Please use this identifier to cite or link to this item: https://hdl.handle.net/10316/113331
DC FieldValueLanguage
dc.contributor.authorBorges, Ana P-
dc.contributor.authorAntunes, Célia-
dc.contributor.authorAlves, Filipe Caseiro-
dc.date.accessioned2024-02-15T11:58:46Z-
dc.date.available2024-02-15T11:58:46Z-
dc.date.issued2023-05-09-
dc.identifier.issn2075-4418pt
dc.identifier.urihttps://hdl.handle.net/10316/113331-
dc.description.abstractUsing two different energy levels, dual-energy computed tomography (DECT) allows for material differentiation, improves image quality and iodine conspicuity, and allows researchers the opportunity to determine iodine contrast and radiation dose reduction. Several commercialized platforms with different acquisition techniques are constantly being improved. Furthermore, DECT clinical applications and advantages are continually being reported in a wide range of diseases. We aimed to review the current applications of and challenges in using DECT in the treatment of liver diseases. The greater contrast provided by low-energy reconstructed images and the capability of iodine quantification have been mostly valuable for lesion detection and characterization, accurate staging, treatment response assessment, and thrombi characterization. Material decomposition techniques allow for the non-invasive quantification of fat/iron deposition and fibrosis. Reduced image quality with larger body sizes, cross-vendor and scanner variability, and long reconstruction time are among the limitations of DECT. Promising techniques for improving image quality with lower radiation dose include the deep learning imaging reconstruction method and novel spectral photon-counting computed tomography.pt
dc.language.isoengpt
dc.publisherMDPIpt
dc.rightsopenAccesspt
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt
dc.subjectdual-energy CTpt
dc.subjectspectral CTpt
dc.subjectliver diseasept
dc.subjectpancreatic diseasept
dc.subjectdual-source CTpt
dc.subjectfast kVp switchingpt
dc.subjectdual-layer detector CTpt
dc.subjectsplit-filterpt
dc.subjectimage qualitypt
dc.subjectphoton countingpt
dc.titleSpectral CT: Current Liver Applicationspt
dc.typearticle-
degois.publication.firstPage1673pt
degois.publication.issue10pt
degois.publication.titleDiagnosticspt
dc.peerreviewedyespt
dc.identifier.doi10.3390/diagnostics13101673pt
degois.publication.volume13pt
dc.date.embargo2023-05-09*
uc.date.periodoEmbargo0pt
item.grantfulltextopen-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.openairetypearticle-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextCom Texto completo-
crisitem.author.researchunitCNC - Center for Neuroscience and Cell Biology-
crisitem.author.orcid0000-0001-9397-6149-
Appears in Collections:FMUC Medicina - Artigos em Revistas Internacionais
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This item is licensed under a Creative Commons License Creative Commons