State-of-the-Art Evaluation of Urinary Tract Disease with Use of Dual Energy Computed Tomography and Virtual Contrast Images.
In a new technology with dual X-ray tubes embedded in a CT-scanner - Dual Source Computed Tomography (DSCT) . information in collected from two rotating X-ray tubes with different energy (140 kV and 80 kV). The difference in the dissemnination and absorption of the photon's, with different energy in different tissue types provides a possibility to display this as differences in the gray scale of the images obtained from the X-ray tubes. Measurement and analysis of these small differencescan contribute to chemical differentiation of different tissue types, something that is not possible with CT scanners with only one X-ray tube. With dual enregy technology it has been shown that contrast medium provides far greater difference in gray scale than calcifications does. This feature helps to separate information coming from contrast medium from information from e.g. bone structures. Due to these possbilities there is now an opportunity to produce a virtual, non-contrast-enhanced image from a sequence where contrast agents has been given intravenously. One can thus avoid one extra series without intravenous contrast agents, and instead produce this virtually. It would therebybe possible to save the radiation dose from one series to the patient. The aim of this study is to compare the quality of the non-contrast enhanced computed tomography series with the virtual series in patients undergoing computed tomography or the urinary tract.
- Former Staff:
- Project Description:
The investigation is carried out with DSCT according to standard clinical procedures with one series before and one after intravenous administration of iodine contrast agents. The study will include 30 patients. We aim to compare image quality of the native image series before administration of contrast agents with virtually created image series where contrast medium information has been artificially removed. Visual Grading will be used to compare image quality of both image series. Further we plan to investigate if there is possibility to improve image quality and further reduce the radiation dose the patient by use of noise reducing software ContextVision.