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Improving the Quality of Cerebral Perfusion Maps With Monoenergetic Dual-Energy Computed Tomography Reconstructions.
- Source :
-
Journal of computer assisted tomography [J Comput Assist Tomogr] 2021 Jan-Feb 01; Vol. 45 (1), pp. 103-109. - Publication Year :
- 2021
-
Abstract
- Objective: We compared 40- to 70-keV virtual monoenergetic to conventional computed tomography (CT) perfusion reconstructions with respect to quality of perfusion maps.<br />Methods: Conventional CT perfusion (CTP) images were acquired at 80 kVp in 25 patients, and 40- to 70-keV images were acquired with a dual-layer CT at 120 kVp in 25 patients. First, time-attenuation-curve contrast-to-noise ratio was assessed. Second, the perfusion maps of both groups were qualitatively analyzed by observers. Last, the monoenergetic reconstruction with the highest quality was compared with the clinical standard 80-kVp CTP acquisitions.<br />Results: Contrast-to-noise ratio was significantly better for 40 to 60 keV as compared with 70 keV and conventional images (P < 0.001). Visually, the difference between the blood volume maps among reconstructions was minimal. The 50-keV perfusion maps had the highest quality compared with the other monoenergetic and conventional maps (P < 0.002).<br />Conclusions: The quality of 50-keV CTP images is superior to the quality of conventional 80- and 120-kVp images.<br />Competing Interests: The authors declare no conflict of interest.<br /> (Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.)
- Subjects :
- Adult
Aged
Aged, 80 and over
Female
Humans
Male
Middle Aged
Radiation Dosage
Retrospective Studies
Signal-To-Noise Ratio
Young Adult
Brain diagnostic imaging
Radiographic Image Interpretation, Computer-Assisted instrumentation
Radiography, Dual-Energy Scanned Projection methods
Tomography, X-Ray Computed methods
Subjects
Details
- Language :
- English
- ISSN :
- 1532-3145
- Volume :
- 45
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Journal of computer assisted tomography
- Publication Type :
- Academic Journal
- Accession number :
- 32176156
- Full Text :
- https://doi.org/10.1097/RCT.0000000000000981