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    ABSTRACT: To study the clinical value of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) in the diagnosis and staging of lung cancer. Ninety-four patients with lung nodular changes were examined by CT, 18F-FDG PET and pathology, cytology. 18F-FDG PET images were analyzed by semi-quantitative standard uptake value (SUV) only and (or) SUV plus visual observation. Focuses with a SUV > 2.5 were judged as malignant changes, while SUV < or = 2.5 was judged as benign. SUV plus visual analysis, based on the focal SUV, the nodular size and shape, and clinical data, was carried out by two nuclear doctors. CT imaging was interpreted by two radiological doctors. The sensitivity, specificity, accuracy, positive predictive and negative predictive values of 18F-FDG PET and CT in the diagnosis, and in the evaluation of lymphatic metastasis and remote metastasis of lung lesions were calculated. The diagnostic efficiency of the two methods (SUV or visual plus SUV method) was compared. (1) 58 cases were confirmed to be malignant by surgery or pathological examination, while 36 cases were proved benign by pathology or empirical therapy. (2) The sensitivity, specificity, accuracy, positive and negative predictive values were 69%, 65%, 68%, 82% and 49% respectively for CT; and 91%, 89%, 90%, 93% and 87% respectively for SUV analysis; and 95%, 94%, 95%, 97% and 92% respectively for visual plus SUV methods. (3) Among 34 patients with mediastinal lymph node involvement confirmed by pathology, 18F-FDG PET detected 30 cases, while CT detected only 18 cases (P < 0.01). (4) 18F-FDG PET revealed 19 cases with distant metastases, while CT only discovered 8 cases with distant metastases. As a result, the therapy was modified by PET examination in 14 patients. 18F-FDG PET imaging is of important clinical value in the diagnosis of lung lesions and the staging of malignancy.
    No preview · Article · Mar 2005 · Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases