Measuring [18F]FDG uptake in breast cancer during chemotherapy: comparison of analytical methods

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Abstract
Over the years several analytical methods have been proposed for the measurement of glucose metabolism using fluorine-18 fluorodeoxyglucose ([^18F]FDG) and positron emission tomography (PET). The purpose of this study was to evaluate which of these (often simplified) methods could potentially be used for clinical response monitoring studies in breast cancer. Prior to chemotherapy, dynamic [^18F]FDG scans were performed in 20 women with locally advanced ( n =10) or metastasised ( n =10) breast cancer. Additional PET scans were acquired after 8 days ( n =8), and after one, three and six courses of chemotherapy ( n =18, 10 and 6, respectively). Non-linear regression (NLR) with the standard two tissue compartment model was used as the gold standard for measurement of [^18F]FDG uptake and was compared with the following methods: Patlak graphical analysis, simplified kinetic method (SKM), SUV-based net influx constant ("Sadato" method), standard uptake value [normalised for weight, lean body mass (LBM) and body surface area (BSA), with and without corrections for glucose (g)], tumour to non-tumour ratio (TNT), 6P model and total lesion evaluation (TLE). Correlation coefficients between each analytical method and NLR were calculated using multilevel analysis. In addition, for the most promising methods (Patlak, SKM, SUV_LBMg and SUV_BSAg) it was explored whether correlation with NLR changed with different time points after the start of therapy. Three methods showed excellent correlation ( r >0.95) with NLR for the baseline scan: Patlak10–60 and Patlak10–45 ( r =0.98 and 0.97, respectively), SKM40–60 ( r =0.96) and SUV_LBMg ( r =0.96). Good correlation was found between NLR and SUV-based net influx constant, TLE and SUV_BSAg (0.90< r <0.95). The 6P model and TNT had the lowest correlation ( r ≤0.84). SUV was least accurate in predicting changes in [^18F]FDG uptake over time during therapy. For all methods, correlation with NLR was significantly lower for bone metastases than for other (primary or metastatic) tumour lesions ( P <0.05). In conclusion, three methods with different degrees of complexity appear to be promising alternatives to NLR for measuring glucose metabolism in breast cancer: Patlak, SKM and SUV (normalised for LBM and with a correction for plasma glucose).