Date: 25 Mar 2010

Prediction of chemotherapy outcome in patients with metastatic soft tissue sarcomas based on dynamic FDG PET (dPET) and a multiparameter analysis

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Abstract

Purpose

Dynamic PET studies with 18F-FDG were performed in patients with metastatic soft tissue sarcomas who received conventional chemotherapy with doxorubicin hydrochloride (Adriamycin) and ifosfamide (AI-G). The goal of the study was to evaluate the impact of full kinetic analysis and assess its value with regard to the therapy outcome based on survival data.

Methods

The evaluation included 17 patients with 29 metastatic lesions of soft tissue sarcomas, who were treated with chemotherapy consisting of an AI-G regimen prior to high-dose chemotherapy and peripheral blood stem cell transplantation where applicable. Patients were examined prior to onset of therapy and after completion of the first cycle of AI-G. Restaging data (n = 17) based on Response Evaluation Criteria in Solid Tumors were available. Survival data (n = 14) served for reference. The following parameters were retrieved from the dynamic PET studies: standardized uptake value (SUV), fractal dimension, two-compartment model with computation of k1, k2, k3, k4 (unit: 1/min), the fractional blood volume and the FDG influx calculated according to Patlak.

Results

The mean SUV was 6.9 prior to therapy and 4.7 after one cycle. The mean influx was 0.066 prior to therapy in comparison to 0.058 after one cycle. We dichotomized the patients according to the median survival time of 320 days into response (n = 6) and non-response (n = 8). The mean SUV was 7.6 in the group of responders and 5.4 in the group of non-responders prior to therapy. Responders revealed a mean SUV of 3.8 after therapy as compared to 5.0 SUV for non-responders. We used discriminant analysis to classify the patients into the two response groups. The classification of the non-responders was generally higher (negative predictive value > 61%) than for the responders. Finally, the combined use of the four predictor variables, namely mean SUV and k1 of both studies led to the highest accuracy of 90% for both groups.

Conclusion

The data demonstrate that only a multiparameter analysis based on a combination of the absolute values of mean SUV and k1 of a baseline study and a follow-up study after completion of one cycle was the best combination for a group-based analysis, into response or non-response. The quantitative assessment of the FDG kinetics in tumours should be used to quantify the “inhibitory effect” of chemotherapy and to individualize treatment. The main effect of the AI-G therapy may be on angiogenesis (k1 effect) rather than on proliferation.