Quantitative computed tomography analysis for stratifying the severity of Coronavirus Disease 2019

To examine the feasibility of using a computer tool for stratifying the severity of Coronavirus Disease 2019(COVID-19)based on computed tomography(CT)images.We retrospectively examined 44 confirmed COVID-19 cases.All cases were evaluated separately by radiologists(visually)and through an in-house computer software.The degree of lesions was visually scored by the radiologist,as follows,for each of the 5 lung lobes:0,no lesion present;1,<1/3 involvement;2,>1/3 and<2/3 involvement;and 3,>2/3 involvement.Lesion density was assessed based on the proportion of ground-glass opacity(GGO),consolidation and fibrosis of the lesions.The parameters obtained using the computer tool included lung volume(mL),lesion volume(mL),lesion percentage(%),and mean lesion density(HU)of the whole lung,right lung,left lung,and each lobe.The scores obtained by the radiologists and quantitative results generated by the computer software were tested for correlation.A Chi-square test was used to test the consistency of radiologist-and computer-derived lesion percentage in the right/left lung,upper/lower lobe,and each of the 5 lobes.The results showed a strong to moderate correlation between lesion percentage scores obtained by radiologists and the computer software(r ranged from 0.7679 to 0.8373,P<0.05),and a moderate correlation between the proportion of GGO and mean lesion density(r=-0.5894,P<0.05),and proportion of consolidation and mean lesion density(r=0.6282,P<0.05).Computer-aided quantification showed a statistical significant higher lesion percentage for lower lobes than that assessed by the radiologists(x^2=8.160,P=0.004).Our experiments demonstrated that the computer tool could reliably and accurately assess the severity and distribution of pneumonia on CT scans.