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10.3389/fmolb.2021.614207

http://scihub22266oqcxt.onion/10.3389/fmolb.2021.614207
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33869276!8044917!33869276
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suck abstract from ncbi


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pmid33869276      Front+Mol+Biosci 2021 ; 8 (ä): 614207
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  • Chest CT Images for COVID-19: Radiologists and Computer-Based Detection #MMPMID33869276
  • Dou Q; Liu J; Zhang W; Gu Y; Hsu WT; Ho KC; Tong HS; Yu WY; Lee CC
  • Front Mol Biosci 2021[]; 8 (ä): 614207 PMID33869276show ga
  • BACKGROUND: Characteristic chest computed tomography (CT) manifestation of 2019 novel coronavirus (COVID-19) was added as a diagnostic criterion in the Chinese National COVID-19 management guideline. Whether the characteristic findings of Chest CT could differentiate confirmed COVID-19 cases from other positive nucleic acid test (NAT)-negative patients has not been rigorously evaluated. PURPOSE: We aim to test whether chest CT manifestation of 2019 novel coronavirus (COVID-19) can be differentiated by a radiologist or a computer-based CT image analysis system. METHODS: We conducted a retrospective case-control study that included 52 laboratory-confirmed COVID-19 patients and 80 non-COVID-19 viral pneumonia patients between 20 December, 2019 and 10 February, 2020. The chest CT images were evaluated by radiologists in a double blind fashion. A computer-based image analysis system (uAI System, Lianying Inc., Shanghai, China) detected the lesions in 18 lung segments defined by Boyden classification system and calculated the infected volume in each segment. The number and volume of lesions detected by radiologist and computer system was compared with Chi-square test or Mann-Whitney U test as appropriate. RESULTS: The main CT manifestations of COVID-19 were multi-lobar/segmental peripheral ground-glass opacities and patchy air space infiltrates. The case and control groups were similar in demographics, comorbidity, and clinical manifestations. There was no significant difference in eight radiologist identified CT image features between the two groups of patients. There was also no difference in the absolute and relative volume of infected regions in each lung segment. CONCLUSION: We documented the non-differentiating nature of initial chest CT image between COVID-19 and other viral pneumonia with suspected symptoms. Our results do not support CT findings replacing microbiological diagnosis as a critical criterion for COVID-19 diagnosis. Our findings may prompt re-evaluation of isolated patients without laboratory confirmation.
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