A method for improving iodine contrast enhancement in abdominal computed tomography: experimental study in a pig model

• Published in: European radiology Vol. 23; no. 4; pp. 985 - 990
• Main Authors: Noël, Peter B., Bendik, Edgar, Münzel, Daniela, Schneider, Armin, Goshen, Liran, Gringauz, Asher, Lamash, Yechiel, Vlassenbroek, Alain, Fingerle, Alexander A., Rummeny, Ernst J., Dobritz, Martin
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01-04-2013; Springer Nature B.V
• Subjects: Abdomen; Algorithms; Anesthesia; Animals; Computed Tomography; Contrast agents; Contrast Media - administration & dosage; Diagnostic Radiology; Dose-Response Relationship, Drug; Imaging; Internal Medicine; Interventional Radiology; Iodine; Iopamidol - administration & dosage; Iopamidol - analogs & derivatives; Medicine; Medicine & Public Health; Neuroradiology; Radiographic Image Enhancement - methods; Radiography, Abdominal - methods; Radiology; Reproducibility of Results; Sensitivity and Specificity; Swine; Tomography; Tomography, X-Ray Computed - methods; Ultrasound; United States > US; Germany; Non-ionic iodine; Computed tomography; Contrast-enhanced computed tomography; Contrast enhancement; Contrast agent
• ISSN: 0938-7994; 1432-1084
• DOI: 10.1007/s00330-012-2668-y

Objectives
To investigate the improvement in diagnostic image quality of an iodine contrast enhancement tool in an animal model for computed tomography (CT).
Methods
One pig was examined over several consecutive days with a CT system. The quantity of iodine as contrast medium (0.6–1.2 ml/kg) varied among different acquisitions. The contrast enhancement in the reconstructed slices was improved via a post-processing tool. The post-processing tool is an algorithm designed for enhancement of iodine contrast in CT data. Contrast-to-noise ratio (CNR), the detectability between soft-tissue and vascular structures, and quantitative image analysis were assessed.
Results
When reducing the quantity of contrast medium, our subjective image quality assessment revealed that it is visually possible to generate similar enhancement with less iodine. This observation was confirmed quantitatively in our CNR results. While employing the algorithm, the CNR between vascular structures and subcutaneous fat significantly improved. For unenhanced regions, we identified no change in HU values and no significant strengthening of artefacts.
Conclusions
With post-processing there was a significantly improved diagnostic image quality compared with non-processed data. In particular, similar contrast enhancement could be achieved with a reduced quantity of contrast medium injected during the CT acquisition.
Key Points
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Enhancement with iodine based contrast agents is an essential part of CT
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A new post-processing tool significantly improves diagnostic image quality
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It may also help reduce the iodine load required for intravenous enhancement.