Dynamic evolution of COVID-19 on chest computed tomography: experience from Jiangsu Province of China.

ABSTRACT:

Objectives

To determine the patterns of chest computed tomography (CT) evolution according to disease severity in a large coronavirus disease 2019 (COVID-19) cohort in Jiangsu Province, China.

Methods

This retrospective cohort study was conducted from January 10, 2020, to February 18, 2020. All patients diagnosed with COVID-19 in Jiangsu Province were included, retrospectively. Quantitative CT measurements of pulmonary opacities including volume, density, and location were extracted by deep learning algorithm. Dynamic evolution of these measurements was investigated from symptom onset (day 1) to beyond day 15. Comparison was made between severity groups.

Results

A total of 484 patients (median age of 47 years, interquartile range 33-57) with 954 CT examinations were i

SUBMITTER: Wang YC 

PROVIDER: S-EPMC7283983 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature