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suck abstract from ncbi


10.1016/j.amsu.2021.102489

http://scihub22266oqcxt.onion/10.1016/j.amsu.2021.102489
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34178312!8214462!34178312
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suck abstract from ncbi

pmid34178312      Ann+Med+Surg+(Lond) 2021 ; 69 (ä): 102489
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  • Covid-19 imaging: A narrative review #MMPMID34178312
  • Ramdani H; Allali N; Chat L; El Haddad S
  • Ann Med Surg (Lond) 2021[Sep]; 69 (ä): 102489 PMID34178312show ga
  • BACKGROUND: The 2019 novel coronavirus disease (COVID-19) imaging data is dispersed in numerous publications. A cohesive literature review is to be assembled. OBJECTIVE: To summarize the existing literature on Covid-19 pneumonia imaging including precautionary measures for radiology departments, Chest CT's role in diagnosis and management, imaging findings of Covid-19 patients including children and pregnant women, artificial intelligence applications and practical recommendations. METHODS: A systematic literature search of PubMed/med line electronic databases. RESULTS: The radiology department's staff is on the front line of the novel coronavirus outbreak. Strict adherence to precautionary measures is the main defense against infection's spread. Although nucleic acid testing is Covid-19's pneumonia diagnosis gold standard; kits shortage and low sensitivity led to the implementation of the highly sensitive chest computed tomography amidst initial diagnostic tools. Initial Covid-19 CT features comprise bilateral, peripheral or posterior, multilobar ground-glass opacities, predominantly in the lower lobes. Consolidations superimposed on ground-glass opacifications are found in few cases, preponderantly in the elderly. In later disease stages, GGO transformation into multifocal consolidations, thickened interlobular and intralobular lines, crazy paving, traction bronchiectasis, pleural thickening, and subpleural bands are reported. Standardized CT reporting is recommended to guide radiologists. While lung ultrasound, pulmonary MRI, and PET CT are not Covid-19 pneumonia's first-line investigative diagnostic modalities, their characteristic findings and clinical value are outlined. Artificial intelligence's role in strengthening available imaging tools is discussed. CONCLUSION: This review offers an exhaustive analysis of the current literature on imaging role and findings in COVID-19 pneumonia.
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