Room 201
Purpose: To demonstrate that images with substantially reduced artifacts and quantitatively accurate estimation of iodine contrast estimation can be achieve for dual-energy pulmonary CT scans collected with limited-angular-range (LAR) data for reducing radiation time and scanning dose and for avoiding collision.
Methods: A digital chest phantom was used. Dual energy data were collected with a 2D fan-beam scanning geometry, where low- and high-kVp scans consist of overlapping arcs of limited-angular ranges. Three LARs were investigated, as 90o, 120o, and 150o, with an angular interval of 0.25o per view. A non-linear data model was used to generate data, considering two polychromatic X-ray spectra of 80 and 140 kVps. The data were first decomposed into basis sinogram using a standard data-domain decomposition method. Basis images were reconstructed from the basis sinogram, by use of the directional-total-variation (DTV) algorithm. From basis images, virtual monochromatic images (VMIs) were composed and visually assessed, while iodine contrast concentrations were estimated for quantitatively evaluation.
Results: The results show that, for the LARs and data condition considered in the work, the DTV algorithm yields VMIs that are visually comparable to the reference, obtained from the full-angular range of 360o, from noiseless LAR data and VMIs with substantially reduced artifacts from noisy LAR data. The iodine contrast concentrations can also be accurately estimated, as compared to the results obtained with the full-scan data of 360o.
Conclusion: We have investigated image reconstruction for quantitative dual-energy CT with LAR data for pulmonary scans. Dual-energy LAR data were collected with overlapping scanning arcs of low- and high-kVp spectra. Image artifacts, including BH and LAR artifacts, are correct for by the data-domain decomposition and DTV algorithm, and consequently quantitatively accurate estimation of iodine contrast concentration can be obtained, which could potentially be used for quantitative evaluation in lung cancer differentiation and myocardial perfusion.
Funding Support, Disclosures, and Conflict of Interest: XP serves as the Editor-in-Chief of IEEE Transactions on Biomedical Engineering, and is a shareholder and co-founder of Clarix Imaging Co. and XPIM LLC. There is no conflict of interest.