A comprehensive review of imaging findings in COVID-19. Status in early 2021
Creators
- Afshar-Oromieh, Ali1
- Bohn, Karl Peter1
- Alberts, Ian1
- Mingels, Clemens1
- Shi, Kuangyu1
- Rominger, Axel1
- Prosch, Helmut2
- Thurnher, Majda2
- Schaefer-Prokop, Cornelia3, 4
- Cumming, Paul5, 1
- Peters, Alan6
- Huber, Adrian6
- Heverhagen, Johannes T.6
- Christe, Andreas6
- Ebner, Lukas6
- Geleff, Silvana7
- Lan, Xiaoli8
- Wang, Feng9
- Gräni, Christoph10
- Fontanellaz, Matthias11, 12
- Schöder, Heiko13
- Mougiakakou, Stavroula12, 6
- 1. Department of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, Freiburgstr. 18, CH-3010, Bern (Switzerland)
- 2. Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna (Austria)
- 3. Department of Medical Imaging, Radboud University, Nijmegen (Netherlands)
- 4. Department of Radiology, Meander Medical Center, Amersfoort (Netherlands)
- 5. School of Psychology and Counselling, Queensland University of Technology, Brisbane (Australia)
- 6. Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, Bern University Hospital, University of Bern, Bern (Switzerland)
- 7. Clinical Institute of Pathology, Medical University of Vienna, Vienna (Austria)
- 8. Department of Nuclear Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (China)
- 9. Department of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, Jiangsu (China)
- 10. Department of Cardiology, Inselspital, Bern University Hospital, University of Bern, Bern (Switzerland)
- 11. Department of Emergency Medicine, Inselspital, Bern University Hospital, University of Bern, Bern (Switzerland)
- 12. ARTORG Center for Biomedical Engineering Research, University of Bern, Bern (Switzerland)
- 13. Molecular Imaging and Therapy Service, Memorial Sloan Kettering Cancer Center, New York, NY (United States)
Description
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 [F]-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.
Additional details
Identifiers
Publishing Information
- Journal Title
- European Journal of Nuclear Medicine and Molecular Imaging
- Journal Volume
- 48
- Journal Issue
- 8
- Journal Page Range
- p. 2500-2524
- ISSN
- 1619-7070
- CODEN
- EJNMA6
INIS
- Country of Publication
- Germany
- Country of Input or Organization
- Germany
- INIS RN
- 52103883
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- ANGIOTENSIN; BIOMEDICAL RADIOGRAPHY; BRAIN; COMPARATIVE EVALUATIONS; CORONAVIRUSES; DIAGNOSIS; ENZYMES; GENETICS; HISTOLOGY; IMAGE PROCESSING; LUNGS; MACHINE LEARNING; NMR IMAGING; PATHOGENESIS; PERFORMANCE; PNEUMONIA; POSITRON COMPUTED TOMOGRAPHY; RECEPTORS; SCINTISCANNING; TISSUE DISTRIBUTION; ULTRASONOGRAPHY
- Descriptors DEC
- ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOLOGY; BODY; CARDIOVASCULAR AGENTS; CENTRAL NERVOUS SYSTEM; COMPUTERIZED TOMOGRAPHY; COUNTING TECHNIQUES; DIAGNOSTIC TECHNIQUES; DISEASES; DISTRIBUTION; DRUGS; EMISSION COMPUTED TOMOGRAPHY; EVALUATION; GLOBULINS; INFECTIOUS DISEASES; LEARNING; MATHEMATICAL LOGIC; MEDICINE; MEMBRANE PROTEINS; MICROORGANISMS; NERVOUS SYSTEM; NUCLEAR MEDICINE; ORGANIC COMPOUNDS; ORGANS; PARASITES; PROCESSING; PROTEINS; RADIOISOTOPE SCANNING; RADIOLOGY; RESPIRATORY SYSTEM; RESPIRATORY SYSTEM DISEASES; TOMOGRAPHY; VASOCONSTRICTORS; VIRAL DISEASES; VIRUSES; ZOONOTIC DISEASES