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abstract
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Abstract Computed tomography (CT) scans are performed both with and without intravenous (IV) and/or enteric contrast, drugs used to improve the discrimination of vascular structures, improve tissue characterization, search for bowel perforation or fistulae, and many related applications. IV contrast is nephrotoxic, especially in patients with impaired renal function. Consequently, many patients cannot or should not have IV contrast, so non-contrast CT (NC-CT) scans are often performed, despite their intrinsic limitations, which include poor contrast-to-noise properties. There is a critical and immediate need to improve the diagnostic performance of such unenhanced scans. The long-term goal of this project is to overcome the limitations of NC-CT using statistically principled image reconstruction optimized for specific applications. The intrinsic contrast-to-noise will be increased by reducing noise while preserving resolution using projection-domain smoothing and restoration with explicit models of measurement statistics. Successful completion of this work may provide superior CT imaging performance for patients with chronic kidney disease, contrast allergy, obesity, and for screening applications where radiation dose is limited. There are 4 specific aims: (1) An instrument-specific mathematical model will be synthesized using the statistical and physical properties of a particular clinical CT scanner. (2) Penalized-likehood sinogram restoration methods will be implemented on NC-CT exams. (3) The NC-CT image reconstruction strategy will be implemented on dedicated hardware to achieve clinically useful reconstruction times. (4) The penalized-likelihood sinogram restoration strategy will be optimized to deliver tailored algorithms for specific NC-CT applications and tested on a database of clinical cases. On completion, this project will provide a validated means to reconstruct non-contrast CT scans with significantly improved signal-to-noise and contrast-to-noise, thereby improving the diagnostic performance for emergency examinations. The system will be flexible and clinically feasible for multicenter testing in selected applications. The reconstruction methods will be optimized for the most promising applications, and preliminary measurements of diagnostic performance will be available. Project Narrative The long term goal of this project is to develop and apply statistically principled image reconstruction approaches for non-contrast computed tomography (CT). The intrinsic contrast-to-noise will be increased by reducing noise while preserving resolution using projection-domain smoothing and restoration with explicit models of measurement statistics.
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label
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Tailored Algorithms for Non-Contrast Computed Tomography Using Sinogram Restorati
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