Non-contrast photon counting computed tomography of the head

\(\bf Background\) Photon counting CT (PCCT) is a promising technique for neuroradiological CT examinations. In initial studies on non-contrast PCCT of the head (NCCT), however, artifacts close to the calvarium were noticed, which lead to an inhomogeneous representation of the brain tissue. In this study, a new software for image reconstruction to reduce artifacts is evaluated. \(\bf Methods\) In the new CT software developed by the manufacturer, off-focal radiation was remodeled and is mathematically corrected in the NCCT in data processing during image formation. For the evaluation, 60 patients with an NCCT in the currently used software and 44 patients in the new software were included retrospectively. A detailed quantitative analysis using multiple regions of interest and a qualitative analysis with a reading by experienced radiologists was performed to evaluate image quality and tissue homogeneity below the calvarium. \(\bf Results\) The new software reduced the inhomogeneity of the cortical brain tissue near the calvarium. As a quantitative measure, there is a clear reduction of the signal difference of the gray and white matter at different distances from the calvarium (\(\it p\) < 0.001). In the qualitative analysis, the inhomogeneity of the brain tissue was reduced, and the gray-white differentiation improved (\(\it p\) < 0.001) in the clinically used virtual monoenergetic image at 65 keV. \(\bf Conclusions\) Optimized modelling and mathematical correction of the off-focal radiation in the new software led to an effective reduction of the inhomogeneity of the cortical brain tissue and thus improved image quality.

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Dokumentenrepositorium der RUB (Ruhr University Bochum)
Published
2025-07-18
Primary Topic
Advanced X-ray and CT Imaging
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article

Non-contrast photon counting computed tomography of the head

Martin Petersilka, Lukas Goertz, Tanja Kurzendorfer, Arwed Elias Michael et al.
Dokumentenrepositorium der RUB (Ruhr University Bochum)
Advanced X-ray and CT Imaging
article

Non-contrast photon counting computed tomography of the head

Martin Petersilka, Lukas Goertz, Tanja Kurzendorfer, Arwed Elias Michael, D Schönbeck, Matthias Michael Woeltjen, Julius Henning Niehoff, Christoph Mönninghoff, Jan (Univ.-Prof. Dr. med.) Borggrefe
article en

Abstract

\(\bf Background\) Photon counting CT (PCCT) is a promising technique for neuroradiological CT examinations. In initial studies on non-contrast PCCT of the head (NCCT), however, artifacts close to the calvarium were noticed, which lead to an inhomogeneous representation of the brain tissue. In this study, a new software for image reconstruction to reduce artifacts is evaluated. \(\bf Methods\) In the new CT software developed by the manufacturer, off-focal radiation was remodeled and is mathematically corrected in the NCCT in data processing during image formation. For the evaluation, 60 patients with an NCCT in the currently used software and 44 patients in the new software were included retrospectively. A detailed quantitative analysis using multiple regions of interest and a qualitative analysis with a reading by experienced radiologists was performed to evaluate image quality and tissue homogeneity below the calvarium. \(\bf Results\) The new software reduced the inhomogeneity of the cortical brain tissue near the calvarium. As a quantitative measure, there is a clear reduction of the signal difference of the gray and white matter at different distances from the calvarium (\(\it p\) < 0.001). In the qualitative analysis, the inhomogeneity of the brain tissue was reduced, and the gray-white differentiation improved (\(\it p\) < 0.001) in the clinically used virtual monoenergetic image at 65 keV. \(\bf Conclusions\) Optimized modelling and mathematical correction of the off-focal radiation in the new software led to an effective reduction of the inhomogeneity of the cortical brain tissue and thus improved image quality.

Dokumentenrepositorium der RUB (Ruhr University Bochum)
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Advanced X-ray and CT Imaging
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