Article ; Online: Use of radiographic features in COVID-19 diagnosis: Challenges and perspectives.
Journal of the Chinese Medical Association : JCMA
2020 Volume 83, Issue 7, Page(s) 644–647
Abstract: ... we will discuss the challenges and the future perspectives of using radiographic modalities for COVID-19 diagnosis ... with specific pathologic features for staging and treatment arrangement. Although the radiographic imaging is ... The rapid surge and wide spread of the coronavirus disease-2019 (COVID-19) overshadows the entire ...
| Abstract | The rapid surge and wide spread of the coronavirus disease-2019 (COVID-19) overshadows the entire medical industries worldwide. The stringent medical resources hinder the diagnostic capacity globally, while 84 000 of new cases confirmed within a single day of April 14, 2020. Real-time reverse-transcription polymerase chain reaction (RT-PCR) with is the current first-line diagnosis, but the false-negative rate remains concerned. Radiographic technologies and tools, including computed tomography (CT) and chest X-ray, were applied for initial screening and follow-up, from which the tools provide detail diagnosis with specific pathologic features for staging and treatment arrangement. Although the radiographic imaging is found less sensitive, numerous CT-positive patients were not screened out by RT-PCR initially and later confirmed as COVID-19 positive. Besides, the shortage of sampling kits and the longer turn-over time of PCR examinations in some areas were noticed due to logistic issues and healthcare burden. In this review, we will discuss the challenges and the future perspectives of using radiographic modalities for COVID-19 diagnosis in view of securing human lives amid the crisis. |
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| MeSH term(s) | Betacoronavirus ; COVID-19 ; Coronavirus Infections/diagnostic imaging ; Humans ; Pandemics ; Pneumonia, Viral/diagnostic imaging ; SARS-CoV-2 ; Tomography, X-Ray Computed |
| Keywords | covid19 |
| Language | English |
| Publishing date | 2020-06-08 |
| Publishing country | Netherlands |
| Document type | Journal Article ; Research Support, Non-U.S. Gov't ; Review |
| ZDB-ID | 2107283-8 |
| ISSN | 1728-7731 ; 1726-4901 |
| ISSN (online) | 1728-7731 |
| ISSN | 1726-4901 |
| DOI | 10.1097/JCMA.0000000000000336 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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