title: Computer model to optimise contrast in chest radiography.
abstract: X-ray imaging of the chest is challenging because of the large differences in x-ray attenuation between the mediastinal and lung regions of the chest. This large dynamic range of chest exit exposure, along with associated large changes in the scatter component of the beam, makes film based chest imaging difficult to optimise in terms of image contrast and image receiver latitude. Chest radiographic contrast has been studied in terms of intensifying screen luminance differences, as a function of kVp and scatter rejection. An anatomical model has been derived from CT studies and includes simulation of typical lung, retrocardiac and mediastinal regions with the contrast medium of a 5 mm water equivalent mass. Information has also been obtained on the range of luminance generated in the receptor between the three regions. Comparative patient doses have also been calculated. The computer model consists of analytical algorithms, beginning with the primary spectra generated after the method of Birch and Marshall. The generation of secondary radiation is achieved by an algorithm that parameterises published Monte Carlo data. Grid transmission is calculated for both primary and secondary radiation. The energy absorbed in the screen is calculated to include the absorption of K-characteristic radiation. Simulation of energies from 60-120 kVp with a variety of grids (including no grid) showed that contrast, in all areas of the chest radiograph, was a weak function of kVp and a strong function of scatter rejection. This was most evident in thicker regions such as the mediastinum.(ABSTRACT TRUNCATED AT 250 WORDS)
authors.affiliation: School of Medical Radiation Technology, University of Sydney, Lidcombe.
authors.forename: D
authors.initials: D
authors.lastname: McLean
mesh_terms: D003198:Computer Simulation; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging; D008482:Mediastinum / Q000000981:diagnostic imaging; D008954:Models, Biological; D008961:Models, Structural; D009010:Monte Carlo Method; D011856:Radiographic Image Enhancement / Q000379:methods*; D013902:Radiography, Thoracic; D014057:Tomography, X-Ray Computed