[en] In this review the findings of response monitoring studies in breast cancer, using [¹⁸F]2-fluoro-2-deoxy-d-glucose (FDG) and positron emission tomography (PET), are summarised. These studies indicate that there is a strong relationship between response and decrease in FDG signal even at an early stage of therapy. The review concentrates on methodological aspects of monitoring response with FDG: timing of serial scans, approach to region of interest definition, method of quantification and pitfalls of FDG. It is argued that, for clinical applications, there is now a need to standardise methodology. This would be necessary to establish firm cut-off values for discriminating responders from non-responders, which in turn would provide a means for providing optimal treatment for as many patients as possible. (orig.)

[en] Quantitative measurement of tracer uptake in a tumour can be influenced by a number of factors, including the method of defining regions of interest (ROIs) and the reconstruction parameters used. The main purpose of this study was to determine the effects of different ROI methods on quantitative outcome, using two reconstruction methods and the standard uptake value (SUV) as a simple quantitative measure of FDG uptake. Four commonly used methods of ROI definition (manual placement, fixed dimensions, threshold based and maximum pixel value) were used to calculate SUV (SUV_[MAN], SUV_15mm, SUV₅₀, SUV₇₅ and SUV_max, respectively) and to generate ''metabolic'' tumour volumes. Test-retest reproducibility of SUVs and of ''metabolic'' tumour volumes and the applicability of ROI methods during chemotherapy were assessed. In addition, SUVs calculated on ordered subsets expectation maximisation (OSEM) and filtered back-projection (FBP) images were compared. ROI definition had a direct effect on quantitative outcome. On average, SUV_[MAN], SUV_15mm, SUV₅₀ and SUV₇₅, were respectively 48%, 27%, 34% and 15% lower than SUV_max when calculated on OSEM images. No statistically significant differences were found between SUVs calculated on OSEM and FBP reconstructed images. Highest reproducibility was found for SUV_15mm and SUV_[MAN] (ICC 0.95 and 0.94, respectively) and for ''metabolic'' volumes measured with the manual and 50% threshold ROIs (ICC 0.99 for both). Manual, 75% threshold and maximum pixel ROIs could be used throughout therapy, regardless of changes in tumour uptake or geometry. SUVs showed the same trend in relative change in FDG uptake after chemotherapy, irrespective of the ROI method used. The method of ROI definition has a direct influence on quantitative outcome. In terms of simplicity, user-independence, reproducibility and general applicability the threshold-based and fixed dimension methods are the best ROI methods. Threshold methods are in addition relatively independent of changes in size and geometry, however, and may therefore be more suitable for response monitoring purposes. (orig.)

[en] Quantitative accuracy of positron emission tomography (PET) is affected by partial volume effects resulting in increased underestimation of the standardized uptake value (SUV) with decreasing tumour volume. The purpose of the present study was to assess accuracy and precision of different partial volume correction (PVC) methods. Three methods for PVC were evaluated: (1) inclusion of the point spread function (PSF) within the reconstruction, (2) iterative deconvolution of PET images and (3) calculation of spill-in and spill-out factors based on tumour masks. Simulations were based on a mathematical phantom with tumours of different sizes and shapes. Phantom experiments were performed in 2-D mode using the National Electrical Manufacturers Association (NEMA) NU2 image quality phantom containing six differently sized spheres. Clinical studies (2-D mode) included a test-retest study consisting of 10 patients with stage IIIB and IV non-small cell lung cancer and a response monitoring study consisting of 15 female breast cancer patients. In all studies tumour or sphere volumes of interest (VOI) were generated using VOI based on adaptive relative thresholds. Simulations and experiments provided similar results. All methods were able to accurately recover true SUV within 10% for spheres equal to and larger than 1 ml. Reconstruction-based recovery, however, provided up to twofold better precision than image-based methods. Clinical studies showed that PVC increased SUV by 5-80% depending on tumour size. Test-retest variability slightly worsened from 9.8 ± 6.5 without to 10.8 ± 7.9% with PVC. Finally, PVC resulted in slightly smaller SUV responses, i.e. from -30.5% without to -26.3% with PVC after the first cycle of treatment (p < 0.01). PVC improves accuracy of SUV without decreasing (clinical) test-retest variability significantly and it has a small, but significant effect on observed tumour responses. Reconstruction-based PVC outperforms image-based methods, but requires dedicated reconstruction software. Image-based methods are good alternatives because of their ease of implementation and their similar performance in clinical studies. (orig.)

[en] 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). (orig.)