Comparison of different quantification methods for 18F-fluorodeoxyglucose-positron emission tomography studies in rat brains

Prando, Silvana; Carneiro, Camila de Godoi; Robilotta, Cecil Chow; Sapienza, Marcelo Tatit

doi:10.6061/clinics/2019/e1273

Cited by 6 publications

(12 citation statements)

References 31 publications

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“…Normalization of SUV by a reference region (such as pons or cerebellum) reduced the sample size down to 2 animals because of their much lower inter-and intra-individual variabilities. We noticed here that accounting for glycemia in SUV (SUV×Gly) did not reduce variability, in agreement with previous report [39].…”

Section: Plos Onesupporting

confidence: 93%

Comparative test-retest variability of outcome parameters derived from brain [18F]FDG PET studies in non-human primates

et al. 2020

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Introduction Knowledge of the repeatability of quantitative parameters derived from [ 18 F]FDG PET images is essential to define the group size and allow correct interpretation. Here we tested repeatability and accuracy of different [ 18 F]FDG absolute and relative quantification parameters in a standardized preclinical setup in nonhuman primates (NHP). Material and methods Repeated brain [ 18 F]FDG scans were performed in 6 healthy NHP under controlled experimental factors likely to account for variability. Regional cerebral metabolic rate of glucose (CMRglu) was calculated using a Patlak plot with blood input function Semi-quantitative approaches measuring standard uptake values (SUV, SUV×glycemia and SUVR (SUV Ratio) using the pons or cerebellum as a reference region) were considered. Test-retest variability of all quantification parameters were compared in different brain regions in terms of absolute variability and intra-and-inter-subject variabilities. In an independent [ 18 F]FDG PET experiment, robustness of these parameters was evaluated in 4 naive NHP. Results Experimental conditions (injected dose, body weight, animal temperature) were the same at both imaging sessions (p >0.4). No significant difference in the [ 18 F]FDG quantification parameters was found between test and retest sessions. Absolute variability of CMRglu, SUV, SUV×glycemia and normalized SUV ranged from 25 to 43%, 16 to 21%, 23 to 28%, and 7 to 14%, respectively. Intra-subject variability largely explained the absolute variability of all quantitative parameters. They were all significantly correlated to each other and they were all robust. Arterial and venous glycemia were highly correlated (r = 0.9691; p<0.0001).

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Section: Plos Onesupporting

confidence: 93%

Comparative test-retest variability of outcome parameters derived from brain [18F]FDG PET studies in non-human primates

et al. 2020

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“…Furthermore, we compared the quantification of DTW to several existing simplified quantification methods, including Patlak analysis, FUR, and SUV, as a surrogate for the net influx rate K i . The proposed DTW protocol produced the most accurate quantification, followed by FUR and Patlak analysis, while SUV had the lowest correlation, which is consistent with previous study findings [ 20 , 26 , 46 ]. In terms of visual performance, the DTW protocol generated parametric K i and K 1 images that were more consistent with the reference and had less noise than the Patlak analysis had.…”

Section: Discussionsupporting

confidence: 91%

Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Wang

et al. 2022

EJNMMI Phys

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Purpose Efforts have been made both to avoid invasive blood sampling and to shorten the scan duration for dynamic positron emission tomography (PET) imaging. A total-body scanner, such as the uEXPLORER PET/CT, can relieve these challenges through the following features: First, the whole-body coverage allows for noninvasive input function from the aortic arteries; second, with a dramatic increase in sensitivity, image quality can still be maintained at a high level even with a shorter scan duration than usual. We implemented a dual-time-window (DTW) protocol for a dynamic total-body 18F-FDG PET scan to obtain multiple kinetic parameters. The DTW protocol was then compared to several other simplified quantification methods for total-body FDG imaging that were proposed for conventional setup. Methods The research included 28 patient scans performed on an uEXPLORER PET/CT. By discarding the corresponding data in the middle of the existing full 60-min dynamic scan, the DTW protocol was simulated. Nonlinear fitting was used to estimate the missing data in the interval. The full input function was obtained from 15 subjects using a hybrid approach with a population-based image-derived input function. Quantification was carried out in three areas: the cerebral cortex, muscle, and tumor lesion. Micro- and macro-kinetic parameters for different scan durations were estimated by assuming an irreversible two-tissue compartment model. The visual performance of parametric images and region of interest-based quantification in several parameters were evaluated. Furthermore, simplified quantification methods (DTW, Patlak, fractional uptake ratio [FUR], and standardized uptake value [SUV]) were compared for similarity to the reference net influx rate Ki. Results Ki and K1 derived from the DTW protocol showed overall good consistency (P < 0.01) with the reference from the 60-min dynamic scan with 10-min early scan and 5-min late scan (Ki correlation: 0.971, 0.990, and 0.990; K1 correlation: 0.820, 0.940, and 0.975 in the cerebral cortex, muscle, and tumor lesion, respectively). Similar correlationss were found for other micro-parameters. The DTW protocol had the lowest bias relative to standard Ki than any of the quantification methods, followed by FUR and Patlak. SUV had the weakest correlation with Ki. The whole-body Ki and K1 images generated by the DTW protocol were consistent with the reference parametric images. Conclusions Using the DTW protocol, the dynamic total-body FDG scan time can be reduced to 15 min while obtaining accurate Ki and K1 quantification and acceptable visual performance in parametric images. However, the trade-off between quantification accuracy and protocol implementation feasibility must be considered in practice. We recommend that the DTW protocol be used when the clinical task requires reliable visual assessment or quantifying multiple micro-parameters; FUR with a hybrid input function may be a more feasible approach to quantifying regional metabolic rate with a known lesion position or organs of interest.

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“…Whereas graphical analysis is a more accurate method of quantification, it could not be performed for the “late” studies; thus, we chose to quantify BGU using the FUR. Even though the FUR is considered a less accurate method, it correlates very well with Patlak ( 23 ) and is a valid alternative of quantification of PET data, which could be applied more often in research settings. The individuals included in the current data set had apparent normal cognitive function, but cognitive function testing was not performed.…”

Section: Discussionmentioning

confidence: 99%

“…Although compartmental modeling and graphical Gjedde-Patlak analysis could have been used for the “early” data (as originally planned for these experiments ( 16 , 17 )), we used fractional uptake rate (FUR) for all data to homogenize the mathematical modeling across the whole data set. Of note, the Gjedde-Patlak analysis and FUR strongly correlate with each other ( 23 ). Thus, BGU (in μmol ⋅ 100 g −1 ⋅ min −1 ) was calculated at the voxel level as fractional uptake rate multiplied by the average plasma glucose concentration from the injection until the end of the brain scan, divided by the lumped constant for the brain (set at 0.65) ( 24 ).…”

Section: Methodsmentioning

confidence: 96%

Insulin Resistance Is Associated With Enhanced Brain Glucose Uptake During Euglycemic Hyperinsulinemia: A Large-Scale PET Cohort

et al. 2021

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OBJECTIVE Whereas insulin resistance is expressed as reduced glucose uptake in peripheral tissues, the relationship between insulin resistance and brain glucose metabolism remains controversial. Our aim was to examine the association of insulin resistance and brain glucose uptake (BGU) during a euglycemic hyperinsulinemic clamp in a large sample of study participants across a wide range of age and insulin sensitivity. RESEARCH DESIGN AND METHODS [ 18 F]-fluorodeoxyglucose positron emission tomography (PET) data from 194 participants scanned under clamp conditions were compiled from a single-center cohort. BGU was quantified by the fractional uptake rate. We examined the association of age, sex, M value from the clamp, steady-state insulin and free fatty acid levels, C-reactive protein levels, HbA 1c , and presence of type 2 diabetes with BGU using Bayesian hierarchical modeling. RESULTS Insulin sensitivity, indexed by the M value, was associated negatively with BGU in all brain regions, confirming that in insulin-resistant participants BGU was enhanced during euglycemic hyperinsulinemia. In addition, the presence of type 2 diabetes was associated with additional increase in BGU. On the contrary, age was negatively related to BGU. Steady-state insulin levels, C-reactive protein and free fatty acid levels, sex, and HbA 1c were not associated with BGU. CONCLUSIONS In this large cohort of participants of either sex across a wide range of age and insulin sensitivity, insulin sensitivity was the best predictor of BGU.

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Comparison of different quantification methods for 18F-fluorodeoxyglucose-positron emission tomography studies in rat brains

Cited by 6 publications

References 31 publications

Comparative test-retest variability of outcome parameters derived from brain [18F]FDG PET studies in non-human primates

Comparative test-retest variability of outcome parameters derived from brain [18F]FDG PET studies in non-human primates

Comparison between a dual-time-window protocol and other simplified protocols for dynamic total-body 18F-FDG PET imaging

Insulin Resistance Is Associated With Enhanced Brain Glucose Uptake During Euglycemic Hyperinsulinemia: A Large-Scale PET Cohort

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