| Objective By using the open source medical image processing software 3DSlicer to conduct quantitative analysis of lung density on chest computed tomography(CT)images of COVID-19 patients,and combining with laboratory examination indicators,to identify the correlation between the two and disease risk factors,so as to provide a new idea for clinical imaging diagnosis of lung related diseases.Methods In this study,general clinical data,laboratory indicators and imaging data of patients were collected from the REALONE electronic medical record system of the hospital,and 3DSlicer software was used to quantify the volume of the damaged lung tissue.According to the clinical classification criteria of COVID-19 pneumonia(mild,medium,severe and critical)in the Diagnosis and Treatment Protocol for novel coronavirus infection(trial 10 th edition)released by China,the clinical classification of medium type was included in the medium group,and the clinical classification of severe type and critical type was included in the severe group.The data were analyzed and processed visually by Graphpad Prism(version 8)and SPSS(version 27.0).The relevant data of demographic characteristics,laboratory results and CT quantitative lung density were compared between the two groups.For numerical variables,normality test was conducted first.All groups did not meet normal distribution.Median(interquartile spacing)was used for statistical description,and non-parametric test(Mann-whitney test)was used for comparison between groups.Categorical variables were described in the form of case number(percentage),and comparison between groups was performed by chisquare test or Fisher exact probability method.Then binary logistic linear regression was used to screen the risk factors for disease progression.P<0.05 were considered statistically significant.Results In this study,75 patients with COVID-19 pneumonia confirmed by RT-PCR laboratory in the First Affiliated Hospital of Guangzhou Medical University from March 2020 to January 2023 were included,including 55 in the medium group and 20 in the severe group.1.Comparison results of general clinical data(1)There was no significant difference in incidence between men and women(P > 0.05);(2)The median age of medium patients was 70,and that of severe patients was 77.5,with statistically significant difference between ages(P < 0.05),and was positively correlated with the proportion of damaged lung volume(%)(r=0.2382,P < 0.05).(3)Among the basic diseases,the proportion of hypertension was the highest,followed by diabetes.Patients with no basic diseases were mainly concentrated in the medium group,and patients in the severe group had basic medical history.Patients with hypertension and diabetes were distributed in both the medium and severe groups,but there was no statistical difference in the basic diseases between the two groups(P > 0.05).(4)All the death patients were accompanied by hypertension and diabetes,and 89% of the death patients were distributed in the severe group.The higher the infection rate,the greater the possibility of death(P < 0.05).(5)There were statistically significant differences in different oxygen delivery modes among different groups(P < 0.05).2.Comparison of laboratory results(1)The leukocyte,neutrophil count and D-dimer values in the severe group were higher than those in the medium group,and the leukocyte,neutrophil count and D-dimer levels were statistically different between the two groups(P < 0.05).The number of leukocytes,neutrophils and D-dimer were positively correlated with the volume of damaged lung(%)(r=0.4434/0.4740/0.5425,P < 0.01).(2)The number of lymphocytes in the severe group was significantly lower than that in the medium group,and there was a statistically significant difference between the two groups(P < 0.05),which was negatively correlated with the damaged lung volume(%)(r=-0.3989,P < 0.01).(3)There were no significant differences in monocyte number,IL-6 and IL-8 between the two groups(P > 0.05).3.Comparison of lung density results with quantitative CT Both lung volumes were larger in the moderate group than in the severe group,and there was a statistically significant difference between the two groups(P<0.01),There was a negative correlation with damaged lung volume(%)(r=-0.6941,P <0.01).The basic manifestations of chest CT imaging in patients with moderate COVID-19 are ground-glass shadows,while the pulmonary lesions in severe patients are often groundglass shadows with solid shadows(P < 0.01).4.Multivariate binary logistic regression analysis of progression Multivariate binary logistic regression analysis of disease progression: IL-6 and D-dimer were risk factors for disease progression(OR=1.015/0.999,P < 0.05).Conclusion The degree of lung tissue damage in COVID-19 pneumonia is correlated with the number of leukocytes,neutrophils,lymphocytes and D-dimer,which are risk factors for the progression of lung tissue damage.Using 3DSlicer to quantify lung density can evaluate and predict the disease severity of patients. |
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