Abstract

Objective. The purpose of this study was to determine the degree to which the number and angular disparity of component projections influence depth discrimination with tuned-aperture computed tomography. Study design. Groups of three tiny steel spheres served as fiducial references on and in four partially edentulous mandibles. Two spheres were attached to the facial and lingual surfaces of each mandible, and the third was fixed in the apical region of an open tooth socket. Errors in estimates of the depth of the apically positioned sphere relative to the other two spheres were determined from three-dimensional tuned-aperture computed tomography reconstructions. These data were compared with actual measurements produced independently with an optical micrometer. Multiple projections required by the tuned-aperture computed tomography reconstruction algorithm were produced from radially symmetric exposures bearing angular disparities of 5, 15, 30, and 45 degrees. The number of symmetrically dispersed projections per tuned-aperture computed tomography reconstruction likewise was varied systematically (2, 4, 8, 12, and 16 projections). These variables were manipulated through the use of a balanced factorial design. Depth estimates were performed by trained observers; the estimates were based on the determination of tuned-aperture computed tomography slices perceived as imaging the respective apical spheres in sharpest focus. Specimen and observer effects were also considered as independent variables. Resulting data were normalized by logarithmic transformation and analyzed statistically by analysis of variance. Results. Significant differences ( p < 0.005) were demonstrated for angular disparity and specimen effects, but the number of projections and the effect of the observer were not found to be statistically significant. Conclusions. In dentistry, angular disparities of 15 degrees or greater should be used when tuned-aperture computed tomography is being applied to diagnostic tasks requiring maximal depth discrimination accuracy.

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