Objective To explore the application value of high-resolution computed tomography(HRCT)quantitative parameters combined with vascular classification in evaluating the invasiveness of lung adenocarcinoma.Methods 113 patients with lung adenocarcinoma(a total of 138 nodules)confirmed by surgical pathology from March 2021 to June 2023 in our hospital were selected and divided into a non-invasive group of 81 patients(atypical adenoma hyperplasia/adenocar-cinoma in situ/microinvasive adenocarcinoma)and 57 in the invasive group(invasive adenocarcinoma)according to the pathological type.The clinical data,HRCT quantitative parameters and nodule vascular classification of the two groups were compared,a Logistic regression model was constructed,and the receiver operating characteristic(ROC)curve was used to evaluate the value of HRCT quantitative parameters combined with vascular classification in predicting invasive lung adeno-carcinoma.Results The maximum diameter of nodules,average CT value of ground glass component,CT difference value,volume,mass,and the proportion of blood vessel classification of type Ⅲ/Ⅳ in the invasive group were all greater than those in the non-invasive group(P＜0.05).Multivariate Logistic regression analysis showed that the maximum diameter of the nodule,average CT value of ground glass component,CT difference value,volume,mass,and blood vessel type were inde-pendent risk factors for invasive lung adenocarcinoma(P＜0.05).The results of the ROC curve analysis showed that the maximum diameter of the nodule,the average CT value of the ground glass component,the CT difference value,the volume,the mass,the blood vessel classification,and the areas under the curve of combined detection to evaluate invasive lung ade-nocarcinoma were 0.619,0.669,0.753,0.747,0.728,0.799,0.861,respectively.The evaluation value of HRCT quantita-tive parameters combined with vascular classification was higher than that of a single indicator.Conclusion The com-bined detection of HRCT quantitative parameters and vascular classification has good predictive performance for invasive lung adenocarcinoma and has clinical application value in patients with lung adenocarcinoma.
High-resolution computed tomographyVascular classificationLung adenocarcinomaInvasivenessApplication value
维普
万方数据
