A comprehensive review of imaging findings in COVID-19 - status in early 2021.
Medical imaging methods are assuming a greater role in the workup of patients with COVID-19, mainly in relation to the primary manifestation of pulmonary disease and the tissue distribution of the angiotensin-converting-enzyme 2 (ACE 2) receptor. However, the field is so new that no consensus view h...
| Publicado en: | European Journal of Nuclear Medicine & Molecular Imaging Vol. 48; no. 8; pp. 2500 - 2525 |
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| Autores principales: | , , , , , , , , , , , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Jul2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=152814353&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 152814353 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16197070 NPC jtl: European Journal of Nuclear Medicine & Molecular Imaging issn: 16197070 maglogo: N pubinfo: dt: Jul2021 vid: 48 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 152814353 150099497 10.1007/s00259-021-05375-3 152814353 ppf: 2500 ppct: 25 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A comprehensive review of imaging findings in COVID-19 - status in early 2021. aug: au: Afshar-Oromieh, Ali Prosch, Helmut Schaefer-Prokop, Cornelia Bohn, Karl Peter Alberts, Ian Mingels, Clemens Thurnher, Majda Cumming, Paul Shi, Kuangyu Peters, Alan Geleff, Silvana Lan, Xiaoli Wang, Feng Huber, Adrian Gräni, Christoph Heverhagen, Johannes T. Rominger, Axel Fontanellaz, Matthias Schöder, Heiko Christe, Andreas affil: Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, Freiburgstr. 18, CH-3010, Bern, Switzerland sug: ab: Medical imaging methods are assuming a greater role in the workup of patients with COVID-19, mainly in relation to the primary manifestation of pulmonary disease and the tissue distribution of the angiotensin-converting-enzyme 2 (ACE 2) receptor. However, the field is so new that no consensus view has emerged guiding clinical decisions to employ imaging procedures such as radiography, computer tomography (CT), positron emission tomography (PET), and magnetic resonance imaging, and in what measure the risk of exposure of staff to possible infection could be justified by the knowledge gained. The insensitivity of current RT-PCR methods for positive diagnosis is part of the rationale for resorting to imaging procedures. While CT is more sensitive than genetic testing in hospitalized patients, positive findings of ground glass opacities depend on the disease stage. There is sparse reporting on PET/CT with [18F]-FDG in COVID-19, but available results are congruent with the earlier literature on viral pneumonias. There is a high incidence of cerebral findings in COVID-19, and likewise evidence of gastrointestinal involvement. Artificial intelligence, notably machine learning is emerging as an effective method for diagnostic image analysis, with performance in the discriminative diagnosis of diagnosis of COVID-19 pneumonia comparable to that of human practitioners. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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