Dual-Energy Computed Tomography Angiography of the Head and Neck With Single-Source Computed Tomography: A New Technical (Split Filter) Approach for Bone Removal. Issue 10 (October 2016)

• Record Type: Journal Article
• Authors: Kaemmerer, Nadine; Brand, Michael; Hammon, Matthias; May, Matthias; Wuest, Wolfgang; Krauss, Bernhard; Uder, Michael; Lell, Michael M.
• Is Part Of: Investigative radiology. Volume 51:Issue 10(2016:Oct.)
• Publication Date: 2016-10
• Subjects: dual-energy CT -- single-source CT -- bone removal -- carotid artery -- CT angiography -- atherosclerosis -- head and neck imaging; Diagnosis, Radioscopic -- Periodicals; Radiology, Medical -- Periodicals; 616.0757
• DOI: 10.1097/RLI.0000000000000290
• Languages: English
• ISSNs: 0020-9996

Abstract

Abstract : Objectives: Dual-energy computed tomographic angiography (DE-CTA) has been demonstrated to improve the visualization of the head and neck vessels. The aim of this study was to test the potential of split-filter single-source dual-energy CT to automatically remove bone from the final CTA data set. Materials and Methods: Dual-energy CTA was performed in 50 consecutive patients to evaluate the supra-aortic arteries, either to grade carotid artery stenosis or to rule out traumatic dissections. Dual-energy CTA was performed on a 128-slice single-source CT system equipped with a special filter array to separate the 120-kV spectrum into a high- and a low-energy spectrum for DE-based automated bone removal. Image quality of fully automated bone suppression and subsequent manual optimization was evaluated by 2 radiologists on maximum intensity projections using a 4-grade scoring system. The effect of image reconstruction with an iterative metal artifact reduction algorithm on DE postprocessing was tested using a 3-grade scoring system, and the time demand for each postprocessing step was measured. Results: Two patients were excluded due to insufficient arterial contrast enhancement; in the remaining 48 patients, automated bone removal could be performed successfully. The addition of iterative metal artifact reduction algorithm improved image quality in 58.3% of the cases. After manual optimization, DE-CTA image quality was rated excellent in 7, good in 29, and moderate in 10 patients. Interobserver agreement was high (κ = 0.85). Stenosis grading was not influenced using DE-CTA with bone removal as compared with the original CTA. The time demand for DE image reconstruction was significantly higher than for single-energy reconstruction (42.1 vs 20.9 seconds). Conclusions: Our results suggest that bone removal in DE-CTA of the head and neck vessels with a single-source CT is feasible and can be performed within acceptable time and moderate user interaction.