Differential Diagnosis Of Focal Organizing Pneumonia And Small Peripheral Lung Carcinoma By CT Combined With Circulating Tumor Cell

Objective:To investigate the value of CT imaging features of combined circulating tumor cells(CTCs)in the differential diagnosis of focal organizing pneumonia(FOP)and small peripheral lung carcinoma(SPLC).Methods:The clinical and CT imaging data of 22 FOP patients(FOP group)and 40 SPLC patients(SPLC group)confirmed by routine pathology after operation were retrospectively analyzed.Circulating tumor cells were detected in all patients before operation.Logistic regression and regression model were established for the statistically significant indexes between the two groups.Receiver Operating Characteristic Curve(ROC)was drawn,and Area Under Curve(AUC)of each index was compared to compare the diagnostic efficacy of each index.Results:There were significant differences between FOP group and SPLC group in the age of illness,the increase of venous CT value,the enhancement rate of venous CT value and CTCs value(p<0.05).The difference between the two groups:in CT imaging showed burr sign and spinous process sign was statistically significant(P<0.05).There was no significant difference between the two groups in sex,lesion edge,lobulation sign,vascular bundle sign,bronchial inflation sign,pleural traction sign,lesion location,average CT value of plain scan and average CT value of venous phase(P>0.05).According to the above results,logistic regression analysis was carried out on age,burr,spinous process,CT enhancement rate in venous phase,and CT enhancement amount in venous phase and CTCs index.A regression model Y=1/[1+e-(0207+0.055X1-0.926X2-1.401X3-0.114X4-0.125X5+0.441X6)]was established.According to Y,ROC curve was drawn,AUC was 0.927,which was higher than any other single index.Conclusion:Age,CT manifestations of burr sign,spinous process sign,increase of CT value in venous phase,increase rate of CT value in venous phase,CTCs have certain reference value in differential diagnosis of SPLC and FOP.The comprehensive application of logistic regression and ROC curve analysis can improve the efficiency of identification.