Your browser doesn't support javascript.
[Dynamic changes of chest CT imaging in patients with COVID-19]
Non-conventional in Chinese | WHO COVID | ID: covidwho-234346
ABSTRACT

OBJECTIVE:

To analyze the dynamic changes of chest CT images of patients with coronavirus disease 2019 (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.
Search on Google
Collection: Databases of international organizations Database: WHO COVID Type of study: Prognostic study Language: Chinese Document Type: Non-conventional

Similar

MEDLINE

...
LILACS

LIS

Search on Google
Collection: Databases of international organizations Database: WHO COVID Type of study: Prognostic study Language: Chinese Document Type: Non-conventional