Dynamic 2-Deoxy-2-[18F]Fluoro-D-Glucose Positron Emission Tomography for Chemotherapy Response Monitoring of Breast Cancer Xenografts
Non-invasive response monitoring can potentially be used to guide therapy selection for breast cancer patients. We employed dynamic 2-deoxy-2-[18F]fluoro-D-glucose positron emission tomography ([18F]FDG PET) to evaluate changes in three breast cancer xenograft lines in mice following three chemotherapy regimens.
Sixty-six athymic nude mice bearing bilateral breast cancer xenografts (two basal-like and one luminal-like subtype) underwent three 60 min [18F]FDG PET scans. Scans were performed prior to and 3 and 10 days after treatment with doxorubicin, paclitaxel, or carboplatin. Tumor growth was monitored in parallel. A pharmacokinetic compartmental model was fitted to the tumor uptake curves, providing estimates of transfer rates between the vascular, non-metabolized, and metabolized compartments. Early and late standardized uptake values (SUVE and SUVL, respectively); the rate constants k1, k2, and k3, and the intravascular fraction vB were estimated. Changes in tumor volume were used as a response measure. Multivariate partial least-squares regression (PLSR) was used to assess if PET parameters could model tumor response and to identify PET parameters with the largest impact on response.
Treatment responders had significantly larger perfusion-related parameters (k1 and k2) and lower metabolism-related parameter (k3) than non-responders 10 days after the start of treatment. These findings were further supported by the PLSR analysis, which showed that k1 and k2 at day 10 and changes in k3 explained most of the variability in response to therapy, whereas SUVL and particularly SUVE were of lesser importance.
Overall, rate parameters related to both tumor perfusion and metabolism were associated with tumor response. Conventional metrics of [18F]FDG uptake such as SUVE and SUVL apparently had little relation to tumor response, thus necessitating full dynamic scanning and pharmacokinetic analysis for optimal evaluation of chemotherapy-induced changes in breast cancers.