Abstract
In CT colonography, orally administered positive-contrast fecal-tagging agents are used for differentiating residual fluid and feces from true lesions. However, the presence of high-density tagging agent in the colon can introduce erroneous artifacts, such as local pseudo-enhancement and beam-hardening, on the reconstructed CT images, thereby complicating reliable detection of soft-tissue lesions. In dual-energy CT colonography, such image artifacts can be reduced by the calculation of virtual monochromatic CT images, which provide more accurate quantitative attenuation measurements than conventional single-energy CT colonography. In practice, however, virtual monochromatic images may still contain some pseudo-enhancement artifacts, and efforts to minimize radiation dose may enhance such artifacts. In this study, we evaluated the effect of image-based pseudo-enhancement post-correction on virtual monochromatic images in standard-dose and low-dose dual-energy CT colonography. The mean CT values of the virtual monochromatic standard-dose CT images of 51 polyps and those of the virtual monochromatic low-dose CT images of 20 polyps were measured without and with the pseudo-enhancement correction. Statistically significant differences were observed between uncorrected and pseudo-enhancement-corrected images of polyps covered by fecal tagging in standard-dose CT (p < 0.001) and in low-dose CT (p < 0.05). The results indicate that image-based pseudo-enhancement post-correction can be useful for optimizing the performance of image-processing applications in virtual monochromatic CT colonography.
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Acknowledgments
This work was supported in part by grant CA095279, CA131781, and CA166816 from the National Cancer Institute at the National Institutes of Health.
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Tachibana, R., Näppi, J.J., Yoshida, H. (2014). Application of Pseudo-enhancement Correction to Virtual Monochromatic CT Colonography. In: Yoshida, H., Näppi, J., Saini, S. (eds) Abdominal Imaging. Computational and Clinical Applications. ABD-MICCAI 2014. Lecture Notes in Computer Science(), vol 8676. Springer, Cham. https://doi.org/10.1007/978-3-319-13692-9_16
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DOI: https://doi.org/10.1007/978-3-319-13692-9_16
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