Paper
18 March 2015 Reduction of iodinated contrast medium in CT: feasibility study
Author Affiliations +
Abstract
In CT, the magnitude of enhancement is proportional to the amount of contrast medium (CM) injected. However, high doses of iodinated CM pose health risks, ranging from mild side effects to serious complications such as contrast-induced nephropathy (CIN). This work presents a method that enables the reduction of CM dosage, without affecting the diagnostic image quality. The technique proposed takes advantage of the additional spectral information provided by photon-counting CT systems. In the first step, we apply a material decomposition technique on the projection data to discriminate iodine from other materials. Then, we estimated the noise of the decomposed image by calculating the Cramér-Rao lower bound of the parameter estimator. Next, we iteratively reconstruct the iodine-only image by using the decomposed image and the estimation of noise as an input into a maximum-likelihood iterative reconstruction algorithm. Finally, we combine the iodine-only image with the original image to enhance the contrast of low iodine concentrations. The resulting reconstructions show a notably improved contrast in the final images. Quantitatively, the combined image has a significantly improved CNR, while the measured concentrations are closer to the actual concentrations of the iodine. The preliminary results from our technique show the possibility of reducing the clinical dosage of iodine, without affecting the diagnostic image quality.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Radin A. Nasirudin, Kai Mei, Felix K. Kopp, Petar Penchev, Ernst J. Rummeny M.D., Martin Fiebich, and Peter B. Noël "Reduction of iodinated contrast medium in CT: feasibility study", Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 94122L (18 March 2015); https://doi.org/10.1117/12.2082143
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KEYWORDS
Iodine

Image enhancement

Reconstruction algorithms

Curium

Diagnostics

Photons

Sensors

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