Objective To analyze the imaging features of solitary pulmonary nodules ( SPNs) , and compare the two types of lung cancer prediction models in distinguishing malignancy of SPNs.
Methods A retrospective study was performed on the patients admitted to Ruijin Hospital between 2002 and 2009 with newly discovered SPNs. The patients all received pathological diagnosis. The clinical and imaging characteristics were analyzed. Then the diagnostic accuracy of two lung cancer prediction models for distinguishing malignancy of SPNs was evaluated and compared.
Results A total of 90 patients were enrolled, of which 32 cases were with benign SPNs, 58 cases were with malignant SPNs. The SPNs could be identified between benign and maligant by the SPN edge features of lobulation ( P lt;0. 05) . The area under ROC curve of VA model was 0. 712 ( 95% CI 0. 606 to 0. 821) . The area under ROC curve of Mayo Clinic model was 0. 753 ( 95% CI 0. 652 to 0. 843) , which was superior to VA model.
Conclusions It is meaningful for the identification of benign and maligant SPNs by the obulation sign in CT scan. We can integrate the clinical features and the lung cancer predicting models to guide clinical work.
Citation： OU Zhaorong,TAO Lianqin,SHI Guochao,WAN Huanying. Radiological Features of Solitary Pulmonary Nodules and Diagnostic Value of Two Lung CancerPrediction Models for Distinguishing Malignancy. Chinese Journal of Respiratory and Critical Care Medicine, 2012, 11(2): 168-171. doi: Copy