RESUMEN
BACKGROUND: Patients with primary malignant disease undergoing oncological surveillance, upon completion of their treatment, are a unique population that is gradually growing. Therefore, the number of patients with a pulmonary nodule and a previous malignant disease has increased over recent years. In order to select appropriate management for these patients, a few questions should be answered: Is it a malignant lesion? Secondly, is it primary or metastatic? Is it the only one? In the past, several imaging and invasive diagnostic procedures were used to clarify theses uncertainties. However, in many cases the results were equivocal and it was difficult to establish treatment policy. In recent years PET/CT-FDG was found to be specific, sensitive and accurate in the evaluation and staging of patients with primary malignant disease. In this study we analyzed the accuracy and value of PET/CT-FDG in patients with primary malignant disease and an indeterminate pulmonary nodule. METHODS: Patients with primary malignant disease in the past and undefined pulmonary nodule/s were recruited. Computerized retrospective screening was performed. The specificity, sensitivity, positive and negative predictive value of PET/CT-FDG were calculated. The influence of the PET results on the clinical policy was evaluated. RESULTS: Forty one patients with previous malignant disease entered the study. PET/CT-FDG was positive in 15 cases. In 13 patients (87%) the FDG positive nodule was found to be malignant. In 26 patients the PET/CT was negative. In 19 (73%) diagnosis of non-malignant nodule was confirmed. The positive and negative predictive value of PET/CT-FDG for metastatic disease was 87% and 91% respectively and the accuracy 86%. CONCLUSIONS: The results of the present study demonstrate that PET/CT-FDG is a very valuable tool in the evaluation of patients with previous primary malignant disease and a pulmonary nodule. This imaging technique was able to clarify most of the thoracic surgeon's uncertainties and provided enough data to choose the optimal treatment strategy.