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Clustering time activity curves of PET images have been used to separate clinically relevant areas of the brain or tumours. However, PET image segmentation in multiorgan level is much less studied due to the available total-body data being limited to animal studies. Now, the new PET scanners providing the opportunity to acquire total-body PET scans also from humans are becoming more common, which opens plenty of new clinically interesting opportunities. Therefore, organ-level segmentation of PET images has important applications, yet it lacks sufficient research. In this proof of concept study, we evaluate if the previously used segmentation approaches are suitable for segmenting dynamic human total-body PET images in organ level. Our focus is on general-purpose unsupervised methods that are independent of external data and can be used for all tracers, organisms, and health conditions. Additional anatomical image modalities, such as CT or MRI, are not used, but the segmentation is done purely based on the dynamic PET images. The tested methods are commonly used building blocks of the more sophisticated methods rather than final methods as such, and our goal is to evaluate if these basic tools are suited for the arising human total-body PET image segmentation. First, we excluded methods that were computationally too demanding for the large datasets from human total-body PET scanners. These criteria filtered out most of the commonly used approaches, leaving only two clustering methods, k -means and Gaussian mixture model (GMM), for further analyses. We combined k -means with two different preprocessing approaches, namely, principal component analysis (PCA) and independent component analysis (ICA). Then, we selected a suitable number of clusters using 10 images. Finally, we tested how well the usable approaches segment the remaining PET images in organ level, highlight the best approaches together with their limitations, and discuss how further research could tackle the observed shortcomings. In this study, we utilised 40 total-body [18F] fluorodeoxyglucose PET images of rats to mimic the coming large human PET images and a few actual human total-body images to ensure that our conclusions from the rat data generalise to the human data. Our results show that ICA combined with k -means has weaker performance than the other two computationally usable approaches and that certain organs are easier to segment than others. While GMM performed sufficiently, it was by far the slowest one among the tested approaches, making k -means combined with PCA the most promising candidate for further development. However, even with the best methods, the mean Jaccard index was slightly below 0.5 for the easiest tested organ and below 0.2 for the most challenging organ. Thus, we conclude that there is a lack of accurate and computationally light general-purpose segmentation method that can analyse dynamic total-body PET images. [ABSTRACT FROM AUTHOR]

Purpose: In this study we compared the recently developed TSPO tracer [18F]F-DPA, with [18F]DPA-714 and [11C]PBR28 by performing in vivo PET imaging on the same Alzheimer's disease mouse model APP/PS1-21 (TG) and wild-type (WT) mice with all three radiotracers. Procedures: To compare the radiotracer uptake, percentage of injected dose/mL (%ID/mL), standardized uptake value ratios to cerebellum (SUVRCB), and voxel-wise analyses were performed. Results: The peak uptake of [18F]F-DPA was higher than 4.3% ID/mL, while [18F]DPA-714 reached just over 3% ID/mL, and [11C]PBR28 was over 4% ID/mL in only one brain region in the WT mice. The peak/60-min uptake ratios of [18F]F-DPA were significantly higher (p < 0.001) than those of [18F]DPA-714 and [11C]PBR28. The differences in [18F]F-DPA SUVRCB between WT and TG mice were highly significant (p < 0.001) in the three studied time periods after injection. [18F]DPA-714 uptake was significantly higher in TG mice starting in the 20–40-min timeframe and increased thereafter, whereas [11C]PBR28 uptake became significant at 10–20 min (p < 0.05). The voxel-wise analysis confirmed the differences between the radiotracers. Conclusions: [18F]F-DPA displays higher brain uptake, higher TG-to-WT SUVRCB ratios, and faster clearance than [18F]DPA-714 and [11C]PBR28, and could prove useful for detecting low levels of inflammation and allow for shorter dynamic PET scans. [ABSTRACT FROM AUTHOR]

[18F]F-DPA, a novel translocator protein 18 kDa (TSPO)-specific radioligand for imaging neuroinflammation, has to date been synthesized with low to moderate molar activities (Am's). In certain cases, low Am can skew the estimation of specific binding. The high proportion of the non-radioactive component can reduce the apparent-specific binding by competitively binding to receptors. We developed a nucleophilic synthesis of [18F]F-DPA resulting in high Am (990 ± 150 GBq/µmol) and performed in vivo comparison with low Am (9.0 ± 2.9 GBq/µmol) [18F]F-DPA in the same APP/PS1-21 and wild-type mice (injected masses: 0.34 ± 0.13 µg/kg and 38 ± 15 µg/kg, respectively). The high level of microgliosis in the APP/PS1-21 mouse model enables good differentiation between diseased and healthy animals and serves better to distinguish the effect of differing Am on specific binding. The differing injected masses affect the washout profile and shape of the time–activity curves. Ratios of standardized uptake values obtained with high and low Am [18F]F-DPA demonstrate that there is a 1.5-fold higher uptake of radioactivity in the brains of APP/PS1-21 animals when imaging is carried out with high Am [18F]F-DPA. The differences between APP/PS1-21 and wild-type animals showed higher significance when high Am was used. [ABSTRACT FROM AUTHOR]

Purpose: The α2-adrenoceptors mediate many effects of norepinephrine and epinephrine, and participate in the regulation of neuronal, endocrine, cardiovascular, vegetative, and metabolic functions. Of the three receptor subtypes, only α2A and α2C are found in the brain in significant amounts. Subtype-selective positron emission tomography (PET) imaging of α2-adrenoceptors has been limited to the α2C subtype. Here, we report the synthesis of 6-[18F]fluoro-marsanidine, a subtype-selective PET tracer candidate for α2A-adrenoceptors, and its preclinical evaluation in rats and mice. Procedures: 6-[18F]Fluoro-marsanidine was synthesized using electrophilic F-18 fluorination with [18F]Selectfluor bis(triflate). The tracer was evaluated in Sprague Dawley rats and in α2A-knockout (KO) and wild-type (WT) mice for subtype selectivity. In vivo PET imaging and ex vivo brain autoradiography were performed to determine the tracer distribution in the brain. The specificity of the tracer for the target was determined by pretreatment with the subtype-non-selective α2-agonist medetomidine. The peripheral biodistribution and extent of metabolism of 6-[18F]fluoro-marsanidine were also analyzed. Results: 6-[18F]Fluoro-marsanidine was synthesized with [18F]Selectfluor bis(triflate) in a radiochemical yield of 6.4 ± 1.7 %. The molar activity was 3.1 to 26.6 GBq/μmol, and the radiochemical purity was > 99 %. In vivo studies in mice revealed lower uptake in the brains of α2A-KO mice compared to WT mice. The results for selectivity were confirmed by ex vivo brain autoradiography. Blocking studies revealed reduced uptake in α2A-adrenoceptor-rich brain regions in pretreated animals, demonstrating the specificity of the tracer. Metabolite analyses revealed very rapid metabolism of 6-[18F]fluoro-marsanidine with blood-brain barrier-permeable metabolites in both rats and mice. Conclusion: 6-[18F]Fluoro-marsanidine was synthesized and evaluated as a PET tracer candidate for brain α2A-adrenoceptors. However, rapid metabolism, extensive presence of labeled metabolites in the brain, and high non-specific uptake in mouse and rat brain make 6-[18F]fluoro-marsanidine unsuitable for α2A-adrenoceptor targeting in rodents in vivo. [ABSTRACT FROM AUTHOR]