Preclinical in vivo and in vitro comparison of the translocator protein PET ligands [18F]PBR102 and [18F]PBR111

Eberl, Stefan; Katsifis, Andrew; Peyronneau, Marie-Anne; Wen, Lingfeng; Henderson, David; Loc’h, Christian; Greguric, Ivan; Verschuer, Jordan; Pham, Tien; Lam, Peter; Mattner, Filomena; Mohamed, Armin; Fulham, Michael

doi:10.1007/s00259-016-3517-z

Cited by 21 publications

(13 citation statements)

References 37 publications

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“…V ND values we obtain with HYDECA average 27% of total binding in ventral striatum for [ 11 C]DASB, and 22% of the total binding in hippocampus for [ 11 C]CUMI-101, which is generally in line with reports for other PET tracers [31, 32]. …”

Section: Resultssupporting

confidence: 89%

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region

2017

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Background and aimEstimation of a PET tracer’s non-displaceable distribution volume (VND) is required for quantification of specific binding to its target of interest. VND is generally assumed to be comparable brain-wide and is determined either from a reference region devoid of the target, often not available for many tracers and targets, or by imaging each subject before and after blocking the target with another molecule that has high affinity for the target, which is cumbersome and involves additional radiation exposure. Here we propose, and validate for the tracers [11C]DASB and [11C]CUMI-101, a new data-driven hybrid deconvolution approach (HYDECA) that determines VND at the individual level without requiring either a reference region or a blocking study.MethodsHYDECA requires the tracer metabolite-corrected concentration curve in blood plasma and uses a singular value decomposition to estimate the impulse response function across several brain regions from measured time activity curves. HYDECA decomposes each region’s impulse response function into the sum of a parametric non-displaceable component, which is a function of VND, assumed common across regions, and a nonparametric specific component. These two components differentially contribute to each impulse response function. Different regions show different contributions of the two components, and HYDECA examines data across regions to find a suitable common VND. HYDECA implementation requires determination of two tuning parameters, and we propose two strategies for objectively selecting these parameters for a given tracer: using data from blocking studies, and realistic simulations of the tracer. Using available test-retest data, we compare HYDECA estimates of VND and binding potentials to those obtained based on VND estimated using a purported reference region.ResultsFor [11C]DASB and [11C]CUMI-101, we find that regardless of the strategy used to optimize the tuning parameters, HYDECA provides considerably less biased estimates of VND than those obtained, as is commonly done, using a non-ideal reference region. HYDECA test-retest reproducibility is comparable to that obtained using a VND determined from a non-ideal reference region, when considering the binding potentials BPP and BPND.ConclusionsHYDECA can provide subject-specific estimates of VND without requiring a blocking study for tracers and targets for which a valid reference region does not exist.

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Section: Resultssupporting

confidence: 89%

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region

2017

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“…The polar radiometabolite has been identified previously as 18 Ffluoropropionic acid (21). According to other studies, none of the radiometabolites entered the brain within 60 min after injection (21,22). Parent and metabolite profiles did not vary across the clinical groups.…”

Section: Discussionmentioning

confidence: 71%

“…Metabolite analysis revealed that 18 F-PBR111 rapidly decreased over time with formation of both polar and semiapolar radiometabolites in the arterial plasma. The polar radiometabolite has been identified previously as 18 Ffluoropropionic acid (21). According to other studies, none of the radiometabolites entered the brain within 60 min after injection (21,22).…”

Section: Discussionmentioning

confidence: 91%

¹⁸F-PBR111 PET Imaging in Healthy Controls and Schizophrenia: Test–Retest Reproducibility and Quantification of Neuroinflammation

et al. 2018

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Activated microglia express the translocator protein (TSPO) on the outer mitochondrial membrane. F-PBR111 is a second-generation PET ligand that specifically binds the TSPO, allowing in vivo visualization and quantification of neuroinflammation. The aim of this study was to evaluate whether the test-retest variability ofF-PBR111 in healthy controls is acceptable to detect a psychosis-associated neuroinflammatory signal in schizophrenia. Dynamic 90-minF-PBR111 scans were obtained in 17 healthy male controls (HCs) and 11 male schizophrenia patients (SPs) during a psychotic episode. Prior genotyping for the rs6917 polymorphism distinguished high-affinity binders (HABs) and mixed-affinity binders (MABs). Total volume of distribution (V) was determined from 2-tissue-compartment modeling with vascular trapping and a metabolite-corrected plasma input function. A subgroup of HCs ( = 12; 4 HABs and 8 MABs) was scanned twice to assess absolute test-retest variability and intraclass correlation coefficients of the regional V values. Differences in TSPO binding between HC and SP were assessed using mixed model analysis adjusting for age, genotype, and age*cohort. The effect of using different scan durations (V versus V) was determined based on Pearson r. Data were mean ± SD. Mean absolute variability in V ranged from 16% ± 14% (19% ± 20% HAB; 15% ± 11% MAB) in the cortical gray matter to 22% ± 15% (23% ± 15% HAB; 22% ± 16% MAB) in the hippocampus. Intraclass correlation coefficients were consistently between 0.64 and 0.82 for all tested regions. TSPO binding in SP compared with HC depended on age (cohort*age: < 0.05) and was increased by +14% ± 4% over the regions. There was a significant effect of genotype on TSPO binding, and V of HABs was 31% ± 8% (HC: 17% ± 5%, SP: 61% ± 14%) higher than MABs. Across all clinical groups, V and V were strongly correlated ( > 0.7, < 0.0001). F-PBR111 can be used for monitoring of TSPO binding, as shown by medium test-retest variability and reliability of V in HCs. Microglial activation is present in SPs depending on age and needs to be adjusted for genotype.

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“…In one such study, incubation of PBR102 and PBR111 with rat microsomes showed dealkylation and hydroxylation to be the predominant pathways, with lesser metabolism by human microsomes. 130 We summarize the metabolism of 13 tracers that have been employed in quantitative molecular imaging studies of TSPO in healthy human brain ( Table 1). There is substantial metabolism of most of these tracers during a dynamic PET/SPECT examination, such that proper quantitation of brain uptake entails chromatographic analysis of extracts from plasma derived from serial arterial blood sampling.…”

Section: Metabolism and Plasma Protein Bindingmentioning

confidence: 99%

Sifting through the surfeit of neuroinflammation tracers

Cumming

Burgher

Patkar

et al. 2017

J Cereb Blood Flow Metab

100

113

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The first phase of molecular brain imaging of microglial activation in neuroinflammatory conditions began some 20 years ago with the introduction of [C]-( R)-PK11195, the prototype isoquinoline ligand for translocator protein (18 kDa) (TSPO). Investigations by positron emission tomography (PET) revealed microgliosis in numerous brain diseases, despite the rather low specific binding signal imparted by [C]-( R)-PK11195. There has since been enormous expansion of the repertoire of TSPO tracers, many with higher specific binding, albeit complicated by allelic dependence of the affinity. However, the specificity of TSPO PET for revealing microglial activation not been fully established, and it has been difficult to judge the relative merits of the competing tracers and analysis methods with respect to their sensitivity for detecting microglial activation. We therefore present a systematic comparison of 13 TSPO PET and single photon computed tomography (SPECT) tracers belonging to five structural classes, each of which has been investigated by compartmental analysis in healthy human brain relative to a metabolite-corrected arterial input. We emphasize the need to establish the non-displaceable binding component for each ligand and conclude with five recommendations for a standard approach to define the cellular distribution of TSPO signals, and to characterize the properties of candidate TSPO tracers.

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Preclinical in vivo and in vitro comparison of the translocator protein PET ligands [18F]PBR102 and [18F]PBR111

Cited by 21 publications

References 37 publications

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region

¹⁸F-PBR111 PET Imaging in Healthy Controls and Schizophrenia: Test–Retest Reproducibility and Quantification of Neuroinflammation

Sifting through the surfeit of neuroinflammation tracers

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Preclinical in vivo and in vitro comparison of the translocator protein PET ligands [18F]PBR102 and [18F]PBR111

Cited by 21 publications

References 37 publications

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region

A hybrid deconvolution approach for estimation of in vivo non-displaceable binding for brain PET targets without a reference region

18F-PBR111 PET Imaging in Healthy Controls and Schizophrenia: Test–Retest Reproducibility and Quantification of Neuroinflammation

Sifting through the surfeit of neuroinflammation tracers

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¹⁸F-PBR111 PET Imaging in Healthy Controls and Schizophrenia: Test–Retest Reproducibility and Quantification of Neuroinflammation