Objective To observe the value of intratumoral and peritumoral radiomics models combined with clinical and routine CT features for differentiating adenocarcinoma in situ(AIS)and microinvasive adenocarcinoma(MIA)of lung.Methods Totally 180 patients with isolated AIS and 180 with isolated MIA were retrospectively included,among them 160 AIS cases and 160 MIA cases were randomly selected into training set(n=320),while the other 20 AIS cases and 20 MIA cases were selected into test set(n=40).In training set,clinical and conventional CT features being statistically different between AIS and MIA were obtained to construct clinical model.Besides,radiomics features were extracted from intratumoral(CTi)ROI,intra-and peritumoral 2 mm(CTi+p2mm)ROI and intra-and peritumoral 4 mm(CTi+p4mm)ROI,and then CTi model,CTi+p2mm model and CTi+p4mm model for differentiating MIA and AIS were constructed.The optimal radiomics model for predicting MIA was selected using the area under the curve(AUC)of receiver operating characteristic(ROC)curve,and a combined model was built based on the optimal radiomics model combining with clinical and conventional CT features.The AUC,calibration and net benefit of the clinical model,the optimal radiomics model and the combined model were assessed.Results In training set,the larger nodular diameter,higher percentage of inhomogeneous density and ratio of nodules with vascular signals were observed in MIA compared with those in AIS(all P＜0.05).In test set,CTi+p2mm model had the highest efficacy(AUC=0.838)for differentiating MIA from AIS(P＜0.05),and the combined model had better efficacy(AUC=0.867,P＜0.05).The calibration of combined model was good,and the net benefit was high in 0.60-0.90 threshold probability range.Conclusion The radiomics model constructed with intratumoral and peritumoral 2 mm ROI based on plain CT was effective for differentiating MIA from AIS.Combining with clinical and routine CT features could furtherly improve differential diagnostic efficacy.