Parametric method performance for dynamic 39-Deoxy-39-18F-Fluorothymidine PET/CT in epidermal growth factor receptor-mutated non-small cell lung carcinoma patients before and during therapy

Abstract

The objective of this study was to validate several parametric methods for quantification of 39-deoxy-39-18F-fluorothymidine (18FFLT) PET in advanced-stage non-small cell lung carcinoma (NSCLC) patients with an activating epidermal growth factor receptor mutation who were treated with gefitinib or erlotinib. Furthermore, we evaluated the impact of noise on accuracy and precision of the parametric analyses of dynamic 18F-FLT PET/CT to assess the robustness of these methods. Methods: Ten NSCLC patients underwent dynamic 18F-FLT PET/CT at baseline and 7 and 28 d after the start of treatment. Parametric images were generated using plasma input Logan graphic analysis and 2 basis functions-based methods: a 2-tissue-compartment basis function model (BFM) and spectral analysis (SA). Whole-tumor-averaged parametric pharmacokinetic parameters were compared with those obtained by nonlinear regression of the tumor time-activity curve using a reversible 2-tissue-compartment model with blood volume fraction. In addition, 2 statistically equivalent datasets were generated by countwise splitting the original list-mode data, each containing 50% of the total counts. Both new datasets were reconstructed, and parametric pharmacokinetic parameters were compared between the 2 replicates and the original data. Results: After the settings of each parametric method were optimized, distribution volumes (VT) obtained with Logan graphic analysis, BFM, and SA all correlated well with those derived using nonlinear regression at baseline and during therapy (R2 0.94; intraclass correlation coefficient . 0.97). SAbased VT images were most robust to increased noise on a voxellevel (repeatability coefficient, 16% vs. .26%). Yet BFM generated the most accurate K1 values (R2 5 0.94; intraclass correlation coefficient, 0.96). Parametric K1 data showed a larger variability in general; however, no differences were found in robustness between methods (repeatability coefficient, 80%-84%). Conclusion: Both BFM and SA can generate quantitatively accurate parametric 18FFLT VT images in NSCLC patients before and during therapy. SA was more robust to noise, yet BFM provided more accurate parametric K1 data. We therefore recommend BFM as the preferred parametric method for analysis of dynamic 18F-FLT PET/CT studies; however, SA can also be used.