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.
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.
Authors: K Kobayashi; T Sugimoto; H Makino; M Kumagai; M Unoura; N Tanaka; Y Kato; N Hattori Journal: Hepatology Date: 1985 Nov-Dec Impact factor: 17.425
Authors: T E Mayer; G F Hamann; J Baranczyk; B Rosengarten; E Klotz; M Wiesmann; U Missler; G Schulte-Altedorneburg; H J Brueckmann Journal: AJNR Am J Neuroradiol Date: 2000-09 Impact factor: 3.825
Authors: James D Eastwood; Michael H Lev; Max Wintermark; Clemens Fitzek; Daniel P Barboriak; David M Delong; Ting-Yim Lee; Tarek Azhari; Michael Herzau; Vani R Chilukuri; James M Provenzale Journal: AJNR Am J Neuroradiol Date: 2003-10 Impact factor: 3.825
Authors: Daniele Marin; Rendon C Nelson; Sebastian T Schindera; Samuel Richard; Richard S Youngblood; Terry T Yoshizumi; Ehsan Samei Journal: Radiology Date: 2010-01 Impact factor: 11.105
Authors: Young Wook Jeon; Seo Hyun Kim; Ji Yong Lee; Kum Whang; Myung Soon Kim; Young Ju Kim; Myeong Sub Lee Journal: Korean J Radiol Date: 2011-12-23 Impact factor: 3.500
Authors: Edgar Bendik; Peter B Noël; Daniela Münzel; Alexander A Fingerle; Martin Henninger; Christian Markus; Alain Vlassenbroek; Ernst J Rummeny; Martin Dobritz Journal: Eur Radiol Date: 2013-09-03 Impact factor: 5.315