OBJECTIVES: The aim of this study was to evaluate the effects on objective and subjective image quality of virtual monoenergetic reconstructions at various energy levels of dual-energy computed tomography (DECT) in patients with head and neck cancer. MATERIALS AND METHODS: We included 71 (53 men, 18 women; age, 59.3 ± 12.0 years; range, 33-90 years) patients with biopsy-proven untreated primary (n = 55) or recurrent (n = 16) squamous cell carcinoma who underwent head and neck DECT. Images were reconstructed with a linear blending setting emulating 120 kV acquisition (M_0.3; 30% of 80 kV, 70% of 140 kV spectrum) and as virtual monoenergetic images with photon energies of 40, 60, 80, and 100 keV. Attenuation of lesion, various anatomic landmarks, and image noise were objectively measured, and lesion contrast-to-noise ratio (CNR) was calculated. Two independent blinded radiologists subjectively rated each image series using a 5-point grading scale regarding overall image quality, lesion delineation, image sharpness, and image noise. RESULTS: Tumor attenuation peaked at 40 keV (140.2 ± 42.6 HU) followed by the 60 keV (121.7 ± 25.5 HU) and M_0.3 series (102.7 ± 22.3; all P < 0.001). However, the calculated lesion CNR was highest in the 60 keV reconstructions (12.45 ± 7.17), 80 keV reconstructions (8.66 ± 6.58), and M_0.3 series (5.21 ± 3.15; all P < 0.001) and superior to the other monoenergetic series (all P < 0.001). Subjective image analysis was highest for the 60 keV series regarding overall image quality (4.22; κ = 0.411) and lesion delineation (4.35; κ = 0.459) followed by the M_0.3 series (3.81; κ = 0.394; 3.77; κ = 0.451; all P < 0.001). Image sharpness showed no significant difference between both series (3.81 vs 3.79; P = 0.78). Image noise was rated superior in the 80 and 100 keV series (4.31 vs 4.34; P = 0.522). CONCLUSIONS: Compared with linearly blended images, virtual monoenergetic reconstructions of DECT data at 60 keV significantly improve lesion enhancement and CNR, subjective overall image quality, and tumor delineation of head and neck squamous cell carcinoma.
OBJECTIVES: The aim of this study was to evaluate the effects on objective and subjective image quality of virtual monoenergetic reconstructions at various energy levels of dual-energy computed tomography (DECT) in patients with head and neck cancer. MATERIALS AND METHODS: We included 71 (53 men, 18 women; age, 59.3 ± 12.0 years; range, 33-90 years) patients with biopsy-proven untreated primary (n = 55) or recurrent (n = 16) squamous cell carcinoma who underwent head and neck DECT. Images were reconstructed with a linear blending setting emulating 120 kV acquisition (M_0.3; 30% of 80 kV, 70% of 140 kV spectrum) and as virtual monoenergetic images with photon energies of 40, 60, 80, and 100 keV. Attenuation of lesion, various anatomic landmarks, and image noise were objectively measured, and lesion contrast-to-noise ratio (CNR) was calculated. Two independent blinded radiologists subjectively rated each image series using a 5-point grading scale regarding overall image quality, lesion delineation, image sharpness, and image noise. RESULTS: Tumor attenuation peaked at 40 keV (140.2 ± 42.6 HU) followed by the 60 keV (121.7 ± 25.5 HU) and M_0.3 series (102.7 ± 22.3; all P < 0.001). However, the calculated lesion CNR was highest in the 60 keV reconstructions (12.45 ± 7.17), 80 keV reconstructions (8.66 ± 6.58), and M_0.3 series (5.21 ± 3.15; all P < 0.001) and superior to the other monoenergetic series (all P < 0.001). Subjective image analysis was highest for the 60 keV series regarding overall image quality (4.22; κ = 0.411) and lesion delineation (4.35; κ = 0.459) followed by the M_0.3 series (3.81; κ = 0.394; 3.77; κ = 0.451; all P < 0.001). Image sharpness showed no significant difference between both series (3.81 vs 3.79; P = 0.78). Image noise was rated superior in the 80 and 100 keV series (4.31 vs 4.34; P = 0.522). CONCLUSIONS: Compared with linearly blended images, virtual monoenergetic reconstructions of DECT data at 60 keV significantly improve lesion enhancement and CNR, subjective overall image quality, and tumor delineation of head and neck squamous cell carcinoma.
Authors: Tommaso D'Angelo; Giuseppe Cicero; Silvio Mazziotti; Giorgio Ascenti; Moritz H Albrecht; Simon S Martin; Ahmed E Othman; Thomas J Vogl; Julian L Wichmann Journal: Br J Radiol Date: 2019-04-09 Impact factor: 3.039
Authors: Moritz H Albrecht; Jan-Erik Scholtz; Johannes Kraft; Ralf W Bauer; Moritz Kaup; Patricia Dewes; Andreas M Bucher; Iris Burck; Jens Wagenblast; Thomas Lehnert; J Matthias Kerl; Thomas J Vogl; Julian L Wichmann Journal: Eur Radiol Date: 2015-02-14 Impact factor: 5.315
Authors: Fabian K Lohöfer; Georgios A Kaissis; Frances L Köster; Sebastian Ziegelmayer; Ingo Einspieler; Carlos Gerngross; Michael Rasper; Peter B Noel; Steffen Koerdt; Andreas Fichter; Ernst J Rummeny; Rickmer F Braren Journal: Eur Radiol Date: 2018-05-28 Impact factor: 5.315
Authors: Simon S Martin; Moritz H Albrecht; Julian L Wichmann; Kristina Hüsers; Jan-Erik Scholtz; Christian Booz; Boris Bodelle; Ralf W Bauer; Sarah C Metzger; Thomas J Vogl; Thomas Lehnert Journal: Eur Radiol Date: 2016-05-28 Impact factor: 5.315
Authors: H Kuno; K Sakamaki; S Fujii; K Sekiya; K Otani; R Hayashi; T Yamanaka; O Sakai; M Kusumoto Journal: AJNR Am J Neuroradiol Date: 2018-01-25 Impact factor: 3.825
Authors: Moritz H Albrecht; Jan-Erik Scholtz; Kristina Hüsers; Martin Beeres; Andreas M Bucher; Moritz Kaup; Simon S Martin; Sebastian Fischer; Boris Bodelle; Ralf W Bauer; Thomas Lehnert; Thomas J Vogl; Julian L Wichmann Journal: Eur Radiol Date: 2015-09-03 Impact factor: 5.315
Authors: Matthias Stefan May; Marco Wiesmueller; Rafael Heiss; Michael Brand; Joscha Bruegel; Michael Uder; Wolfgang Wuest Journal: Eur Radiol Date: 2018-10-18 Impact factor: 5.315