Objective To analyze the initial clinical features and imaging finding of corona virus disease 2019 (COVID-19).

Methods The clinical data of 46 patients with COVID-19 were retrospectively analyzed.The thin-slice CT scan in all cases were performed to analyze the number of pulmonary segments and lobes, distribution and signs of lesion involvement.According to the time interval between the first symptom and CT examination, the course of disease was divided into the early stage(18 cases, ≤ 3d), middle stage(14 cases, 4-7d) and advanced stage (14 cases, >7d), and the imaging findings were analyzed.

Results Among 46 cases with COVID-19, the history of direct or indirect exposure to Wuhan in 45 cases(97.8%) were identified, and the most common clinical symptoms were cough(28/46, 68.6%) and fever (40/46, 87.0%).In terms of clinical symptoms, the lesions were mainly distributed in bilateral lungs(39/46, 84.8%), the diffused distribution was main, and the number of involved lung segments was more than 7(27/46, 58.7%).The thin-section CT images were mainly characterized by pure ground grass opacity (23/46, 50.0%), ground grass opacity complicated with glass grinding consolidation(32/46, 69.6%), paving stone sign(41/46, 89.1%), vascular thickening(41/46, 89.1%), halo sign(34/46, 73.9%) and air bronchogram(38/46, 82.6%).In the early stage of disease, the patients with pure ground grass opacity were more common compared with patients at the middle or late stage of disease.The signs of consolidation in the advanced patients were more common compared with patients at the early and middle stages of disease, and the proportion of the involve lung segment more than 7 in the advanced patients was higher than that in the early and middle stages of disease.

Conclusions The clinical and imaging signs of COVID-19 patients are complex and changeable, but which has the certain characteristics, and the CT signs have a certain evolution law.The CT examination combined with clinical symptoms has important clinical significance and value in the early diagnosis of COVID-19.