能谱CT参数对纯磨玻璃结节肺腺癌浸润程度的预测价值OA北大核心CSTPCD

Objective:To investigate the value of qualitative and quantitative parameters of spectral CT for predicting the invasiveness of lung adenocarcinoma presenting as pure ground glass nodules(pGGN).Methods:This study enrolled 79 patients with lung adenocarcinoma with pGGNs confirmed by surgical pathology from November 2019 to June 2023.Clinical and imaging data were analyzed retrospectively.A total of 79 pGGNs were classified into non-infiltrating group(Group A)and infiltrating group(Group B).Morphological signs included the presence of lobulation,spiculation,bubblelike lucency,air bronchogram,pleu-ral indentation and abnormal vascular architecture.Quantitative parameters included were nodule size,the slope of the spectral curve,iodine concentration,normalized iodine concentration and water content.The difference of each parameter between group A and group B was performed using the chi-square test and independent samples t-test.Multifactorial logistic regression and ROC curves were performed to evaluate the predictive efficacy of each parameter on the degree of pGGN infiltration.The dif-ference between the efficacies was compared using the Delong test.Results:The presence of pleural retraction and abnormal vascular architecture in pGGNs were more inclined to infiltrate.The performances of the slope of spectral curve,iodine con-centration and normalized iodine concentration were not statistically significant between the two groups.While nodule size and water content of both arterial and venous phases of group B were larger than those of group A(P<0.05).The multifactorial lo-gistic regression showed that nodule size and water content of both arterial and venous phases in pGGNs were independent predictors of the degree of lung adenocarcinoma infiltration.ROC curve showed that water content of both arterial and venous phases and nodule size in pGGNs had a similar effect in predicting the degree of lung adenocarcinoma infiltration(P>0.05).The combination of the above three parameters in pGGNs could improve the predictive efficacy(AUC=0.866,95%CI 0.770～0.932,P<0.05).Conclusion:The combination of water content and nodule size of pGGN measured by spectroscopic CT,has good predictive efficacy for the degree of lung adenocarcinoma infiltration,which is helpful for clinical treatment decision-making.