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Optimizing Dual-Energy CT Technique for Iodine-Based Compound Contrast-To-Noise Ratio

E Sidky1*, F Terzioglu2, J Phillips1, G Bal1, I Reiser1, X Pan1, (1) University of Chicago, Chicago, IL, (2) North Carolina State University

Presentations

PO-GePV-I-7 (Sunday, 7/10/2022)   [Eastern Time (GMT-4)]

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Purpose: Dual-energy can be useful for enhancing contrast in CT imaging with iodine-based contrast agents. The goal of this work is to establish a framework in which iodine-based compound contrast is optimized over scan technique, which includes X-ray source kilovoltage-peak (kVp) settings and source fluence for both the low and high kVP scans.

Methods: We consider only physics-based processing for the dual-energy X-ray transmission data, where this data is processed into sinograms of basis materials that are subsequently reconstructed and used to form a virtual monochromatic image (VMI). This image represents the X-ray attenuation map at a set X-ray energy value that is also optimized for contrast-to-noise ratio (CNR). This physics-based approach is selected because it avoids beam-hardening artifacts that can appear in image-based processing. The VMI is chosen over basis tissue images for display, because dual-energy data is notsufficient to uniquely determine bone, soft-tissue, and iodine-compound sinograms. The physics modeling for the dual-energy CT system includes available models for Tungsten X-ray source spectra, low and high kVp fluence, response of energy-integrating detectors, and compound Poisson noise. For the dual-energy CT transmission data processing and image formation, the considered factors are: the Jacobian of transmission-to-sinogram transform, basis tissues, and the energy for the VMI. The methodology is demonstrated on a 2D dual-energy CT simulated scan of a simple circular water phantom with inserted Iodine-solution and calcium disk signals.

Results: The dual-energy CT scan parameters are optimized on the CNR of the lowest concentration iodine-solution disk. The dependence of CNR on some of the involved parameters is shown in the supplemental document.

Conclusion: Optimizing dual-energy CT scan parameters depends strongly on the imaging task, and careful consideration of all of the relevant factors is needed in order to maximize the task metric.

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