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Acta Radiol
. 2021 Feb 25;284185121992655.
doi: 10.1177/0284185121992655. Online ahead of print.
CT findings and dynamic imaging changes of COVID-19 in 2908 patients: a systematic review and meta-analysis
Xiuxiu Zhou 1 , Yu Pu 1 , Di Zhang 1 , Yi Xia 1 , Yu Guan 1 , Shiyuan Liu 1 , Li Fan 1
Affiliations
- PMID: 33631941
- DOI: 10.1177/0284185121992655
Abstract
Quick screening patients with COVID-19 is the most important way of controlling transmission by isolation and medical treatment. Chest computed tomography (CT) has been widely used during the initial screening process, including pneumonia diagnosis, severity assessment, and differential diagnosis of COVID-19. The course of COVID-19 changes rapidly. Serial CT imaging could observe the distribution, density, and range of lesions dynamically, monitor the changes, and then guide towards appropriate treatment. The aim of the review was to explore the chest CT findings and dynamic CT changes of COVID-19 using systematic evaluation methods, instructing the clinical imaging diagnosis. A systematic literature search was performed. The quality of included literature was evaluated with a quality assessment tool, followed by data extraction and meta-analysis. Homogeneity and publishing bias were analyzed. A total of 109 articles were included, involving 2908 adults with COVID-19. The lesions often occurred in bilateral lungs (74%) and were multifocal (77%) with subpleural distribution (81%). Lesions often showed ground-glass opacity (GGO) (68%), followed by GGO with consolidation (48%). The thickening of small vessels (70%) and thickening of intralobular septum (53%) were also common. The dynamic changes of chest CT manifestations showed that lesions were absorbed and improved gradually after reaching the peak (80%), had progressive deterioration (55%), were absorbed and improved gradually (46%), fluctuated (22%), or remained stable (26%). The review showed the common and key CT features and the dynamic imaging change patterns of COVID-19, helping with timely management during COVID-19 pandemic.
Keywords: 2019 novel coronavirus disease; X-ray computed tomography; dynamic change; meta-analysis; retrospective study.