Photon-Counting Computed Tomography for Vascular Imaging of the Head and Neck: First In Vivo Human Results. Issue 3 (March 2018)

• Record Type: Journal Article
• Authors: Symons, Rolf; Reich, Daniel S.; Bagheri, Mohammadhadi; Cork, Tyler E.; Krauss, Bernhard; Ulzheimer, Stefan; Kappler, Steffen; Bluemke, David A.; Pourmorteza, Amir
• Is Part Of: Investigative radiology. Volume 53:Issue 3(2018:Mar.)
• Publication Date: 2018-03
• Subjects: photon-counting CT -- spectral CT -- CT angiography -- image quality -- carotid imaging -- brain angiography -- virtual monoenergetic images -- iodine mapping -- beam hardening; Diagnosis, Radioscopic -- Periodicals; Radiology, Medical -- Periodicals; 616.0757
• DOI: 10.1097/RLI.0000000000000418
• Languages: English
• ISSNs: 0020-9996

Abstract

Abstract : Purpose: The purpose of this study was to evaluate image quality of a spectral photon-counting detector (PCD) computed tomography (CT) system for evaluation of major arteries of the head and neck compared with conventional single-energy CT scans using energy-integrating detectors (EIDs). Methods: In this institutional review board–approved study, 16 asymptomatic subjects (7 men) provided informed consent and received both PCD and EID contrast-enhanced CT scans of the head and neck (mean age, 58 years; range, 46–75 years). Tube settings were (EID: 120 kVp/160 mA vs PCD: 140 kVp/108 mA) for all volunteers. Quantitative analysis included measurements of mean attenuation, image noise, and contrast-to-noise ratio (CNR). Spectral PCD data were used to reconstruct virtual monoenergetic images and iodine maps. A head phantom was used to validate iodine concentration measurements in PCD images only. Two radiologists blinded to detector type independently scored the image quality of different segments of the arteries, as well as diagnostic acceptability, image noise, and severity of artifacts of the PCD and EID images. Reproducibility was assessed with intraclass correlation coefficient. Linear mixed models that account for within-subject correlation of analyzed arterial segments were used. Linear regression and Bland-Altman analysis with 95% limits of agreement were used to calculate the accuracy of material decomposition. Results: Photon-counting detector image quality scores were significantly higher compared with EID image quality scores with lower image noise ( P < 0.01) and less image artifacts ( P < 0.001). Photon-counting detector image noise was 9.1% lower than EID image noise (8.0 ± 1.3 HU vs 8.8 ± 1.5 HU, respectively, P < 0.001). Arterial segments showed artifacts on EID images due to beam hardening that were not present on PCD images. On PCD images of the head phantom, there was excellent correlation ( R 2 = 0.998) between actual and calculated iodine concentrations without significant bias (bias: −0.4 mg/mL [95% limits of agreements: −1.1 to 0.4 mg/mL]). Iodine maps had 20.7% higher CNR compared with nonspectral PCD (65.2 ± 9.0 vs 54.0 ± 4.5, P = 0.01), and virtual monoenergetic image at 70 keV showed similar CNR to nonspectral images (52.6 ± 4.2 vs 54.0 ± 4.5, P = 0.39). Conclusions: Photon-counting CT has the potential to improve the image quality of carotid and intracranial CT angiography compared with single-energy EID CT.