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 = 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.
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 = 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.
Authors: J P Schlomka; E Roessl; R Dorscheid; S Dill; G Martens; T Istel; C Bäumer; C Herrmann; R Steadman; G Zeitler; A Livne; R Proksa Journal: Phys Med Biol Date: 2008-07-08 Impact factor: 3.609
Authors: Victor Neuhaus; Nuran Abdullayev; Nils Große Hokamp; Gregor Pahn; Christoph Kabbasch; Anastasios Mpotsaris; David Maintz; Jan Borggrefe Journal: Invest Radiol Date: 2017-08 Impact factor: 6.016
Authors: Rolf Symons; Bernhard Krauss; Pooyan Sahbaee; Tyler E Cork; Manu N Lakshmanan; David A Bluemke; Amir Pourmorteza Journal: Med Phys Date: 2017-08-20 Impact factor: 4.071
Authors: S Leng; R Gutjahr; A Ferrero; S Kappler; A Henning; A Halaweish; W Zhou; J Montoya; C McCollough Journal: Proc SPIE Int Soc Opt Eng Date: 2017-03-09
Authors: Jan S Iwanczyk; Einar Nygård; Oded Meirav; Jerry Arenson; William C Barber; Neal E Hartsough; Nail Malakhov; Jan C Wessel Journal: IEEE Trans Nucl Sci Date: 2009 Impact factor: 1.679
Authors: Wei Zhou; David J Bartlett; Felix E Diehn; Katrina N Glazebrook; Amy L Kotsenas; Rickey E Carter; Joel G Fletcher; Cynthia H McCollough; Shuai Leng Journal: Invest Radiol Date: 2019-04 Impact factor: 6.016
Authors: W Zhou; J I Lane; M L Carlson; M R Bruesewitz; R J Witte; K K Koeller; L J Eckel; R E Carter; C H McCollough; S Leng Journal: AJNR Am J Neuroradiol Date: 2018-08-09 Impact factor: 3.825
Authors: Joakim da Silva; Fredrik Grönberg; Björn Cederström; Mats Persson; Martin Sjölin; Zlatan Alagic; Robert Bujila; Mats Danielsson Journal: J Med Imaging (Bellingham) Date: 2019-10-15
Authors: David J Bartlett; Chi Wan Koo; Brian J Bartholmai; Kishore Rajendran; Jayse M Weaver; Ahmed F Halaweish; Shuai Leng; Cynthia H McCollough; Joel G Fletcher Journal: Invest Radiol Date: 2019-03 Impact factor: 6.016
Authors: A Pourmorteza; R Symons; D S Reich; M Bagheri; T E Cork; S Kappler; S Ulzheimer; D A Bluemke Journal: AJNR Am J Neuroradiol Date: 2017-10-05 Impact factor: 3.825