Tools
Tools
Wang, Yuan-Cheng, Luo, Huanyuan, Liu, Songqiao, Huang, Shan, Zhou, Zhen, Yu, Qian, Zhang, Shijun, Zhao, Zhen, Yu, Yizhou, Yang, Yi, Wang, Duolao 
ORCID: https://orcid.org/0000-0003-2788-2464 and Ju, Shenghong
(2020)
'Dynamic evolution of COVID-19 on chest computed tomography: experience from Jiangsu Province of China'. European Radiology, Vol 30, pp. 6194-6203.
|
Text
EURA-D-20-01283_D Wang.pdf - Accepted Version Download (965kB) | Preview |
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 included, and each was assigned to one of the three groups: asymptomatic/mild (n = 63), moderate (n = 378), severe/critically ill (n = 43). Time series showed different evolution patterns of CT measurements in the groups. Following disease onset, posteroinferior subpleural area of the lung was the most common location for pulmonary opacities. Opacity volume continued to increase beyond 15 days in the severe/critically ill group, compared with peaking on days 13–15 in the moderate group. Asymptomatic/mild group had the lowest opacity volume which almost resolved after 15 days. The opacity density began to drop from day 10 to day 12 for moderately ill patients.
Conclusions
Volume, density, and location of the pulmonary opacity and their evolution on CT varied with disease severity in COVID-19. These findings are valuable in understanding the nature of the disease and monitoring the patient’s condition during the course of illness.
| Item Type: | Article |
|---|---|
| Subjects: | WA Public Health > WA 100 General works WA Public Health > WA 105 Epidemiology WC Communicable Diseases > Virus Diseases > Viral Respiratory Tract Infections. Respirovirus Infections > WC 505 Viral respiratory tract infections WN Radiology. Diagnostic imaging > WN 20 Research (General) |
| Faculty: Department: | Clinical Sciences & International Health > Clinical Sciences Department |
| Digital Object Identifer (DOI): | https://doi.org/10.1007/s00330-020-06976-6 |
| Depositing User: | Stacy Murtagh |
| Date Deposited: | 11 Jun 2020 16:02 |
| Last Modified: | 10 Jun 2021 01:02 |
| URI: | https://archive.lstmed.ac.uk/id/eprint/14721 |
Statistics
Actions (login required)
 |
Edit Item |