Dynamic changes of chest CT imaging in patients with corona virus disease-19 (COVID-19).
- Author:
Jincheng WANG
1
;
Jinpeng LIU
1
;
Yuanyuan WANG
1
;
Wei LIU
1
;
Xiaoqun CHEN
1
;
Chao SUN
1
;
Xiaoyong SHEN
1
;
Qidong WANG
1
;
Yaping WU
1
;
Wenjie LIANG
1
;
Lingxiang RUAN
1
Author Information
1. Radiology Department, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
- Publication Type:Journal Article
- From:
Journal of Zhejiang University. Medical sciences
2020;49(1):0-0
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVE:To analyze the dynamic changes of chest CT images of patients with corona virus disease-19 (COVID-19).
METHODS:Fifty-two cases of COVID-19 were admitted in the First Affiliated Hospital of Zhejiang University School of Medicine. The consecutive chest CT scans were followed up for all patients with an average of 4 scans performed per patient during the hospitalization. The shortest interval between each scan was 2 days and the longest was 7 days. The shape, number and distribution of lung shadows, as well as the characteristics of the lesions on the CT images were reviewed.
RESULTS:The obvious shadows infiltrating the lungs were shown on CT images in 50 cases, for other 2 cases there was no abnormal changes in the lungs during the first CT examination. Ground-glass opacities (GGO) were found in 48 cases (92.3%), and 19 cases (36.5%) had patchy consolidation and sub-consolidation, which were accompanied with air bronchi sign in 17 cases (32.7%). Forty one cases (78.8%) showed a thickened leaflet interval, 4 cases (7.6%) had a small number of fibrous stripes. During hospitalization, GGO lesions in COVID-19 patients gradually became rare, the fibrous strip shadows increased and it became the most common imaging manifestation. The lesions rapidly progressed in 39 cases (75.0%) within 6-9 days after admission. On days 10-14 of admission, the lesions distinctly resolved in 40 cases (76.9%).
CONCLUSIONS:The chest CT images of patients with COVID-19 have certain characteristics with dynamic changes, which are of value for monitoring disease progress and clinical treatment.
