Quantification of CT images in 83 cases of COVID-19
LIN Chunmiao*, QIN Tong, LU Yuyang, YU Lexi
*Departments of Radiology, Zhejiang Provincial People's Hospital（Affiliated People's Hospital,Hangzhou Medical College）, Hangzhou, Zhejiang 310014, China
Abstract：Objective To quantitatively analyze the chest computerized tomography ( CT ) images of coronavirus disease 2019 ( COVID-19 ) cases by automatic artificial intelligence ( AI ) system, so as to provide the basis for the prediction of severe cases and early clinical intervention. Methods Eighty-three confirmed cases of COVID-19 from January 23 to February 14, 2020 in Wuchang Hospital of Wuhan were selected and the clinical data were collected. According to the diagnosis and treatment Plan of COVID-19 (seventh trial), the patients were divided into an ordinary group and a severe group. The parameters of chest CT images were quantified by the automatic AI system, and the CT imaging features of two groups were compared. Results There were 46 cases in the ordinary group and 37 cases in the severe group, with the age of ( 62.68 ±13.69 ) years and ( 50.52 ±12.45 ) years, respectively. The percentages of total pulmonary lesions, the lesion volume of bilateral lungs, the lesion volume of right lower lung, the left lung volume and the right lung volume from -300 to -200 Hu [median (inter-quartile range)] were 19.80% ( 21.69% ), 622.87 ( 1 145.73 ) cm3, 205.73 ( 246.95 ) cm3, 26.50 (21.20) cm3 and 38.02 (48.78) cm3 in the severe group, which were significantly different from 9.78% ( 13.24% ), 333.55 ( 401.77 ) cm3, 126.02 (164.21) cm3, 21.43 (13.11) cm3 and 26.92 ( 18.04 ) cm3 in the ordinary group ( P<0.05 ). The volume of pulmonary lesions reached the peak from 10 to 16 days after infection. Conclusion The lung lesions in severe cases of COVID-19 are large, especially in the right lower lung, and need to be closely monitored from 10 to 16 days after infection for early warning of severe cases.
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