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Background: Microglial activation is one hallmark of Alzheimer disease (AD) neuropathology but the impact of the regional interplay of microglia cells in the brain is poorly understood. We hypothesized that microglial activation is regionally synchronized in the healthy brain but experiences regional desynchronization with ongoing neurodegenerative disease. We addressed the existence of a microglia connectome and investigated microglial desynchronization as an AD biomarker. Methods: To validate the concept, we performed microglia depletion in mice to test whether interregional correlation coefficients (ICCs) of 18 kDa translocator protein (TSPO)-PET change when microglia are cleared. Next, we evaluated the influence of dysfunctional microglia and AD pathophysiology on TSPO-PET ICCs in the mouse brain, followed by translation to a human AD-continuum dataset. We correlated a personalized microglia desynchronization index with cognitive performance. Finally, we performed single-cell radiotracing (scRadiotracing) in mice to ensure the microglial source of the measured desynchronization. Results: Microglia-depleted mice showed a strong ICC reduction in all brain compartments, indicating microglia-specific desynchronization. AD mouse models demonstrated significant reductions of microglial synchronicity, associated with increasing variability of cellular radiotracer uptake in pathologically altered brain regions. Humans within the AD-continuum indicated a stage-depended reduction of microglia synchronicity associated with cognitive decline. scRadiotracing in mice showed that the increased TSPO signal was attributed to microglia. Conclusion: Using TSPO-PET imaging of mice with depleted microglia and scRadiotracing in an amyloid model, we provide first evidence that a microglia connectome can be assessed in the mouse brain. Microglia synchronicity is closely associated with cognitive decline in AD and could serve as an independent personalized biomarker for disease progression. [ABSTRACT FROM AUTHOR]

Purpose: [18F]PI-2620 positron emission tomography (PET) detects misfolded tau in progressive supranuclear palsy (PSP) and Alzheimer's disease (AD). We questioned the feasibility and value of absolute [18F]PI-2620 PET quantification for assessing tau by regional distribution volumes (VT). Here, arterial input functions (AIF) represent the gold standard, but cannot be applied in routine clinical practice, whereas image-derived input functions (IDIF) represent a non-invasive alternative. We aimed to validate IDIF against AIF and we evaluated the potential to discriminate patients with PSP and AD from healthy controls by non-invasive quantification of [18F] PET. Methods: In the first part of the study, we validated AIF derived from radial artery whole blood against IDIF by investigating 20 subjects (ten controls and ten patients). IDIF were generated by manual extraction of the carotid artery using the average and the five highest (max5) voxel intensity values and by automated extraction of the carotid artery using the average and the maximum voxel intensity value. In the second part of the study, IDIF quantification using the IDIF with the closest match to the AIF was transferred to group comparison of a large independent cohort of 40 subjects (15 healthy controls, 15 PSP patients and 10 AD patients). We compared VT and VT ratios, both calculated by Logan plots, with distribution volume (DV) ratios using simplified reference tissue modelling and standardized uptake value (SUV) ratios. Results: AIF and IDIF showed highly correlated input curves for all applied IDIF extraction methods (0.78 < r < 0.83, all p < 0.0001; area under the curves (AUC): 0.73 < r ≤ 0.82, all p ≤ 0.0003). Regarding the VT values, correlations were mainly found between those generated by the AIF and by the IDIF methods using the maximum voxel intensity values. Lowest relative differences (RD) were observed by applying the manual method using the five highest voxel intensity values (max5) (AIF vs. IDIF manual, avg: RD = -82%; AIF vs. IDIF automated, avg: RD = -86%; AIF vs. IDIF manual, max5: RD = -6%; AIF vs. IDIF automated, max: RD = -26%). Regional VT values revealed considerable variance at group level, which was strongly reduced upon scaling by the inferior cerebellum. The resulting VT ratio values were adequate to detect group differences between patients with PSP or AD and healthy controls (HC) (PSP target region (globus pallidus): HC vs. PSP vs. AD: 1.18 vs. 1.32 vs. 1.16; AD target region (Braak region I): HC vs. PSP vs. AD: 1.00 vs. 1.00 vs. 1.22). VT ratios and DV ratios outperformed SUV ratios and VT in detecting differences between PSP and healthy controls, whereas all quantification approaches performed similarly in comparing AD and healthy controls. Conclusion: Blood-free IDIF is a promising approach for quantification of [18F]PI-2620 PET, serving as correlating surrogate for invasive continuous arterial blood sampling. Regional [18F]PI-2620 VT show large variance, in contrast to regional [18F]PI-2620 VT ratios scaled with the inferior cerebellum, which are appropriate for discriminating PSP, AD and healthy controls. DV ratios obtained by simplified reference tissue modeling are similarly suitable for this purpose. [ABSTRACT FROM AUTHOR]

Purpose: According to the World Health Organization classification for tumors of the central nervous system, mutation status of the isocitrate dehydrogenase (IDH) genes has become a major diagnostic discriminator for gliomas. Therefore, imaging-based prediction of IDH mutation status is of high interest for individual patient management. We compared and evaluated the diagnostic value of radiomics derived from dual positron emission tomography (PET) and magnetic resonance imaging (MRI) data to predict the IDH mutation status non-invasively. Methods: Eighty-seven glioma patients at initial diagnosis who underwent PET targeting the translocator protein (TSPO) using [18F]GE-180, dynamic amino acid PET using [18F]FET, and T1-/T2-weighted MRI scans were examined. In addition to calculating tumor-to-background ratio (TBR) images for all modalities, parametric images quantifying dynamic [18F]FET PET information were generated. Radiomic features were extracted from TBR and parametric images. The area under the receiver operating characteristic curve (AUC) was employed to assess the performance of logistic regression (LR) classifiers. To report robust estimates, nested cross-validation with five folds and 50 repeats was applied. Results: TBRGE-180 features extracted from TSPO-positive volumes had the highest predictive power among TBR images (AUC 0.88, with age as co-factor 0.94). Dynamic [18F]FET PET reached a similarly high performance (0.94, with age 0.96). The highest LR coefficients in multimodal analyses included TBRGE-180 features, parameters from kinetic and early static [18F]FET PET images, age, and the features from TBRT2 images such as the kurtosis (0.97). Conclusion: The findings suggest that incorporating TBRGE-180 features along with kinetic information from dynamic [18F]FET PET, kurtosis from TBRT2, and age can yield very high predictability of IDH mutation status, thus potentially improving early patient management. [ABSTRACT FROM AUTHOR]

Objectives: Reactive gliosis is a common pathological hallmark of CNS pathology resulting from neurodegeneration and neuroinflammation. In this study we investigate the capability of a novel monoamine oxidase B (MAO-B) PET ligand to monitor reactive astrogliosis in a transgenic mouse model of Alzheimer's disease (AD). Furthermore, we performed a pilot study in patients with a range of neurodegenerative and neuroinflammatory conditions. Methods: A cross-sectional cohort of 24 transgenic (PS2APP) and 25 wild-type mice (age range: 4.3–21.0 months) underwent 60 min dynamic [18F]fluorodeprenyl-D2 ([18F]F-DED), static 18 kDa translocator protein (TSPO, [18F]GE-180) and β-amyloid ([18F]florbetaben) PET imaging. Quantification was performed via image derived input function (IDIF, cardiac input), simplified non-invasive reference tissue modelling (SRTM2, DVR) and late-phase standardized uptake value ratios (SUVr). Immunohistochemical (IHC) analyses of glial fibrillary acidic protein (GFAP) and MAO-B were performed to validate PET imaging by gold standard assessments. Patients belonging to the Alzheimer's disease continuum (AD, n = 2), Parkinson's disease (PD, n = 2), multiple system atrophy (MSA, n = 2), autoimmune encephalitis (n = 1), oligodendroglioma (n = 1) and one healthy control underwent 60 min dynamic [18F]F-DED PET and the data were analyzed using equivalent quantification strategies. Results: We selected the cerebellum as a pseudo-reference region based on the immunohistochemical comparison of age-matched PS2APP and WT mice. Subsequent PET imaging revealed that PS2APP mice showed elevated hippocampal and thalamic [18F]F-DED DVR when compared to age-matched WT mice at 5 months (thalamus: + 4.3%; p = 0.048), 13 months (hippocampus: + 7.6%, p = 0.022) and 19 months (hippocampus: + 12.3%, p < 0.0001; thalamus: + 15.2%, p < 0.0001). Specific [18F]F-DED DVR increases of PS2APP mice occurred earlier when compared to signal alterations in TSPO and β-amyloid PET and [18F]F-DED DVR correlated with quantitative immunohistochemistry (hippocampus: R = 0.720, p < 0.001; thalamus: R = 0.727, p = 0.002). Preliminary experience in patients showed [18F]F-DED VT and SUVr patterns, matching the expected topology of reactive astrogliosis in neurodegenerative (MSA) and neuroinflammatory conditions, whereas the patient with oligodendroglioma and the healthy control indicated [18F]F-DED binding following the known physiological MAO-B expression in brain. Conclusions: [18F]F-DED PET imaging is a promising approach to assess reactive astrogliosis in AD mouse models and patients with neurological diseases. [ABSTRACT FROM AUTHOR]

Aim: We aimed to investigate the impact of microglial activity and microglial FDG uptake on metabolic connectivity, since microglial activation states determine FDG–PET alterations. Metabolic connectivity refers to a concept of interacting metabolic brain regions and receives growing interest in approaching complex cerebral metabolic networks in neurodegenerative diseases. However, underlying sources of metabolic connectivity remain to be elucidated. Materials and methods: We analyzed metabolic networks measured by interregional correlation coefficients (ICCs) of FDG–PET scans in WT mice and in mice with mutations in progranulin (Grn) or triggering receptor expressed on myeloid cells 2 (Trem2) knockouts (−/−) as well as in double mutant Grn−/−/Trem2−/− mice. We selected those rodent models as they represent opposite microglial signatures with disease associated microglia in Grn−/− mice and microglia locked in a homeostatic state in Trem2−/− mice; however, both resulting in lower glucose uptake of the brain. The direct influence of microglia on metabolic networks was further determined by microglia depletion using a CSF1R inhibitor in WT mice at two different ages. Within maps of global mean scaled regional FDG uptake, 24 pre-established volumes of interest were applied and assigned to either cortical or subcortical networks. ICCs of all region pairs were calculated and z-transformed prior to group comparisons. FDG uptake of neurons, microglia, and astrocytes was determined in Grn−/− and WT mice via assessment of single cell tracer uptake (scRadiotracing). Results: Microglia depletion by CSF1R inhibition resulted in a strong decrease of metabolic connectivity defined by decrease of mean cortical ICCs in WT mice at both ages studied (6–7 m; p = 0.0148, 9–10 m; p = 0.0191), when compared to vehicle-treated age-matched WT mice. Grn−/−, Trem2−/− and Grn−/−/Trem2−/− mice all displayed reduced FDG–PET signals when compared to WT mice. However, when analyzing metabolic networks, a distinct increase of ICCs was observed in Grn−/− mice when compared to WT mice in cortical (p < 0.0001) and hippocampal (p < 0.0001) networks. In contrast, Trem2−/− mice did not show significant alterations in metabolic connectivity when compared to WT. Furthermore, the increased metabolic connectivity in Grn−/− mice was completely suppressed in Grn−/−/Trem2−/− mice. Grn−/− mice exhibited a severe loss of neuronal FDG uptake (− 61%, p < 0.0001) which shifted allocation of cellular brain FDG uptake to microglia (42% in Grn−/− vs. 22% in WT). Conclusions: Presence, absence, and activation of microglia have a strong impact on metabolic connectivity of the mouse brain. Enhanced metabolic connectivity is associated with increased microglial FDG allocation. Highlights: Microglial activation influences metabolic connectivity. Microglial depletion results in distinct decreases of metabolic connectivity. Metabolic connectivity increases in progranulin deficient mice. Cellular FDG allocation in progranulin deficient mice is shifted to microglia. [ABSTRACT FROM AUTHOR]

Haploinsufficiency of the progranulin (PGRN)‐encoding gene (GRN) causes frontotemporal lobar degeneration (GRN‐FTLD) and results in microglial hyperactivation, TREM2 activation, lysosomal dysfunction, and TDP‐43 deposition. To understand the contribution of microglial hyperactivation to pathology, we used genetic and pharmacological approaches to suppress TREM2‐dependent transition of microglia from a homeostatic to a disease‐associated state. Trem2 deficiency in Grn KO mice reduced microglia hyperactivation. To explore antibody‐mediated pharmacological modulation of TREM2‐dependent microglial states, we identified antagonistic TREM2 antibodies. Treatment of macrophages from GRN‐FTLD patients with these antibodies led to reduced TREM2 signaling due to its enhanced shedding. Furthermore, TREM2 antibody‐treated PGRN‐deficient microglia derived from human‐induced pluripotent stem cells showed reduced microglial hyperactivation, TREM2 signaling, and phagocytic activity, but lysosomal dysfunction was not rescued. Similarly, lysosomal dysfunction, lipid dysregulation, and glucose hypometabolism of Grn KO mice were not rescued by TREM2 ablation. Synaptic loss and neurofilament light‐chain (NfL) levels, a biomarker for neurodegeneration, were further elevated in the Grn/Trem2 KO cerebrospinal fluid (CSF). These findings suggest that TREM2‐dependent microglia hyperactivation in models of GRN deficiency does not promote neurotoxicity, but rather neuroprotection. SYNOPSIS: Patients suffering from progranulin (PGRN) associated frontotemporal lobar degeneration (GRN‐FTLD) exhibit hyperactivated microglia, lysosomal dysfunction and TDP‐43 deposition. Suppression of TREM2 reverses hyperactivation of microglia in models of PGRN deficiency.Hyperactivated microglia in models of PGRN deficiency retain neuroprotective functions.Lysosomal dysfunction is independent of microglia activation stages. [ABSTRACT FROM AUTHOR]

keyimage.jpg Influential microglia: Neurodegenerative diseases are associated with alterations in brain energy metabolism. Recent developments in imaging techniques allow to visualize glucose metabolism alterations using 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG-PET). Here, Xiang et al. investigated the role of microglia in determining FDG-PET signal. The authors found that glucose uptake is greater in microglia compared to astrocytes and neurons and that microglia state determined the alterations in FDG-PET signal seen in mouse models of neurodegenerative diseases. In patients, microglia activity correlated with FDG-PET, suggesting the translational value of the preclinical data. The results suggest that microglia activity should be taken into consideration when performing brain FDG-PET. 2-Deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG-PET) is widely used to study cerebral glucose metabolism. Here, we investigated whether the FDG-PET signal is directly influenced by microglial glucose uptake in mouse models and patients with neurodegenerative diseases. Using a recently developed approach for cell sorting after FDG injection, we found that, at cellular resolution, microglia displayed higher glucose uptake than neurons and astrocytes. Alterations in microglial glucose uptake were responsible for both the FDG-PET signal decrease in Trem2-deficient mice and the FDG-PET signal increase in mouse models for amyloidosis. Thus, opposite microglial activation states determine the differential FDG uptake. Consistently, 12 patients with Alzheimer's disease and 21 patients with four-repeat tauopathies also exhibited a positive association between glucose uptake and microglial activity as determined by 18F-GE-180 18-kDa translocator protein PET (TSPO-PET) in preserved brain regions, indicating that the cerebral glucose uptake in humans is also strongly influenced by microglial activity. Our findings suggest that microglia activation states are responsible for FDG-PET signal alterations in patients with neurodegenerative diseases and mouse models for amyloidosis. Microglial activation states should therefore be considered when performing FDG-PET. [ABSTRACT FROM AUTHOR]

Parallax error is a common issue in high-resolution preclinical positron emission tomography (PET) scanners as well as in clinical scanners that have a long axial field of view (FOV), which increases estimation uncertainty of the annihilation position and therefore degrades the spatial resolution. A way to address this issue is depth-of-interaction (DOI) estimation. In this work we propose two machine learning-based algorithms, a dense and a convolutional neural network (NN), as well as a multiple linear regression (MLR)-based method to estimate DOI in depolished PET detector arrays with single-sided readout. The algorithms were tested on an 8× 8 array of 1.53× 1.53× 15 mm3 crystals and a 4× 4 array of 3.1× 3.1× 15 mm3 crystals, both made of Ce:LYSO scintillators and coupled to a 4× 4 array of 3× 3 mm3 silicon photomultipliers (SiPMs). Using the conventional linear DOI estimation method resulted in an average DOI resolution of 3.76 mm and 3.51 mm FWHM for the 8× 8 and the 4× 4 arrays, respectively. Application of MLR outperformed the conventional method with average DOI resolutions of 3.25 mm and 3.33 mm FWHM, respectively. Using the machine learning approaches further improved the DOI resolution, to an average DOI resolution of 2.99 mm and 3.14 mm FWHM, respectively, and additionally improved the uniformity of the DOI resolution in both arrays. Lastly, preliminary results obtained by using only a section of the crystal array for training showed that the NN-based methods could be used to reduce the number of calibration steps required for each detector array. [ABSTRACT FROM AUTHOR]

A system for the production of mutant recombinant human alpha-fetoprotein (rhAFP0) lacking the glycosylation site has been engineered in the yeast Pichia pastoris. A strain of the methylotrophic yeast Pichia pastoris GS115/pPICZαA/rhAFP0, which produces unglycosylated rhAFP0 and secretes it to the culture medium, has been constructed. Optimization and scale-up of the fermentation technology have resulted in an increase in the rhAFP0 yield to 20 mg/L. A scheme of isolation and purification of biologically active rhAFP0 has been developed. The synthesized protein has the antitumor activity, which is analogous to the activity of natural human embryonic alpha-fetoprotein. [ABSTRACT FROM AUTHOR]