Impact of dynamic 18F-FDG PET on the early prediction of therapy outcome in patients with high-risk soft-tissue sarcomasa after neoadjuvant chemotherapy: a feasibility study - Dimitrakopoulou-Strauss, Antonia; Strauss, Ludwig G.; Egerer, Gerlinde; Vasamiliette, Julie Sigrid Lucienne; Mechtersheimer, Gunhild; Schmitt, Thomas; Lehner, Burkhard; Haberkorn, Uwe; Ströbel, Philipp; Kasper, Bernd (Journal of nuclear medicine, 2010)
Dynamic PET (dPET) studies with 18F-FDG were performed in patients with soft-tissue sarcomas who received neoadjuvant chemotherapy early in the course of therapy. The goal of the study was to evaluate the impact of early dPET studies and assess their value with regard to the therapy outcome using histopathologic data. Methods: The evaluation included 31 patients with nonmetastatic soft-tissue sarcomas, who were treated with neoadjuvant chemotherapy consisting of etoposide, ifosfamide, and doxorubicin. Patients were examined before the onset of therapy and after the completion of the second cycle. Histopathologic response served for reference and was available for 25 of 31 patients. Response was defined as less than 10% viable tumor tissue in the resected tumor tissue. The following parameters were retrieved from dPET studies: standardized uptake value (SUV); fractal dimension; 2-compartment model with computation of K1, k2, k3, and k4 (unit, 1/min); fractional blood volume; and influx according to Patlak. Results: The mean SUV was 4.6 before therapy and 2.8 after 2 cycles. The mean influx was 0.059 before therapy and 0.043 after 2 cycles. The mean SUV was 3.9 in the responders and 5.5 in the nonresponders before therapy. After therapy, responders revealed a mean SUV of 2.5, whereas nonresponders had a mean SUV of 3.5. We used linear discriminant analysis to categorize the patients into 2 groups: response (n = 12) and nonresponse (n = 13). The correct classification rate of the responders (positive predictive value) was generally higher (>67%) than that for the nonresponders. Finally, the combined use of the 2 predictor variables, namely SUV and influx, of each study led to the highest accuracy of 83%. This combination was particularly useful for the prediction of responders (positive predictive value, 92%). The use of the percentage change in maximum SUV led to an accuracy of 58%. Conclusion: On the basis of these results, only a multiparameter analysis based on kinetic 18F-FDG data of a baseline study and after 2 cycles is helpful for the early prediction of chemosensitivity in patients with soft-tissue sarcomas receiving neoadjuvant chemotherapy.
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