Improvement of neurovascular imaging using ultra-high-resolution computed tomography angiography

dc.contributor.authorUcar, Felix A.
dc.contributor.authorFrenzel, Marius
dc.contributor.authorKronfeld, Andrea
dc.contributor.authorAltmann, Sebastian
dc.contributor.authorSanner, Antoine P.
dc.contributor.authorAbello Mercado, Mario Alberto
dc.contributor.authorUphaus, Timo
dc.contributor.authorBrockmann, Marc A.
dc.contributor.authorOthman, Ahmed E.
dc.date.accessioned2024-01-16T07:50:11Z
dc.date.available2024-01-16T07:50:11Z
dc.date.issued2023
dc.description.abstractObjective To evaluate diagnostic image quality of ultra-high-resolution computed tomography angiography (UHR-CTA) in neurovascular imaging as compared to normal resolution CT-angiography (NR-CTA). Material and Methods In this retrospective single-center study brain and neck CT-angiography was performed using an ultra-high-resolution computed tomography scanner (n = 82) or a normal resolution CT scanner (NR-CTA; n = 73). Ultra-high-resolution images were reconstructed with a 1024 × 1024 matrix and a slice thickness of 0.25 mm, whereas NR-CT images were reconstructed with a 512 × 512 matrix and a slice thickness of 0.5 mm. Three blinded neuroradiologists assessed overall image quality, artifacts, image noise, overall contrast and diagnostic confidence using a 4-point Likert scale. Furthermore, the visualization and delineation of supra-aortic arteries with an emphasis on the visualization of small intracerebral vessels was assessed using a cerebral vascular score, also utilizing a 4-point Likert scale. Quantitative analyses included signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), noise and the steepness of gray value transition. Radiation exposure was determined by comparison of computed tomography dose index (CTDIvol), dose length product (DLP) and mean effective dose. Interrater agreement was evaluated via determining Fleiss-Kappa. Results Ultra-high-resolution CT-angiography (UHR-CTA) yielded excellent image quality with superior quantitative (SNR: p < 0.001, CNR: p < 0.001, steepness of gray value transition: p < 0.001) and qualitative results (overall image quality: 4 (Inter quartile range (IQR) = 4–4); p < 0.001, diagnostic confidence: 4 (IQR = 4–4); p < 0.001) compared to NR-CT (overall image quality: 3 (IQR = 3–3), diagnostic confidence: 3 (IQR = 3–4)). Furthermore, UHR-CT enabled significantly superior delineation and visualization of all vascular segments, from proximal extracranial vessels to the smallest peripheral cerebral branches (e.g., UHR-CTA PICA: 4 (3–4) vs. NR-CTA PICA: 3 (2–3); UHR-CTA P4: 4 (IQR = 3–4) vs. NR-CTA P4: 2 (IQR = 2–3); UHR-CTA M4: 4 (IQR = 4–4) vs. NR-CTA M4: 3 (IQR = 2–3); UHR-CTA A4: 4 (IQR = 3–4) vs. NR-CTA A4: 2 (IQR = 2–3); all p < 0.001). Noteworthy, a reduced mean effective dose was observed when applying UHR-CT (NR-CTA: 1.8 ± 0.3 mSv; UHR-CTA: 1.5 ± 0.5 mSv; p < 0.001). Conclusion Ultra-high-resolution CT-angiography improves image quality in neurovascular imaging allowing the depiction and evaluation of small peripheral cerebral arteries. It may thus improve the detection of pathologies in small cerebrovascular lesions and the resulting diagnosis.en_GB
dc.identifier.doihttp://doi.org/10.25358/openscience-9779
dc.identifier.urihttps://openscience.ub.uni-mainz.de/handle/20.500.12030/9797
dc.language.isoengde
dc.rightsCC-BY-4.0*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subject.ddc610 Medizinde_DE
dc.subject.ddc610 Medical sciencesen_GB
dc.titleImprovement of neurovascular imaging using ultra-high-resolution computed tomography angiographyen_GB
dc.typeZeitschriftenaufsatzde
jgu.journal.titleClinical neuroradiologyde
jgu.journal.volumeVersion of Record (VoR)de
jgu.organisation.departmentFB 04 Medizinde
jgu.organisation.nameJohannes Gutenberg-Universität Mainz
jgu.organisation.number2700
jgu.organisation.placeMainz
jgu.organisation.rorhttps://ror.org/023b0x485
jgu.publisher.doi10.1007/s00062-023-01348-1de
jgu.publisher.issn1869-1447de
jgu.publisher.nameUrban & Vogelde
jgu.publisher.placeMünchende
jgu.publisher.year2023
jgu.rights.accessrightsopenAccess
jgu.subject.ddccode610de
jgu.subject.dfgLebenswissenschaftende
jgu.type.dinitypeArticleen_GB
jgu.type.resourceTextde
jgu.type.versionPublished versionde

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