIONS: The novel computerized method using temporal subtraction images would be useful in detecting lung nodules on digital chest radiographs.
Authors: Thaworn Dendumrongsup; Andrew A Plumb; Steve Halligan; Thomas R Fanshawe; Douglas G Altman; Susan Mallett Journal: PLoS One Date: 2014-12-26 Impact factor: 3.240