OBJECTIVE: The aim of this study was to evaluate and compare the ability of C-11-methionine (MET) and F-18 fluoro-deoxy-D-glucose positron emission tomography (FDG-PET) to diagnose lung cancer in patients with pneumoconiosis. METHODS: Twenty-six subjects underwent both whole-body MET-PET and FDG-PET on the same day. The first group was a lung cancer group, which consisted of 15 patients, and included those with pneumoconiosis with increased nodules (13 cases), hemoptysis (1 case), and positive sputum cytology (1 case). The second group was a no-malignancy control group, consisting of 11 patients with pneumoconiosis. RESULTS: Significant correlations between nodule size and the maximum standardized uptake value (SUV(max)) of the two PET tracers were observed in the control group. The larger the nodule size, the greater were the amounts of these tracers accumulated (MET: r = 0.771, P < 0.0001; FDG: r = 0.903, P < 0.0001). The SUV(max) of MET was significantly lower than that of FDG in the pneumoconiotic nodules (P < 0.0001). Lung cancer was found in 5 of 19 nodules (two with adenocarcinoma, one with squamous cell carcinoma, one with small cell carcinoma, and one with large cell carcinoma) in the first group. As for nodules equal to or less than 3 cm in diameter, the SUV(max) of MET was significantly higher in the lung cancer than in the pneumoconiotic nodules, with 3.48 +/- 1.18 (mean +/- SE) for the lung cancer and 1.48 +/- 0.08 for the pneumoconiotic nodules (P < 0.01), similar to the SUV(max) of FDG, with 7.12 +/- 2.36 and 2.85 +/- 0.24 (P < 0.05), respectively. On the basis of the criteria for the control group, FDG and MET identified lung cancer with sensitivities of 60% and 80%, specificities of 100% and 93%, accuracies of 90% and 90%, positive predictive values of 100% and 80%, and negative predictive values of 88% and 93%, respectively. CONCLUSIONS: Our results indicate that nodules with an intense uptake of MET and FDG relative to their size should be carefully observed because of a high risk for lung cancer.
OBJECTIVE: The aim of this study was to evaluate and compare the ability of C-11-methionine (MET) and F-18 fluoro-deoxy-D-glucose positron emission tomography (FDG-PET) to diagnose lung cancer in patients with pneumoconiosis. METHODS: Twenty-six subjects underwent both whole-body MET-PET and FDG-PET on the same day. The first group was a lung cancer group, which consisted of 15 patients, and included those with pneumoconiosis with increased nodules (13 cases), hemoptysis (1 case), and positive sputum cytology (1 case). The second group was a no-malignancy control group, consisting of 11 patients with pneumoconiosis. RESULTS: Significant correlations between nodule size and the maximum standardized uptake value (SUV(max)) of the two PET tracers were observed in the control group. The larger the nodule size, the greater were the amounts of these tracers accumulated (MET: r = 0.771, P < 0.0001; FDG: r = 0.903, P < 0.0001). The SUV(max) of MET was significantly lower than that of FDG in the pneumoconiotic nodules (P < 0.0001). Lung cancer was found in 5 of 19 nodules (two with adenocarcinoma, one with squamous cell carcinoma, one with small cell carcinoma, and one with large cell carcinoma) in the first group. As for nodules equal to or less than 3 cm in diameter, the SUV(max) of MET was significantly higher in the lung cancer than in the pneumoconiotic nodules, with 3.48 +/- 1.18 (mean +/- SE) for the lung cancer and 1.48 +/- 0.08 for the pneumoconiotic nodules (P < 0.01), similar to the SUV(max) of FDG, with 7.12 +/- 2.36 and 2.85 +/- 0.24 (P < 0.05), respectively. On the basis of the criteria for the control group, FDG and MET identified lung cancer with sensitivities of 60% and 80%, specificities of 100% and 93%, accuracies of 90% and 90%, positive predictive values of 100% and 80%, and negative predictive values of 88% and 93%, respectively. CONCLUSIONS: Our results indicate that nodules with an intense uptake of MET and FDG relative to their size should be carefully observed because of a high risk for lung cancer.
Authors: Ken Herrmann; Toshiki Takei; Kakuko Kanegae; Tohru Shiga; Andreas K Buck; Jennifer Altomonte; Markus Schwaiger; Tibor Schuster; Kenichi Nishijima; Yuji Kuge; Nagara Tamaki Journal: Mol Imaging Biol Date: 2009-04-02 Impact factor: 3.488