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Determination of contrast media administration to achieve a targeted contrast enhancement in computed tomography.

作者信息

Sahbaee Pooyan, Segars Paul P, Marin Daniele, Nelson Rendon, Samei Ehsan

机构信息

Duke University, Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina 27705, United States; Siemens Medical Solutions USA, Inc., Malvern, Pennsylvania 19355, United States.

Duke University, Ravin Advanced Imaging Laboratories, Department of Radiology, Durham, North Carolina 27705, United States; Duke University, Medical Physics Graduate Program, Durham, North Carolina 27705, United States.

出版信息

J Med Imaging (Bellingham). 2016 Jan;3(1):013501. doi: 10.1117/1.JMI.3.1.013501. Epub 2016 Jan 20.

Abstract

Contrast enhancement is a key component of computed tomography (CT) imaging and offers opportunities for optimization. The design and optimization of techniques, however, require orchestration with the scan parameters and, further, a methodology to relate contrast enhancement and injection function. We used such a methodology to develop a method, the analytical inverse method, to predict the required injection function to achieve a desired contrast enhancement in a given organ by incorporation of a physiologically based compartmental model. The method was evaluated across 32 different target contrast enhancement functions for aorta, kidney, stomach, small intestine, and liver. The results exhibited that the analytical inverse method offers accurate performance with error in the range of 10% deviation between the predicted and desired organ enhancement curves. However, this method is incapable of predicting the injection function based on the liver enhancement. The findings of this study can be useful in optimizing contrast medium injection function as well as scan timing to provide more consistency in the way contrast-enhanced CT examinations are performed. To our knowledge, this work is one of the first attempts to predict the contrast material injection function for a desired organ enhancement curve.

摘要

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