RT Journal Article SR Electronic T1 Dynamic PET 18F-FDG Studies in Patients with Primary and Recurrent Soft-Tissue Sarcomas: Impact on Diagnosis and Correlation with Grading JF Journal of Nuclear Medicine JO J Nucl Med FD Society of Nuclear Medicine SP 713 OP 720 VO 42 IS 5 A1 Antonia Dimitrakopoulou-Strauss A1 Ludwig G. Strauss A1 Matthias Schwarzbach A1 Cyrill Burger A1 Thomas Heichel A1 Frank Willeke A1 Gunhild Mechtersheimer A1 Thomas Lehnert YR 2001 UL http://jnm.snmjournals.org/content/42/5/713.abstract AB The purpose of this study was to evaluate 18F-FDG PET studies of primary and recurrent sarcomas for diagnosis and correlation with grading. Methods: The evaluation included 56 patients, 43 with histologically proven malignancies and 13 with benign lesions. Seventeen patients were referred with suspicion on a primary tumor, and the remaining 39 were referred with suspicion on a recurrent tumor. The FDG studies were accomplished as a dynamic series for 60 min. The evaluation of the FDG kinetics was performed using the following parameters: standardized uptake value (SUV), global influx, computation of the transport constants K1–k4 with consideration of the distribution volume (VB) according to a two-tissue-compartment model, and fractal dimension based on the box-counting procedure (parameter for the inhomogeneity of the tumors). Results: Visual evaluation revealed a sensitivity of 76.2%, a specificity of 42.9%, and an accuracy of 67.9%. The vascular fraction VB and the SUV were higher in malignant tumors compared with benign lesions (t test, P < 0.05). Although the FDG SUV helped to distinguish benign and malignant tumors, there was some overlap, which limited the diagnostic accuracy. The SUV and fractal dimension accounted for significant differences in six of the nine diagnostic pairs. Whereas grade (G) II and G III tumors were differentiated from lipomas on the basis of the fractal dimension and some other kinetic parameters, no differences were found between G I tumors and lipomas. On the basis of the discriminant analysis, the differentiation of soft-tissue tumors was best for the use of six parameters of the FDG kinetics (SUV, VB, K1, k3, influx, and fractal dimension). Eighty-four percent of G III tumors, 37.5% of G II tumors, 80% of G I tumors, 50% of lipomas, and 14.3% of scars could be classified correctly, whereas inflammatory lesions were misclassified. Conclusion: FDG PET should be used preferentially for monitoring patients with G III sarcomas. Visual analysis provides a low specificity. In contrast, the evaluation of the full FDG kinetics provides superior information, particularly for the discrimination of G I and G III tumors (positive predictive value, >80%).