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Feasibility of Ultra-High Resolution Supra-Aortic CT Angiography: An Assessment of Diagnostic Image Quality and Radiation Dose

Authors :
Felix Anton Ucar
Marius Frenzel
Mario Alberto Abello Mercado
Sebastian Altmann
Sebastian Reder
Carolin Brockmann
Marc A Brockmann
Ahmed E Othman
Source :
Tomography, Vol 7, Iss 4, Pp 711-720 (2021)
Publication Year :
2021
Publisher :
MDPI AG, 2021.

Abstract

(1) Background: To evaluate diagnostic image quality and radiation exposure of ultra-high resolution cerebral Computed-Tomography (CT) angiography (CTA) obtained on an ultra-high resolution computed tomography scanner (UHR-CT). (2) Methods: Fifty consecutive patients with UHR-CTA were enrolled. Image reconstruction was processed with a 1024 × 1024 matrix and a slice thickness of 0.25 mm. Quantitative analyses comprising CT values, contrast–noise ratio (CNR) and signal-to-noise ratio (SNR) were performed. Subjective assessment of image quality, vessel contrast, noise, artefacts and delineation of different sized vessels were assessed by two readers on a 4-point scale. Radiation exposure was determined. (3) Results: Hounsfield values (ACI: 461.8 ± 16.8 HU; MCA: 406.1 ± 24.2 HU; BA: 412.2 ± 22.3 HU), SNR (ACI: 35.4 ± 13.1; MCA: 20.8 ± 12.4; BA: 23.7 ± 12.9) and CNR (ACI: 48.7 ± 21; MCA: 63.9 ± 26.9; BA: 48.1 ± 21.4) were remarkably high in all segments. Subjective analysis by two raters (fair agreement, k = 0.26) indicated excellent image qualities (image quality = 4; contrast = 4; noise = 3; artefacts = 4).Our analysis revealed a notably high traceability of the cerebral perforators (3 Points). Radiation exposure was at moderate dose levels (effective dose = 2.5 ± 0.6mSv). (4) Conclusions: UHR-CTA generates highly valuable image qualities that allow the depiction of vessels including cerebral perforators at acceptable dose levels. The UHR-CTA may therefore enhance the detection of small cerebral pathologies and may improve interpretability, especially in settings where high image qualities are crucial for the diagnostic accuracy.

Details

Language :
English
ISSN :
2379139X and 23791381
Volume :
7
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Tomography
Publication Type :
Academic Journal
Accession number :
edsdoj.68a0955495924a70b7e4e26438453b2a
Document Type :
article
Full Text :
https://doi.org/10.3390/tomography7040059