Optimizing High-Resolution MR Angiography: The Synergistic Effects of 3D Wheel Sampling and Deep Learning-Based Reconstruction.
Journal
Journal of computer assisted tomography
ISSN: 1532-3145
Titre abrégé: J Comput Assist Tomogr
Pays: United States
ID NLM: 7703942
Informations de publication
Date de publication:
12 Feb 2024
12 Feb 2024
Historique:
medline:
13
2
2024
pubmed:
13
2
2024
entrez:
12
2
2024
Statut:
aheadofprint
Résumé
The aim of this study was to assess the utility of the combined use of 3D wheel sampling and deep learning-based reconstruction (DLR) for intracranial high-resolution (HR)-time-of-flight (TOF)-magnetic resonance angiography (MRA) at 3 T. This prospective study enrolled 20 patients who underwent head MRI at 3 T, including TOF-MRA. We used 3D wheel sampling called "fast 3D" and DLR for HR-TOF-MRA (spatial resolution, 0.39 × 0.59 × 0.5 mm3) in addition to conventional MRA (spatial resolution, 0.39 × 0.89 × 1 mm3). We compared contrast and contrast-to-noise ratio between the blood vessels (basilar artery and anterior cerebral artery) and brain parenchyma, full width at half maximum in the P3 segment of the posterior cerebral artery among 3 protocols. Two board-certified radiologists evaluated noise, contrast, sharpness, artifact, and overall image quality of 3 protocols. The contrast and contrast-to-noise ratio of fast 3D-HR-MRA with DLR are comparable or higher than those of conventional MRA and fast 3D-HR-MRA without DLR. The full width at half maximum was significantly lower in fast 3D-MRA with and without DLR than in conventional MRA (P = 0.006, P < 0.001). In qualitative evaluation, fast 3D-MRA with DLR had significantly higher sharpness and overall image quality than conventional MRA and fast 3D-MRA without DLR (sharpness: P = 0.021, P = 0.001; overall image quality: P = 0.029, P < 0.001). The combination of 3D wheel sampling and DLR can improve visualization of arteries in intracranial TOF-MRA.
Identifiants
pubmed: 38346820
doi: 10.1097/RCT.0000000000001590
pii: 00004728-990000000-00288
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.
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