Computed tomography scan in COVID-19: a systematic review and meta-analysis

Area of Science:

• Radiology and Imaging
• Infectious Diseases
• Pulmonology

Background:

• Computed tomography (CT) scans are increasingly utilized for diagnosing coronavirus disease 2019 (COVID-19).
• CT imaging offers an alternative diagnostic tool due to limitations associated with reverse transcription-polymerase chain reaction (RT-PCR).
• There is a growing need to understand the specific CT scan features indicative of COVID-19.

Purpose of the Study:

• To systematically review and meta-analyze available data on the computed tomography (CT) scan features of COVID-19.
• To summarize the prevalence of various CT findings in patients diagnosed with COVID-19.
• To compare CT features of COVID-19 with other types of pneumonia.

Main Methods:

• A systematic search of electronic databases was performed for studies published between December 1, 2019, and April 4, 2020.
• Included studies investigated CT features in patients with COVID-19, encompassing both preprint and peer-reviewed articles.
• Pooled prevalence of proportional data was calculated using Freeman-Tukey double arcsine transformation with 95% confidence intervals.

Main Results:

• Eighty-six studies involving 7956 patients were included in the meta-analysis.
• Common CT findings included bilateral involvement (78%), multi-lobar involvement (75%), ground-glass opacities (GGO) (73%), and peripheral distribution (69%).
• Severe COVID-19 cases showed higher rates of pleural effusion and consolidation; CT findings differed between COVID-19 and non-COVID-19 pneumonia.

Conclusions:

• COVID-19 shares some CT features with other viral pneumonias, primarily GGO, but presents differences.
• Consolidation and pleural effusion on CT scans are associated with more severe COVID-19 disease.
• CT imaging characteristics vary by age, disease severity, and patient outcomes within the COVID-19 cohort.