No abstract

Astrocytes and microglia become reactive under most brain pathological conditions, making this neuroinflammation process a surrogate marker of neuronal dysfunction. Neuroinflammation is associated with increased levels of translocator protein 18 kDa (TSPO) and binding sites for TSPO ligands. Positron emission tomography (PET) imaging of TSPO is thus commonly used to monitor neuroinflammation in preclinical and clinical studies. It is widely considered that TSPO PET signal reveals reactive microglia, although a few studies suggested a potential contribution of reactive astrocytes. Because astrocytes and microglia play very different roles, it is crucial to determine whether reactive astrocytes can also overexpress TSPO and yield to a detectable TSPO PET signal in vivo. We used a model of selective astrocyte activation through lentiviral gene transfer of the cytokine ciliary neurotrophic factor (CNTF) into the rat striatum, in the absence of neurodegeneration. CNTF induced an extensive activation of astrocytes, which overexpressed GFAP and become hypertrophic, whereas microglia displayed minimal increaseinreactivemarkers.TwoTSPOradioligands,[ TSPO mRNA levels were significantly increased, and TSPO protein was overexpressed by CNTF-activated astrocytes. We show that reactive astrocytes overexpress TSPO, yielding to a significant and selective binding of TSPO radioligands. Therefore, caution must be used when interpreting TSPO PET imaging in animals or patients because reactive astrocytes can contribute to the signal in addition to reactive microglia.

Translocator protein (TSPO) is expressed at a low level in healthy brain and is upregulated during inflammatory processes that may occur in neurodegenerative diseases. Thus, TSPO may be a suitable in vivo indicator of neurodegeneration. Here, we quantified the 18 F-DPA-714 radioligand in healthy TSPO-genotyped volunteers and developed a method to eliminate the need for invasive arterial blood sampling. Methods: Ten controls (7 high-affinity binders [HABs] and 3 mixed-affinity binders [MABs]) underwent 18 F-DPA-714 PET with arterial and venous sampling. 18 F-DPA-714 binding was quantified with a metabolite-corrected arterial plasma input function, using the 1-and 2-tissue-compartment models (TCMs) as well as the Logan analysis to estimate total volume distribution (V T ) in the regions of interest. Alternative quantification methods were tested, including tissue-to-plasma ratio or population-based input function approaches normalized by late time points of arterial or venous samples. Results: The distribution pattern of 18 F-DPA-714 was consistent with the known distribution of TSPO in humans, with the thalamus displaying the highest binding and the cerebellum the lowest. The 2-TCM best described the regional kinetics of 18 F-DPA-714 in the brain, with good identifiability (percentage coefficient of variation , 5%). For each region of interest, V T was 47.6% ± 6.3% higher in HABs than in MABs, and estimates from the 2-TCM and the Logan analyses were highly correlated. Equilibrium was reached at 60 min after injection. V T calculated with alternative methods using arterial samples was strongly and significantly correlated with that calculated by the 2-TCM. Replacement of arterial with venous sampling in these methods led to a significant but lower correlation. Conclusion: Genotyping of subjects is a prerequisite for a reliable quantification of 18 F-DPA-714 PET images. The 2-TCM and the Logan analyses are accurate methods to estimate 18 F-DPA-714 V T in the human brain of both HAB and MAB individuals. Population-based input function and tissue-to-plasma ratio with a single arterial sample are promising alternatives to classic arterial plasma input function. Substitution with venous samples is promising but still requires methodologic improvements.

There is a great need for a non-invasive methodology enabling the quantification of translocator protein overexpression in PET clinical imaging. [F]DPA-714 has emerged as a promising translocator protein radiotracer as it is fluorinated, highly specific and returned reliable quantification using arterial input function. Cerebellum gray matter was proposed as reference region for simplified quantification; however, this method cannot be used when inflammation involves cerebellum. Here we adapted and validated a supervised clustering (supervised clustering algorithm (SCA)) for [F]DPA-714 analysis. Fourteen healthy subjects genotyped for translocator protein underwent an [F]DPA-714 PET, including 10 with metabolite-corrected arterial input function and three for a test-retest assessment. Two-tissue compartmental modelling provided [Formula: see text] estimates that were compared to either [Formula: see text] or [Formula: see text] generated by Logan analysis (using supervised clustering algorithm extracted reference region or cerebellum gray matter). The supervised clustering algorithm successfully extracted a pseudo-reference region with similar reliability using classes that were defined using either all subjects, or separated into HAB and MAB subjects. [Formula: see text], [Formula: see text] and [Formula: see text] were highly correlated (ICC of 0.91 ± 0.05) but [Formula: see text] were ∼26% higher and less variable than [Formula: see text]. Reproducibility was good with 5% variability in the test-retest study. The clustering technique for [F]DPA-714 provides a simple, robust and reproducible technique that can be used for all neurological diseases.

Increasing evidence suggests that neuroinflammation is active in Parkinson disease (PD) and contributes to neurodegeneration. This process can be studied in vivo with PET and radioligands targeting TSPO, upregulated in activated microglia. Initial PET studies investigating microglial activation in PD with the [ 11 C]-PK11195 have provided inconclusive results. Here we assess the presence and distribution of neuroinflammatory response in PD patients using [ 18 F]-DPA714 and to correlate imaging biomarkers to dopamine transporter imaging and clinical status. Methods: PD patients (n = 24, Hoehn and Yahr I-III) and 28 healthy controls were scanned with [ 18 F]-DPA714 and [ 11 C]-PE2I and analyzed. They were all genotyped for TSPO polymorphism. Regional binding parameters were estimated (reference Logan graphical approach with supervised cluster analysis). Impact of TSPO genotype was analyzed using Wilcoxon signed-rank test. Differences between groups were investigated using a two-way ANOVA and Tukey post hoc tests. Results: PD patients showed significantly higher [ 18 F]-DPA714 binding compared to healthy controls bilaterally in the midbrain (p < 0.001), the frontal cortex (p = 0.001), and the putamen contralateral to the more clinically affected hemibody (p = 0.038). Microglial activation in these regions did not correlate with the severity of motor symptoms, disease duration nor putaminal [ 11 C]-PE2I uptake. However, there was a trend toward a correlation between cortical TSPO binding and disease duration (p = 0.015 uncorrected, p = 0.07 after Bonferroni correction). Conclusion: [ 18 F]-DPA714 binding confirmed that there is a specific topographic pattern of microglial activation in the nigro-striatal pathway and the frontal cortex of PD patients.

[(18)F]DPA-714 binds to TSPO with high specificity in the primate brain under normal conditions and in the QA model. This tracer provides a sensitive tool for assessing neuroinflammation in the human brain.

The 18 kDa translocator protein (TSPO) is a marker of microglia activation and the main target of positron emission tomography (PET) ligands for neuroinflammation. Previous works showed that accounting for TSPO endothelial binding improves PET quantification for [C]PBR28, [F]DPA714 and [C]-R-PK11195. It is still unclear, however, whether the vascular signal is tracer-dependent. This work aims to explore the relationship between the TSPO vascular and tissue components for PET tracers with varying affinity, also assessing the impact of affinity towards the differentiability amongst kinetics and the ensuing ligand amenability to cluster analysis for the extraction of a reference region. First, we applied the compartmental model accounting for vascular binding to [C]-R-PK11195 data from six healthy subjects. Then, we compared the [C]-R-PK11195 vascular binding estimates with previously published values for [F]DPA714 and [C]PBR28. Finally, we determined the suitability for reference region extraction by calculating the angle between grey and white matter kinetics. Our results showed that endothelial binding is common to all TSPO tracers and proportional to their affinity. By consequence, grey and white matter kinetics were most similar for the radioligand with the highest affinity (i.e. [C]PBR28), hence poorly suited for the extraction of a reference region using supervised clustering.

F-DPA-714 is a second-generation tracer for PET imaging of the 18-kDa translocator protein (TSPO), a marker of neuroinflammation. Analysis and interpretation of TSPO PET are challenging, especially because of the basal expression of TSPO. The aim of this study was to evaluate a compartmental model that accounts for the effect of endothelial TSPO binding on the quantification of F-DPA-714 PET scans from a cohort of healthy subjects. Fifteen healthy subjects (9 high-affinity binders and 6 mixed-affinity binders) underwent F-DPA-714 PET scans with arterial blood sampling and metabolite analysis. The kinetic parameters were quantified using a 2-tissue compartmental model (2TC) as well as a 2TC with an extra, irreversible, compartment for endothelial binding (2TC-1K). These regional parameters and messenger RNA (mRNA) expression specific to endothelial cells were correlated with regional TSPO mRNA expression. The 2TC-1K model was more appropriate than the 2TC for 81% of fits. The total volume of distribution was significantly reduced by 21% ± 12% across all regions with the 2TC-1K, compared with the 2TC. The endothelial binding parameter varied highly across brain regions. strongly and significantly correlated with all 3 probes extracted for TSPO mRNA expression ( = 0.80, = 0.79, and = 0.90), but no correlation was seen with the other binding parameters from the 2TC-1K. For the 2TC, there was a lower but significant correlation between the volume of distribution and one of the TSPO mRNA probes ( = 0.65). A strong, significant correlation was seen between mRNA for TSPO and genes specific to endothelial cells. Accounting for endothelial TSPO in the kinetic model improved the fit of PET data. The high correlation between and TSPO mRNA suggests that the 2TC-1K model reveals more biologic information about the regional density of TSPO than the 2TC. The correlation between TSPO and endothelial cell mRNA supports the relationship between the regional variation of and endothelial TSPO. These results can improve the estimation of binding parameter estimates fromF-DPA-714 PET, especially in diseases that induce vascular change.