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• W2083907448 abstract "Rationale and Objectives. We quantified differences in the detection of simulated lung nodules on computed radiographs on the basis of variations in nodule size, local contrast, body habitus (global contrast), and exposure. Methods. A step-wedge phantom was developed to simulate the attenuation ranges of the lung, retrocardiac, and subdiaphragmatic regions of the adult human chest. Additional Lucite wedges were used to simulate two different body thicknesses and to provide variable structural noise. Soft-tissue-equivalent nodules of 3-mm and 5-mm diameter that resulted in 10% differences in attenuation from lung equivalence were embedded in lung-equivalent material. By superimposing the sheets in various positions, 84 unique nodule configurations containing eight nodules per image were exposed on a computed radiography system. Computed radiographs were acquired at two different exposures approximating standard exposure and underexposure. For each resulting phantom image, seven observers scored the presence or absence of a nodule within individual cells of a 5 × 5 grid matrix. Results. True-positive fractions for 3-mm-diameter nodules were very low across all conditions. True-positive fractions for 5-mm-diameter nodules varied from 0.23 to 0.98. Significant differences in the conspicuity of 5-mm nodules depended on differences in phantom thickness and differences in the locations of nodules within lung-, retrocardiac-, or subdiaphragmatic-equivalent regions. Accuracy in detecting nodules was significantly lower at lower exposures when nodules were located in the subdiaphragmatic-equivalent region. Conclusion. On computed radiographs, small nodules (5-mm diameter) can be reliably detected when they are located in areas of high or moderate surrounding local contrast, such as the lung or mediastinal regions. Detection of nodules decreases in regions of lower optical density corresponding to the subdiaphragmatic regions of the chest. The decrease in nodule detectability is greatest under conditions that simulate large body thickness and underexposure. We quantified differences in the detection of simulated lung nodules on computed radiographs on the basis of variations in nodule size, local contrast, body habitus (global contrast), and exposure. A step-wedge phantom was developed to simulate the attenuation ranges of the lung, retrocardiac, and subdiaphragmatic regions of the adult human chest. Additional Lucite wedges were used to simulate two different body thicknesses and to provide variable structural noise. Soft-tissue-equivalent nodules of 3-mm and 5-mm diameter that resulted in 10% differences in attenuation from lung equivalence were embedded in lung-equivalent material. By superimposing the sheets in various positions, 84 unique nodule configurations containing eight nodules per image were exposed on a computed radiography system. Computed radiographs were acquired at two different exposures approximating standard exposure and underexposure. For each resulting phantom image, seven observers scored the presence or absence of a nodule within individual cells of a 5 × 5 grid matrix. True-positive fractions for 3-mm-diameter nodules were very low across all conditions. True-positive fractions for 5-mm-diameter nodules varied from 0.23 to 0.98. Significant differences in the conspicuity of 5-mm nodules depended on differences in phantom thickness and differences in the locations of nodules within lung-, retrocardiac-, or subdiaphragmatic-equivalent regions. Accuracy in detecting nodules was significantly lower at lower exposures when nodules were located in the subdiaphragmatic-equivalent region. On computed radiographs, small nodules (5-mm diameter) can be reliably detected when they are located in areas of high or moderate surrounding local contrast, such as the lung or mediastinal regions. Detection of nodules decreases in regions of lower optical density corresponding to the subdiaphragmatic regions of the chest. The decrease in nodule detectability is greatest under conditions that simulate large body thickness and underexposure." @default.
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• W2083907448 title "Detection of simulated lung nodules with computed radiography: Effects of nodule size, local optical density, global object thickness, and exposure" @default.
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• W2083907448 doi "https://doi.org/10.1016/s1076-6332(96)80412-0" @default.
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