Objectives To characterize and interpret the CT imaging signs of the 2019 novel coronavirus (COVID-19) pneumonia in China. Materials and methods The CT images of 130 patients diagnosed as COVID-19 pneumonia from several hospitals in China were collected and their imaging features were analyzed and interpreted in detail.

Background This multiple-center retrospective study aimed to investigate computed tomography (CT) imaging findings in 72 patients with airway-invasive pulmonary aspergillosis. Material/Methods Seventy-two patients with airway-invasive pulmonary aspergillosis confirmed by pathology results were divided into 3 types according to image characteristics. Type I involved the trachea or the main bronchus. Type II involved the lobular and segmental bronchi, which manifested early as bronchial wall thickening, and later development was divided into types IIa and IIb. Type IIa manifested as bronchiectasis, and type IIb manifested as consolidation around the bronchus. Type III involved the bronchioles and pulmonary parenchyma, with tree-in-bud sign and acinar nodules around. CT signs of the various types and their differentiation were investigated. Results The main clinical manifestations of the 72 patients with airway-invasive pulmonary aspergillosis were shortness of breath (55/72, 76.4%), cough (40/72, 55.6%), expectoration (35/72, 48.6%), dyspnea (8/72, 11.1%), weight loss (2/72, 2.8%), and fever (30/72, 41.7%). CT typing identified 3 types: 2 patients (2.8%) had type I, presenting as thickening of trachea or main bronchial walls; 3 patients (4.2%) had early type II, manifesting as thickening of lobular or segmental bronchial walls; 27 patients (37.5%) developed type IIa, manifesting as bronchiectasis; 22 patients (30.6%) had type IIb, manifesting as consolidation around the bronchus; and 18 patients (25.0%) had type III, presenting as nodules and patchy shadows with small cavities in the periphery of the lung. Conclusions Airway pulmonary aspergillosis has characteristic imaging findings, which can help early clinical diagnosis through classification according to CT imaging characteristics.