BACKGROUND: Increased vessel contrast in low-keV virtual monoenergetic images (VMI) in spectral detector CT angiography of the head and neck requires adaption of window settings. Aim of this study was to define generally applicable window settings of low-keV VMI. METHODS: Two radiologists determined ideal subjective window settings for VMI40-70 keV in 54 patients. To obtain generally applicable window settings, center and width values were modeled against the attenuation of the internal carotid artery (HUICA). This modeling was performed with and without respect to keV. Subsequently, image quality of VMI40-70 keV was assessed using the model-based determined window settings. RESULTS: With decreasing keV values, HUICA increased significantly in comparison to conventional images (CI) (P<0.05 for 40-60 keV). No significant differences between modelled and individually recorded window settings were found confirming validity of the obtained models (P values: 0.2-1.0). However, modelling with respect to keV was marginally less precise. CONCLUSIONS: Window settings of low-keV VMI can be semi-automatically determined in dependency of the ICA attenuation in spectral detector CTA of the head and neck. The reported models are a promising tool to leverage the improved image quality of these images in clinical routine. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
BACKGROUND: Increased vessel contrast in low-keV virtual monoenergetic images (VMI) in spectral detector CT angiography of the head and neck requires adaption of window settings. Aim of this study was to define generally applicable window settings of low-keV VMI. METHODS: Two radiologists determined ideal subjective window settings for VMI40-70 keV in 54 patients. To obtain generally applicable window settings, center and width values were modeled against the attenuation of the internal carotid artery (HUICA). This modeling was performed with and without respect to keV. Subsequently, image quality of VMI40-70 keV was assessed using the model-based determined window settings. RESULTS: With decreasing keV values, HUICA increased significantly in comparison to conventional images (CI) (P<0.05 for 40-60 keV). No significant differences between modelled and individually recorded window settings were found confirming validity of the obtained models (P values: 0.2-1.0). However, modelling with respect to keV was marginally less precise. CONCLUSIONS: Window settings of low-keV VMI can be semi-automatically determined in dependency of the ICA attenuation in spectral detector CTA of the head and neck. The reported models are a promising tool to leverage the improved image quality of these images in clinical routine. 2021 Quantitative Imaging in Medicine and Surgery. All rights reserved.
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