Dataset Information

Intra-individual comparison of ¹?F-FET and ¹?F-DOPA in PET imaging of recurrent brain tumors.

ABSTRACT: BACKGROUND:Both (18)F-fluorodihydroxyphenylalanine ((18)F-DOPA) and (18)F-fluoroethyltyrosine ((18)F-FET) have already been used successfully for imaging of brain tumors. The aim of this study was to evaluate differences between these 2 promising tracers to determine the consequences for imaging protocols and the interpretation of findings. METHODS:Forty minutes of dynamic PET imaging were performed on 2 consecutive days with both (18)F-DOPA and (18)F-FET in patients with recurrent low-grade astrocytoma (n = 8) or high-grade glioblastoma (n = 8). Time-activity-curves (TACs), standardized uptake values (SUVs) and compartment modeling of both tracers were analyzed, respectively. RESULTS:The TAC of DOPA-PET peaked at 8 minutes p.i. with SUV 5.23 in high-grade gliomas and 10 minutes p.i. with SUV 4.92 in low-grade gliomas. FET-PET peaked at 9 minutes p.i. with SUV 3.17 in high-grade gliomas and 40 minutes p.i. with SUV 3.24 in low-grade gliomas. Neglecting the specific uptake of DOPA into the striatum, the tumor-to-brain and tumor-to-blood ratios were higher for DOPA-PET. Kinetic modeling demonstrated a high flow constant k1 (mL/ccm/min), representing cellular internalization through AS-transporters, for DOPA in both high-grade (k1 = 0.59) and low-grade (k1 = 0.55) tumors, while lower absolute values and a relevant dependency from tumor-grading (high-grade k1 = 0.43; low-grade k1 = 0.33) were observed with FET. CONCLUSIONS:DOPA-PET demonstrates superior contrast ratios for lesions outside the striatum, but SUVs do not correlate with grading. FET-PET can provide additional information on tumor grading and benefits from lower striatal uptake but presents lower contrast ratios and requires prolonged imaging if histology is not available in advance due to a more variable time-to-peak.

SUBMITTER: Kratochwil C

PROVIDER: S-EPMC3922512 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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Intra-individual comparison of ¹⁸F-FET and ¹⁸F-DOPA in PET imaging of recurrent brain tumors.

Kratochwil Clemens C Combs Stephanie E SE Leotta Karin K Afshar-Oromieh Ali A Rieken Stefan S Debus Jürgen J Haberkorn Uwe U Giesel Frederik L FL

Neuro-oncology 20131204 3

<h4>Background</h4>Both (18)F-fluorodihydroxyphenylalanine ((18)F-DOPA) and (18)F-fluoroethyltyrosine ((18)F-FET) have already been used successfully for imaging of brain tumors. The aim of this study was to evaluate differences between these 2 promising tracers to determine the consequences for imaging protocols and the interpretation of findings.<h4>Methods</h4>Forty minutes of dynamic PET imaging were performed on 2 consecutive days with both (18)F-DOPA and (18)F-FET in patients with recurren ...[more]

PMID: 24305717

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Project description:PurposeThe aim of our study was to investigate the efficacy of 18F-Fluciclovine brain PET imaging in recurrent gliomas, and to compare the utility of these images to that of contrast enhanced magnetic resonance imaging (MRI) and to [11C-methyl]-L-methionine (11C-Methionine) PET imaging. We also sought to gain insight into the factors affecting the uptake of 18F-FACBC in both tumors and normal brain, and specifically to evaluate how the uptake in these tissues varied over an extended period of time post injection.MethodsTwenty-seven patients with recurrent or progressive primary brain tumor (based on clinical and MRI/CT data) were studied using dynamic 18F-Fluciclovine brain imaging for up to 4 h. Of these, 16 patients also had 11C-Methionine brain scans. Visual findings, semi-quantitative analyses and pharmacokinetic modeling of a subset of the 18F-Fluciclovine images was conducted. The information derived from these analyses were compared to data from 11C-Methionine and to contrast-enhanced MRI.Results18F-Fluciclovine was positive for all 27 patients, whereas contrast MRI was indeterminate for three patients. Tumor 18F-Fluciclovine SUVmax ranged from 1.5 to 10.5 (average: 4.5?±?2.3), while 11C-Methionine's tumor SUVmax ranged from 2.2 to 10.2 (average: 5.0?±?2.2). Image contrast was higher with 18F-Fluciclovine compared to 11C-Methionine (p?<?0.0001). This was due to 18F-Fluciclovine's lower background in normal brain tissue (0.5?±?0.2 compared to 1.3?±?0.4 for 11C-Methionine). 18F-Fluciclovine uptake in both normal brain and tumors was well described by a simple one-compartment (three-parameter: Vb,k1,k2) model. Normal brain was found to approach transient equilibrium with a half-time that varied greatly, ranging from 1.5 to 8.3 h (mean 2.7?±?2.3 h), and achieving a consistent final distribution volume averaging 1.4?±?0.2 ml/cc. Tumors equilibrated more rapidly (t1/2ranging from 4 to 148 min, average 57?±?51 min), with an average distribution volume of 3.2?±?1.1 ml/cc. A qualitative comparison showed that the rate of normal brain uptake of 11C-Methionine was much faster than that of 18F-Fluciclovine.ConclusionTumor uptake of 18F-Fluciclovine correlated well with the established brain tumor imaging agent 11C-Methionine but provided significantly higher image contrast. 18F-Fluciclovine may be particularly useful when the contrast MRI is non-diagnostic. Based on the data gathered, we were unable to determine whether Fluciclovine uptake was due solely to recurrent tumor or if inflammation or other processes also contributed.

Project description:In this study, kinetic parameters of the cellular proliferation tracer (18)F-3'-deoxy-3'-fluoro-L-thymidine (FLT) and the amino acid probe 3,4-dihydroxy-6-(18)F-fluoro-L-phenylalanine (FDOPA) were measured before and early after the start of therapy, and were used to predict the overall survival (OS) of patients with recurrent malignant glioma using multiple linear regression (MLR) analysis.High-grade recurrent brain tumors in 21 patients (11 men and 10 women, age range 26 - 76 years) were investigated. Each patient had three dynamic PET studies with each probe: at baseline and after 2 and 6 weeks from the start of treatment. Treatment consisted of biweekly cycles of bevacizumab (an angiogenesis inhibitor) and irinotecan (a chemotherapeutic agent). For each study, about 3.5 mCi of FLT (or FDOPA) was administered intravenously and dynamic PET images were acquired for 1 h (or 35 min for FDOPA). A total of 126 PET scans were analyzed. A three-compartment, two-tissue model was applied to estimate tumor FLT and FDOPA kinetic rate constants using a metabolite- and partial volume-corrected input function. MLR analysis was used to model OS as a function of FLT and FDOPA kinetic parameters for each of the three studies as well as their relative changes between studies. An exhaustive search of MLR models using three or fewer predictor variables was performed to find the best models.Kinetic parameters from FLT were more predictive of OS than those from FDOPA. The three-predictor MLR model derived using information from both probes (adjusted R(2)?=?0.83) fitted the OS data better than that derived using information from FDOPA alone (adjusted R(2)?=?0.41), but was only marginally different from that derived using information from FLT alone (adjusted R(2)?=?0.82). Standardized uptake values (either from FLT alone, FDOPA alone, or both together) gave inferior predictive results (best adjusted R(2)?=?0.25).For recurrent malignant glioma treated with bevacizumab and irinotecan, FLT kinetic parameters obtained early after the start of treatment (absolute values and their associated changes) can provide sufficient information to predict OS with reasonable confidence using MLR. The slight increase in accuracy for predicting OS with a combination of FLT and FDOPA PET information may not warrant the additional acquisition of FDOPA PET for therapy monitoring in patients with recurrent glioma.

Project description:IntroductionMetabolic brain network analysis based on graph theory using FDG PET imaging is potentially useful for investigating brain activity alternation due to metabolism changes in different stages of Alzheimer's disease (AD). Most studies on metabolic network construction have been based on group data. Here a novel approach in building an individual metabolic network was proposed to investigate individual metabolic network abnormalities.MethodFirst, a weighting matrix was calculated based on the interregional effect size difference of mean uptake between a single subject and average normal controls (NCs). Then the weighting matrix for a single subject was multiplied by a group-based connectivity matrix from an NC cohort. To study the performance of the proposed individual metabolic network, inter- and intra-hemispheric connectivity patterns in the groups of NC, sMCI (stable mild cognitive impairment), pMCI (progressive mild cognitive impairment), and AD using the proposed individual metabolic network were constructed and compared with those from the group-based results. The network parameters of global efficiency and clustering coefficient and the network density score (NDS) in the default-mode network (DMN) of generated individual metabolic networks were estimated and compared among the disease groups in AD.ResultsOur results show that the intra- and inter-hemispheric connectivity patterns estimated from our individual metabolic network are similar to those from the group-based method. In particular, the key patterns of occipital-parietal and occipital-temporal inter-regional connectivity deficits detected in the groupwise network study for differentiating different disease groups in AD were also found in the individual network. A reduction trend was observed for network parameters of global efficiency and clustering coefficient, and also for the NDS from NC, sMCI, pMCI, and AD. There was no significant difference between NC and sMCI for all network parameters.ConclusionWe proposed a novel method in constructing the individual metabolic network using a single-subject FDG PET image and a group-based NC connectivity matrix. The result has shown the effectiveness and feasibility of the proposed individual metabolic network in differentiating disease groups in AD. Future studies should include investigation of inter-individual variability and the correlation of individual network features to disease severities and clinical performance.

Dataset Information

Intra-individual comparison of ¹?F-FET and ¹?F-DOPA in PET imaging of recurrent brain tumors.

Publications

Intra-individual comparison of ¹⁸F-FET and ¹⁸F-DOPA in PET imaging of recurrent brain tumors.

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