RESUMO
BACKGROUND: Quantification of dynamic and static parameters extracted from 3,4-dihydroxy-6-[18F]-fluoro-L-phenylalanine (18F-DOPA, FDOPA) positron emission tomography (PET)/computed tomography (CT) plays a critical role for glioma assessment. The objective of the present study was to investigate the impact of point-spread function (PSF) reconstruction on these quantitative parameters. METHODS: Fourteen patients with untreated gliomas and investigated with FDOPA PET/CT were analyzed. The distribution of the 14 cases was as follows: 6 astrocytomas-isocitrate dehydrogenase-mutant; 2 oligodendrogliomas/1p19q-codeleted-isocitrate dehydrogenase-mutant; and 6 isocitrate dehydrogenase-wild-type glioblastomas. A 0-20-min dynamic images (8×15, 2×30, 2×60, and 3×300 s post-injection) and a 0-20-min static image were reconstructed with and without PSF. Tumoral volumes-of-interest were generated on all of the PET series and the background volumes-of-interest were generated on the 0-20-min static image with and without PSF. Static parameters (SUVmax and SUVmean) of the tumoral and the background volumes-of-interest and kinetic parameters (K1 and k2) of the tumoral volumes-of-interest extracted from using full kinetic analysis were provided. PSF and non-PSF quantitative parameters values were compared. RESULTS: Thirty-three tumor volumes-of-interest and 14 background volumes-of-interest were analyzed. PSF images provided higher tumor SUVmax than non-PSF images for 23/33 VOIs [median SUVmax =3.0 (range, 1.4-10.2) with PSF vs. 2.7 (range, 1.4-9.1) without PSF; P<0.001] and higher tumor SUVmean for 13/33 volumes-of-interest [median SUVmean =2.0 (range, 0.8-7.6) with PSF vs. 2.0 (range, 0.8-7.4) without PSF; P=0.002]. K1 and k2 were significantly lower with PSF than without PSF [respectively median K1 =0.077 mL/ccm/min (range, 0.043-0.445 mL/ccm/min) with PSF vs. 0.101 mL/ccm/min (range, 0.055-0.578 mL/ccm/min) without PSF; P<0.001 and median k2 =0.070 min-1 (range, 0.025-0.146 min-1) with PSF vs. 0.081 min-1 (range, 0.027-0.180 min-1) without PSF; P<0.001]. Background SUVmax and SUVmean were statistically unaffected [respectively median SUVmax =1.7 (range, 1.3-2.0) with PSF vs. 1.7 (range, 1.3-1.9) without PSF; P=0.346 and median SUVmean =1.5 (range, 1.0-1.8) with PSF vs. 1.5 (range, 1.0-1.7) without PSF; P=0.371]. CONCLUSIONS: The present study confirms that PSF significantly increases tumor activity concentrations measured on PET images. PSF algorithms for quantitative PET/CT analysis should be used with caution, especially for quantification of kinetic parameters.
RESUMO
Purpose: The aim of this study was to assess the value of the FDOPA PET kinetic parameters extracted using full kinetic analysis for tumor grading with neuronavigation-guided biopsies as reference in patients with newly-diagnosed gliomas. Methods: Fourteen patients with untreated gliomas were investigated. Twenty minutes of dynamic positron-emission tomography (PET) imaging and a 20-min static image 10 min after injection were reconstructed from a 40-min list-mode acquisition immediately after FDOPA injection. Tumors volume-of-interest (VOI) were generated based on the MRI-guided brain biopsies. Static parameters (TBRmax and TBRmean) and kinetic parameters [K1 and k2 using full kinetic analysis with the reversible single-tissue compartment model with blood volume parameter and the time-to-peak (TTP)] were extracted. Performances of each parameter for differentiating low-grade gliomas (LGG) from high-grade gliomas (HGG) were evaluated by receiver-operating characteristic analyses (area under the curve; AUC). Results: Thirty-two tumoral VOI were analyzed. K1, k2, and TTP were significantly higher for HGG than for LGG (median K1-value = 0.124 vs. 0.074 ml/ccm/min, p = 0.025, median k2-value = 0.093 vs. 0.063 min-1, p = 0.025, and median TTP-value = 10.0 vs. 15.0 min, p = 0.025). No significant difference was observed for the static parameters. The AUC for the kinetic parameters was higher than the AUC for the static parameters (respectively, AUCK1 = 0.787, AUCk2 = 0.785, AUCTTP = 0.775, AUCTBRmax = 0.551, AUCTBRmean = 0.575), significantly compared to TBRmax (respectively, p = 0.001 for K1, p = 0.031 for k2, and p = 0.029 for TTP). Conclusion: The present study suggests an additive value of FDOPA PET/CT kinetic parameters for newly-diagnosed gliomas grading.
RESUMO
INTRODUCTION: 3,4-dihydroxy-6-[18F]fluoro-L-phenylalanine (FDOPA) uptake quantification in glioma assessment can be distorted using a non-optimal time frame binning of time-activity curves (TAC). Under-sampling or over-sampling dynamic PET images induces significant variations on kinetic parameters quantification. We aimed to optimize temporal time frame binning for dynamic FDOPA PET imaging. METHODS: Fourteen patients with 33 tumoral TAC with biopsy-proven gliomas were analysed. The mean SUVmax tumor-to-brain ratio (TBRmax) were compared at 20 min and 35 min post-injection (p.i). Five different time frame samplings within 20 min were compared: 11x10sec-6x15sec-5x20sec-3x300sec; 8x15sec- 2x30sec- 2x60sec- 3x300sec; 6x20sec- 8x60sec- 2x300sec; 10x30sec- 3x300sec and 4x45sec- 3x90sec- 5x150sec. The reversible single-tissue compartment model with blood volume parameter (VB) was selected using the Akaike information criterion. K1 values extracted from 1024 noisy simulated TAC using Monte Carlo method from the 5 different time samplings were compared to a target K1 value as the objective, which is the average of the K1 values extracted from the 33 lesions using an imaging-derived input function for each patient. RESULTS: The mean TBRmax was significantly higher at 20 min p.i. than at 35 min p.i (respectively 1.4 +/- 0.8 and 1.2 +/- 0.6; p <0.001). The target K1 value was 0.161 mL/ccm/min. The 8x15sec- 2x30sec- 2x60sec- 3x300sec time sampling was the optimal time frame binning. K1 values extracted using this optimal time frame binning were significantly different with K1 values extracted from the other time frame samplings, except with K1 values obtained using the 11x10sec- 6x15sec -5x20sec-3x300sec time frame binning. CONCLUSIONS: This optimal sampling schedule design (8x15sec- 2x30sec- 2x60sec- 3x300sec) could be used to minimize bias in quantification of FDOPA uptake in glioma using kinetic analysis.