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High Resolution Computed Tomography (HRCT) Pattern characterization in Corona Virus Disease-2019 (COVID-19): A Meta-Analysis

DOI : https://doi.org/10.36349/easms.2020.v03i10.005
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Abstract: Coronavirus disease-2019(COVID-19) pandemic has quickly become an infectious disease of worldwide concern and there exists gaps in the proper understanding of various patterns on HRCT imaging. This meta-analysis aims to summarise the most frequent HRCT patterns in COVID-19 from various published studies to aid the quick diagnosis. We aim to consolidate knowledge from original studies done on COVID-19 patients and characterise the imaging patterns on HRCT for quick diagnosis. This is a Meta-analysis on the various HRCT chest findings of COVID-19.Studies were procured from PubMed and Google Scholar database published between December 2019 and September 2020.The specific demographic and imaging patterns were analysed and pooled to form the meta-analysis using the random effects model and single-arm analysis. Total of 12 studies met the inclusion criteria. Total pooled data consisted of 2787 RT-PCR positive cases. The three CT patterns most characteristic included Ground Glass Opacities (52%), Consolidation (40.4%), Interlobular Septal Thickening (14%). A combination of GGO and consolidation was most prevalent (59%). Other patterns noted included Crazy Paving pattern, Air Bronchogram, Pleural thickening, Pleural effusion, Bronchiectasis and Tree in bud. Most cases were bilateral (79%) and peripheral (77%). Lower lobe involvement: bilateral (66%), RLL (87%), LLL (81%). Upper lobe: Bilateral (61%), RUL (65%), LUL (69%). Right Middle lobe (55%). 25% had pan-lobar involvement. CT pattern recognition in potentially asymptomatic patients can be a diagnostic aid in early diagnosis of COVID-19. Ground glass opacities, consolidation and interlobar septal thickening in bilateral peripheral lungs was the most typical in COVID-19.

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Dr. Afroza Begum

Lecturer, Dept. of Pharmacology and Therapeutics, Shaheed Monsur Ali Medical College & Hospital, Uttara, Dhaka-1230, Bangladesh

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