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Abstract Parkinson’s disease (PD) is the fastest growing neurodegenerative disease, but at present there is no cure, nor any disease-modifying treatments. Synaptic biomarkers from in vivo imaging have shown promise in imaging loss of synapses in PD and other neurodegenerative disorders. Here, we provide new clinical insights from a cross-sectional, high-resolution positron emission tomography (PET) study of 30 PD individuals and 30 age- and sex-matched healthy controls (HC) with the radiotracer [11C]UCB-J, which binds to synaptic vesicle glycoprotein 2A (SV2A), and is therefore, a biomarker of synaptic density in the living brain. We also examined a measure of relative brain perfusion from the early part of the same PET scan. Our results provide evidence for synaptic density loss in the substantia nigra that had been previously reported, but also extend this to other early-Braak stage regions known to be affected in PD (brainstem, caudate, olfactory cortex). Importantly, we also found a direct association between synaptic density loss in the nigra and severity of symptoms in patients. A greater extent and wider distribution of synaptic density loss in PD patients with longer illness duration suggests that [11C]UCB-J PET can be used to measure synapse loss with disease progression. We also demonstrate lower brain perfusion in PD vs. HC groups, with a greater extent of abnormalities in those with longer duration of illness, suggesting that [11C]UCB-J PET can simultaneously provide information on changes in brain perfusion. These results implicate synaptic imaging as a useful PD biomarker for future disease-modifying interventions.

Abstract Background Effective, disease-modifying therapeutics for the treatment of Alzheimer’s disease (AD) remain a large unmet need. Extensive evidence suggests that amyloid beta (Aβ) is central to AD pathophysiology, and Aβ oligomers are among the most toxic forms of Aβ. CT1812 is a novel brain penetrant sigma-2 receptor ligand that interferes with the binding of Aβ oligomers to neurons. Preclinical studies of CT1812 have demonstrated its ability to displace Aβ oligomers from neurons, restore synapses in cell cultures, and improve cognitive measures in mouse models of AD. CT1812 was found to be generally safe and well tolerated in a placebo-controlled phase 1 clinical trial in healthy volunteers and phase 1a/2 clinical trials in patients with mild to moderate dementia due to AD. The unique objective of this study was to incorporate synaptic positron emission tomography (PET) imaging as an outcome measure for CT1812 in AD patients. Methods The present phase 1/2 study was a randomized, double-blind, placebo-controlled, parallel-group trial conducted in 23 participants with mild to moderate dementia due to AD to primarily evaluate the safety of CT1812 and secondarily its pharmacodynamic effects. Participants received either placebo or 100 mg or 300 mg per day of oral CT1812 for 24 weeks. Pharmacodynamic effects were assessed using the exploratory efficacy endpoints synaptic vesicle glycoprotein 2A (SV2A) PET, fluorodeoxyglucose (FDG) PET, volumetric MRI, cognitive clinical measures, as well as cerebrospinal fluid (CSF) biomarkers of AD pathology and synaptic degeneration. Results No treatment differences relative to placebo were observed in the change from baseline at 24 weeks in either SV2A or FDG PET signal, the cognitive clinical rating scales, or in CSF biomarkers. Composite region volumetric MRI revealed a trend towards tissue preservation in participants treated with either dose of CT1812, and nominally significant differences with both doses of CT1812 compared to placebo were found in the pericentral, prefrontal, and hippocampal cortices. CT1812 was safe and well tolerated. Conclusions The safety findings of this 24-week study and the observed changes on volumetric MRI with CT1812 support its further clinical development. Trial registration The clinical trial described in this manuscript is registered at clinicaltrials.gov (NCT03493282).

Abstract Background The need for arterial blood data in quantitative PET research limits the wider usability of this imaging method in clinical research settings. Image-derived input function (IDIF) approaches have been proposed as a cost-effective and non-invasive alternative to gold-standard arterial sampling. However, this approach comes with its own limitations—partial volume effects and radiometabolite correction among the most important—and varying rates of success, and the use of IDIF for brain PET has been particularly troublesome. Main body This paper summarizes the limitations of IDIF methods for quantitative PET imaging and discusses some of the advances that may make IDIF extraction more reliable. The introduction of automated pipelines (both commercial and open-source) for clinical PET scanners is discussed as a way to improve the reliability of IDIF approaches and their utility for quantitative purposes. Survey data gathered from the PET community are then presented to understand whether the field’s opinion of the usefulness and validity of IDIF is improving. Finally, as the introduction of next-generation PET scanners with long axial fields of view, ultra-high sensitivity, and improved spatial and temporal resolution, has also brought IDIF methods back into the spotlight, a discussion of the possibilities offered by these state-of-the-art scanners—inclusion of large vessels, less partial volume in small vessels, better description of the full IDIF kinetics, whole-body modeling of radiometabolite production—is included, providing a pathway for future use of IDIF. Conclusion Improvements in PET scanner technology and software for automated IDIF extraction may allow to solve some of the major limitations associated with IDIF, such as partial volume effects and poor temporal sampling, with the exciting potential for accurate estimation of single kinetic rates. Nevertheless, until individualized radiometabolite correction can be performed effectively, IDIF approaches remain confined at best to a few tracers.

Abstract Background Antiepileptic drugs, levetiracetam (LEV) and brivaracetam (BRV), bind to synaptic vesicle glycoprotein 2A (SV2A). In their anti-seizure activity, speed of brain entry may be an important factor. BRV showed faster entry into the human and non-human primate brain, based on more rapid displacement of SV2A tracer 11C-UCB-J. To extract additional information from previous human studies, we developed a nonlinear model that accounted for drug entry into the brain and binding to SV2A using brain 11C-UCB-J positron emission tomography (PET) data and the time-varying plasma drug concentration, to assess the kinetic parameter K 1 (brain entry rate) of the drugs. Method Displacement (LEV or BRV p.i. 60 min post-tracer injection) and post-dose scans were conducted in five healthy subjects. Blood samples were collected for measurement of drug concentration and the tracer arterial input function. Fitting of nonlinear differential equations was applied simultaneously to time-activity curves (TACs) from displacement and post-dose scans to estimate 5 parameters: K 1 (drug), K 1(11C-UCB-J, displacement), K 1(11C-UCB-J, post-dose), free fraction of 11C-UCB-J in brain (f ND(11C-UCB-J)), and distribution volume of 11C-UCB-J (V T(UCB-J)). Other parameters (K D(drug), K D(11C-UCB-J), f P(drug), f P(11C-UCB-J, displacement), f P(11C-UCB-J, post-dose), f ND(drug), k off(drug), k off(11C-UCB-J)) were fixed to literature or measured values. Results The proposed model described well the TACs in all subjects; however, estimates of drug K 1 were unstable in comparison with 11C-UCB-J K 1 estimation. To provide a conservative estimate of the relative speed of brain entry for BRV vs. LEV, we determined a lower bound on the ratio BRV K 1/LEV K 1, by finding the lowest BRV K 1 or highest LEV K 1 that were statistically consistent with the data. Specifically, we used the F test to compare the residual sum of squares with fixed BRV K 1 to that with floating BRV K 1 to obtain the lowest possible BRV K 1; the same analysis was performed to find the highest LEV K 1. The lower bound of the ratio BRV K 1/LEV K 1 was ~ 7. Conclusions Under appropriate conditions, this advanced nonlinear model can directly estimate entry rates of drugs into tissue by analysis of PET TACs. Using a conservative statistical cutoff, BRV enters the brain at least sevenfold faster than LEV.

Changes to structural and functional connectivity can give rise to neurodegeneration and neurodevelopmental diseases. Here the authors investigate molecular and connectomic patterns in 13 different neurological, psychiatric and neurodevelopmental diseases from the ENIGMA consortium.

Abstract Purpose Neuronal damage and synapse loss in the spinal cord (SC) have been implicated in spinal cord injury (SCI) and neurodegenerative disorders such as Amyotrophic Lateral Sclerosis (ALS). Current standards of diagnosis for SCI include CT or MRI imaging to evaluate injury severity. The current study explores the use of PET imaging with [11C]UCB-J, which targets the synaptic vesicle protein 2A (SV2A), in the human spinal cord, as a way to visualize synaptic density and integrity in vivo. Results First, simulations of baseline and blocking [11C]UCB-J HRRT scans were performed, based on SC dimensions and SV2A distribution to predict V T, V ND, and V S values. Next, human baseline and blocking [11C]UCB-J HRRT images were used to estimate these values in the cervical SC (cSC). Simulation results had excellent agreement with observed values of V T, V ND, and V S from the real human data, with baseline V T, V ND, and V S of 3.07, 2.15, and 0.92 mL/cm3, respectively, with a BP ND of 0.43. Lastly, we explored full SC imaging with whole-body images. Using automated SC regions of interest (ROIs) for the full SC, cSC, and thoracic SC (tSC), the distribution volume ratio (DVR) was estimated using the brain gray matter as a reference region to evaluate SC SV2A density relative to the brain. In full body imaging, DVR values of full SC, cSC, and tSC were 0.115, 0.145, and 0.112, respectively. Therefore, measured [11C]UCB-J uptake, and thus SV2A density, is much lower in the SC than in the brain. Conclusions The results presented here provide evidence for the feasibility of SV2A PET imaging in the human SC, however, specific binding of [11C]UCB-J is low. Ongoing and future work include further classification of SV2A distribution in the SC as well as exploring higher-affinity PET radioligands for SC imaging.

Introduction: Resting-state network (RSN) connectivity is a widely used measure of the brain’s functional organization in health and disease; however, little is known regarding the underlying neurophysiology of RSNs. The aim of the current study was to investigate associations between RSN connectivity and synaptic density assessed using the synaptic vesicle glycoprotein 2A radioligand 11C-UCB-J PET.Methods: Independent component analyses (ICA) were performed on resting-state fMRI and PET data from 34 healthy adult participants (16F, mean age: 46 ± 15 years) to identify a priori RSNs of interest (default-mode, right frontoparietal executive-control, salience, and sensorimotor networks) and select sources of 11C-UCB-J variability (medial prefrontal, striatal, and medial parietal). Pairwise correlations were performed to examine potential intermodal associations between the fractional amplitude of low-frequency fluctuations (fALFF) of RSNs and subject loadings of 11C-UCB-J source networks both locally and along known anatomical and functional pathways.Results: Greater medial prefrontal synaptic density was associated with greater fALFF of the anterior default-mode, posterior default-mode, and executive-control networks. Greater striatal synaptic density was associated with greater fALFF of the anterior default-mode and salience networks. Post-hoc mediation analyses exploring relationships between aging, synaptic density, and RSN activity revealed a significant indirect effect of greater age on fALFF of the anterior default-mode network mediated by the medial prefrontal 11C-UCB-J source.Discussion: RSN functional connectivity may be linked to synaptic architecture through multiple local and circuit-based associations. Findings regarding healthy aging, lower prefrontal synaptic density, and lower default-mode activity provide initial evidence of a neurophysiological link between RSN activity and local synaptic density, which may have relevance in neurodegenerative and psychiatric disorders.

IntroductionSynapse loss is one of the hallmarks of Alzheimer's disease (AD) and is associated with cognitive decline. In this study, we tested [18F]SDM-16, a novel metabolically stable SV2A PET imaging probe, in the transgenic APPswe/PS1dE9 (APP/PS1) mouse model of AD and age-matched wild-type (WT) mice at 12 months of age.MethodsBased on previous preclinical PET imaging studies using [11C]UCB-J and [18F]SynVesT-1 in the same strain animals, we used the simplified reference tissue model (SRTM), with brain stem as the pseudo reference region to calculate distribution volume ratios (DVRs).ResultsTo simplify and streamline the quantitative analysis, we compared the standardized uptake value ratios (SUVRs) from different imaging windows to DVRs and found that the averaged SUVRs from 60–90 min post-injection (p.i.) are most consistent with the DVRs. Thus, we used averaged SUVRs from 60–90 min for group comparisons and found statistically significant differences in the tracer uptake in different brain regions, e.g., hippocampus (p = 0.001), striatum (p = 0.002), thalamus (p = 0.003), and cingulate cortex (p = 0.0003).ConclusionsIn conclusion, [18F]SDM-16 was used to detect decreased SV2A levels in the brain of APP/PS1 AD mouse model at one year old. Our data suggest that [18F]SDM-16 has similar statistical power in detecting the synapse loss in APP/PS1 mice as [11C]UCB-J and [18F]SynVesT-1, albeit later imaging window (60–90 min p.i.) is needed when SUVR is used as a surrogate for DVR for [18F]SDM-16 due to its slower brain kinetics.

Abstract Background Monoacylglycerol lipase (MAGL) is a key serine hydrolase which terminates endocannabinoid signaling and regulates arachidonic acid driven inflammatory responses within the central nervous system. To develop [11C]PF-06809247 into a clinically usable MAGL positron emission tomography (PET) radioligand, we assessed the occupancy of MAGL by an inhibitor in the non-human primate (NHP) brain. Additionally, we measured the whole-body distribution of [11C]PF-06809247 in NHP and estimated human effective radiation doses. Methods Seven cynomolgus monkeys were enrolled for brain PET measurements. Two PET measurements along with arterial blood sampling were performed in each NHP: one baseline and one pretreatment condition with intravenous administration of PF-06818883, a pro-drug of a selective MAGL inhibitor (total of seven doses between 0.01 and 1.27 mg/kg). Kinetic parameters K 1, k 2 and k 3 were estimated by a two tissue compartment (2TC) model using metabolite corrected plasma radioactivity as the input function. k 4 was set as 0 according to the irreversible binding of [11C]PF-06809247. K i by 2TC and Patlak analysis were calculated as the influx constant. The target occupancy was calculated using K i at baseline and pretreatment conditions. Two cynomolgus monkeys were enrolled for whole-body PET measurements. Estimates of the absorbed radiation dose in humans were calculated with OLINDA/EXM 1.1 using the adult male reference model. Results Radioactivity retention was decreased in all brain regions following pretreatment with PF-06818883. Occupancy was measured as 25.4–100.5% in a dose dependent manner. Whole-body PET showed high radioactivity uptake values in the liver, small intestine, kidney, and brain. The effective dose of [11C]PF-06809247 was calculated as 4.3 μSv/MBq. Conclusions [11C]PF-06809247 is a promising PET ligand for further studies of MAGL in the human brain.

The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets, serving not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data, also known as PET-BIDS, and share several open-access datasets curated following PET-BIDS along with tools for conversion, validation and analysis of PET-BIDS datasets.

Background: Synaptic loss is considered an early pathological event and major structural correlate of cognitive impairment in Alzheimer’s disease (AD). We used principal component analysis (PCA) to identify regional patterns of covariance in synaptic density using [11C]UCB-J PET and assessed the association between principal components (PC) subject scores with cognitive performance. Methods: [11C]UCB-J binding was measured in 45 amyloid + participants with AD and 19 amyloid– cognitively normal participants aged 55–85. A validated neuropsychological battery assessed performance across five cognitive domains. PCA was applied to the pooled sample using distribution volume ratios (DVR) standardized (z-scored) by region from 42 bilateral regions of interest (ROI). Results: Parallel analysis determined three significant PCs explaining 70.2% of the total variance. PC1 was characterized by positive loadings with similar contributions across the majority of ROIs. PC2 was characterized by positive and negative loadings with strongest contributions from subcortical and parietooccipital cortical regions, respectively, while PC3 was characterized by positive and negative loadings with strongest contributions from rostral and caudal cortical regions, respectively. Within the AD group, PC1 subject scores were positively correlated with performance across all cognitive domains (Pearson r = 0.24–0.40, P = 0.06–0.006), PC2 subject scores were inversely correlated with age (Pearson r = -0.45, P = 0.002) and PC3 subject scores were significantly correlated with CDR-sb (Pearson r = 0.46, P = 0.04). No significant correlations were observed between cognitive performance and PC subject scores in CN participants. Conclusions: This data-driven approach defined specific spatial patterns of synaptic density correlated with unique participant characteristics within the AD group. Our findings reinforce synaptic density as a robust biomarker of disease presence and severity in the early stages of AD.

Abstract Preclinical studies have implicated kappa opioid receptors (KORs) in stress responses and depression-related behaviors, but evidence from human studies is limited. Here we present results of a secondary analysis of data acquired using positron emission tomography (PET) with the KOR radiotracer [11C]GR103545 in 10 unmedicated, currently depressed individuals with major depressive disorder (MDD; 32.6 ± 6.5 years, 5 women) and 13 healthy volunteers (34.8 ± 10 years, 6 women). Independent component analysis was performed to identify spatial patterns of coherent variance in KOR binding (tracer volume of distribution, V T) across all subjects. Expression of each component was compared between groups and relationships to symptoms were explored using the 17-item Hamilton Depression Rating Scale (HDRS). Three components of variation in KOR availability across ROIs were identified, spatially characterized by [11C]GR103545 V T in (1) bilateral frontal lobe; (2) occipital and parietal cortices, right hippocampus, and putamen; and (3) right anterior cingulate, right superior frontal gyrus and insula, coupled to negative loading in left middle cingulate. In MDD patients, component 3 was negatively associated with symptom severity on the HDRS (r = −0.85, p = 0.0021). There were no group-wise differences in expression of any component between patients and controls. These preliminary findings suggest that KOR signaling in cortical regions relevant to depression, particularly right anterior cingulate, could reflect MDD pathophysiology.

Head motion presents a continuing problem in brain PET studies. A wealth of motion correction (MC) algorithms had been proposed in the past, including both hardware-based methods and data-driven methods. However, in most real brain PET studies, in the absence of ground truth or gold standard of motion information, it is challenging to objectively evaluate MC quality. For MC evaluation, image-domain metrics, e.g., standardized uptake value (SUV) change before and after MC are commonly used, but this measure lacks objectivity because 1) other factors, e.g., attenuation correction, scatter correction and parameters used in the reconstruction, will confound MC effectiveness; 2) SUV only reflects final image quality, and it cannot precisely inform when an MC method performed well or poorly during the scan time period; 3) SUV is tracer-dependent and head motion may cause increases or decreases in SUV for different tracers, so evaluating MC effectiveness is complicated. Here, we present a new algorithm, i.e., motion corrected centroid-of-distribution (MCCOD) to perform objective quality control for measured or estimated rigid motion information. MCCOD is a three-dimensional surrogate trace of the center of tracer distribution after performing rigid MC using the existing motion information. MCCOD is used to inform whether the motion information is accurate, using the PET raw data only, i.e., without PET image reconstruction, where inaccurate motion information typically leads to abrupt changes in the MCCOD trace. MCCOD was validated using simulation studies and was tested on real studies acquired from both time-of-flight (TOF) and non-TOF scanners. A deep learning-based brain mask segmentation was implemented, which is shown to be necessary for non-TOF MCCOD generation. MCCOD is shown to be effective in detecting abrupt translation motion errors in slowly varying tracer distribution caused by the motion tracking hardware and can be used to compare different motion estimation methods as well as to improve existing motion information.

Brain cannabinoid 1 receptors (CB1Rs) contribute importantly to the regulation of autonomic tone, appetite, mood and cognition. Inconsistent results have been reported from positron emission tomography (PET) studies using different radioligands to examine relationships between age, gender and body mass index (BMI) and CB1R availability in healthy individuals. In this study, we examined these variables in 58 healthy individuals (age range: 18–55 years; 44 male; BMI=27.01±5.56), the largest cohort of subjects studied to date using the CB1R PET ligand [11C]OMAR. There was a significant decline in CB1R availability (VT) with age in the pallidum, cerebellum and posterior cingulate. Adjusting for BMI, age-related decline in VT remained significant in the posterior cingulate among males, and in the cerebellum among women. CB1R availability was higher in women compared to men in the thalamus, pallidum and posterior cingulate. Adjusting for age, CB1R availability negatively correlated with BMI in women but not men. These findings differ from those reported using [11C]OMAR and other radioligands such as [18F]FMPEP-d2 and [18F]MK-9470. Although reasons for these seemingly divergent findings are unclear, the choice of PET radioligand and range of BMI in the current dataset may contribute to the observed differences. This study highlights the need for cross-validation studies using both [11C]OMAR and [18F]FMPEP-d2 within the same cohort of subjects.

Head motion during PET scans causes image quality degradation, decreased concentration in regions with high uptake and incorrect outcome measures from kinetic analysis of dynamic datasets. Previously, we proposed a data-driven method, center of tracer distribution (COD), to detect head motion without an external motion tracking device. There, motion was detected using one dimension of the COD trace with a semiautomatic detection algorithm, requiring multiple user defined parameters and manual intervention. In this study, we developed a new data-driven motion detection algorithm, which is automatic, self-adaptive to noise level, does not require user-defined parameters and uses all three dimensions of the COD trace (3DCOD). 3DCOD was first validated and tested using 30 simulation studies (18F-FDG, N = 15; 11C-raclopride (RAC), N = 15) with large motion. The proposed motion correction method was tested on 22 real human datasets, with 20 acquired from a high resolution research tomograph (HRRT) scanner (18F-FDG, N = 10; 11C-RAC, N = 10) and 2 acquired from the Siemens Biograph mCT scanner. Real-time hardware-based motion tracking information (Vicra) was available for all real studies and was used as the gold standard. 3DCOD was compared to Vicra, no motion correction (NMC), one-direction COD (our previous method called 1DCOD) and two conventional frame-based image registration (FIR) algorithms, i.e., FIR1 (based on predefined frames reconstructed with attenuation correction) and FIR2 (without attenuation correction) for both simulation and real studies. For the simulation studies, 3DCOD yielded -2.3 ± 1.4% (mean ± standard deviation across all subjects and 11 brain regions) error in region of interest (ROI) uptake for 18F-FDG (-3.4 ± 1.7% for 11C-RAC across all subjects and 2 regions) as compared to Vicra (perfect correction) while NMC, FIR1, FIR2 and 1DCOD yielded -25.4 ± 11.1% (-34.5 ± 16.1% for 11C- RAC), -13.4 ± 3.5% (-16.1 ± 4.6%), -5.7 ± 3.6% (-8.0 ± 4.5%) and -2.6 ± 1.5% (-5.1 ± 2.7%), respectively. For real HRRT studies, 3DCOD yielded -0.3 ± 2.8% difference for 18F-FDG (-0.4 ± 3.2% for 11C-RAC) as compared to Vicra while NMC, FIR1, FIR2 and 1DCOD yielded -14.9 ± 9.0% (-24.5 ± 14.6%), -3.6 ± 4.9% (-13.4 ± 14.3%), -0.6 ± 3.4% (-6.7 ± 5.3%) and -1.5 ± 4.2% (-2.2 ± 4.1%), respectively. In summary, the proposed motion correction method yielded comparable performance to the hardware-based motion tracking method for multiple tracers, including very challenging cases with large frequent head motion, in studies performed on a non-TOF scanner.

Abstract Background Attempts to associate amyloid-β (Aβ) pathogenesis with synaptic loss in Alzheimer’s disease (AD) have thus far been limited to small numbers of postmortem studies. Aβ plaque burden is not well-correlated with indices of clinical severity or neurodegeneration—at least in the dementia stage—as deposition of Aβ reaches a ceiling. In this study, we examined in vivo the association between fibrillar Aβ deposition and synaptic density in early AD using positron emission tomography (PET). We hypothesized that global Aβ deposition would be more strongly inversely associated with hippocampal synaptic density in participants with amnestic mild cognitive impairment (aMCI; a stage of continued Aβ accumulation) compared to those with dementia (a stage of relative Aβ plateau). Methods We measured SV2A binding ([11C]UCB-J) and Aβ deposition ([11C]PiB) in 14 participants with aMCI due to AD and 24 participants with mild AD dementia. Distribution volume ratios (DVR) with a cerebellar reference region were calculated for both tracers to investigate the association between global Aβ deposition and SV2A binding in hippocampus. Exploratory analyses examined correlations between both global and regional Aβ deposition and SV2A binding across a broad range of brain regions using both ROI- and surface-based approaches. Results We observed a significant inverse association between global Aβ deposition and hippocampal SV2A binding in participants with aMCI (r = − 0.55, P = 0.04), but not mild dementia (r = 0.05, P = 0.82; difference statistically significant by Fisher z = − 1.80, P = 0.04). Exploratory analyses across other ROIs and whole brain analyses demonstrated no broad or consistent associations between global Aβ deposition and regional SV2A binding in either diagnostic group. ROI-based analyses of the association between regional Aβ deposition and SV2A binding also revealed no consistent pattern but suggested a “paradoxical” positive association between local Aβ deposition and SV2A binding in the hippocampus. Conclusions Our findings lend support to a model in which fibrillar Aβ is still accumulating in the early stages of clinical disease but approaching a relative plateau, a point at which Aβ may uncouple from neurodegenerative processes including synaptic loss. Future research should investigate the relationship between Aβ deposition and synaptic loss in larger cohorts beginning preclinically and followed longitudinally in conjunction with other biomarkers.

PurposeTo assess the pathological aging effect on caudate functional connectivity among mild cognitive impairment (MCI) participants and examine whether and how sex and amyloid contribute to this process.Materials and MethodsTwo hundred and seventy-seven functional magnetic resonance imaging (fMRI) sessions from 163 cognitive normal (CN) older adults and 309 sessions from 139 participants with MCI were included as the main sample in our analysis. Pearson's correlation was used to characterize the functional connectivity (FC) between caudate nuclei and each brain region, then caudate nodal strength was computed to quantify the overall caudate FC strength. Association analysis between caudate nodal strength and age was carried out in MCI and CN separately using linear mixed effect (LME) model with covariates (education, handedness, sex, Apolipoprotein E4, and intra-subject effect). Analysis of covariance was conducted to investigate sex, amyloid status, and their interaction effects on aging with the fMRI data subset having amyloid status available. LME model was applied to women and men separately within MCI group to evaluate aging effects on caudate nodal strength and each region's connectivity with caudate nuclei. We then evaluated the roles of sex and amyloid status in the associations of neuropsychological scores with age or caudate nodal strength. An independent cohort was used to validate the sex-dependent aging effects in MCI.ResultsThe MCI group had significantly stronger age-related increase of caudate nodal strength compared to the CN group. Analyzing women and men separately revealed that the aging effect on caudate nodal strength among MCI participants was significant only for women (left: P = 6.23 × 10−7, right: P = 3.37 × 10−8), but not for men (P > 0.3 for bilateral caudate nuclei). The aging effects on caudate nodal strength were not significantly mediated by brain amyloid burden. Caudate connectivity with ventral prefrontal cortex substantially contributed to the aging effect on caudate nodal strength in women with MCI. Higher caudate nodal strength is significantly related to worse cognitive performance in women but not in men with MCI.ConclusionSex modulates the pathological aging effects on caudate nodal strength in MCI regardless of amyloid status. Caudate nodal strength may be a sensitive biomarker of pathological aging in women with MCI.

The development of novel PET imaging agents for synaptic vesicle glycoprotein 2A (SV2A) allowed for the in vivo detection of synaptic density changes, which are correlated with the progression and severity of a variety of neuropsychiatric diseases. While multiple ongoing clinical investigations using SV2A PET are expanding its applications rapidly, preclinical SV2A PET imaging in animal models is an integral component of the translation research and provides supporting and complementary information. Herein, we overview preclinical SV2A PET studies in animal models of neurodegenerative disorders and discuss the opportunities and practical challenges in small animal SV2A PET imaging. At the Yale PET Center, we have conducted SV2A PET imaging studies in animal models of multiple diseases and longitudinal SV2A PET allowed us to evaluate synaptic density dynamics in the brains of disease animal models and to assess pharmacological effects of novel interventions. In this article, we discuss key considerations when designing preclinical SV2A PET imaging studies and strategies for data analysis. Specifically, we compare the brain imaging characteristics of available SV2A tracers, i.e., [11C]UCB-J, [18F]SynVesT-1, [18F]SynVesT-2, and [18F]SDM-16, in rodent brains. We also discuss the limited spatial resolution of PET scanners for small brains and challenges of kinetic modeling. We then compare different injection routes and estimate the maximum throughput (i.e., number of animals) per radiotracer synthesis by taking into account the injectable volume for each injection method, injected mass, and radioactivity half-lives. In summary, this article provides a perspective for designing and analyzing SV2A PET imaging studies in small animals.

Abstract The ability to quantify synaptic density in vivo in human adults and adolescents is of vital importance to understanding neuropsychiatric disorders. Here, we performed whole-body scans to determine organ radiation dosimetry of 11C-UCB-J in humans. Methods Dynamic whole-body PET scans were performed in four healthy adults after injection of 11C-UCB-J. Regions of interest (ROIs) were drawn manually for the brain, heart, stomach, kidneys, liver, pancreas, spleen, gallbladder, lungs, urinary bladder, and intestines. ROIs were applied to dynamic images to generate time-activity curves (TACs). Decay correction was removed from TACs, and the area under the curve (AUC) for each ROI was calculated. AUCs were then normalized by injected activity and organ volumes to produce radioligand residence times for each organ. These times were then used as input into the OLINDA/EXM 1.0 software to determine the total radiation dose in each organ and the effective dose for these OLINDA models: 55-kg female, 70-kg male, and 15-year-old adolescent. Results Visual evaluation detected high uptake in the liver, brain, gallbladder, gastrointestinal tract, and urinary bladder. The dose-limiting organ was the urinary bladder for adult males (0.0224 mSv/MBq) and liver for adult females (0.0248 mSv/MBq) with single-study dose limits of 2239 MBq and 2017 MBq 11C-UCB-J, respectively. For adolescents, the large intestine was the dose-limiting organ (0.0266 mSv/MBq) with a single-study dose limit of 188 MBq. Conclusions 11C-UCB-J dosimetry in adults is consistent with those for many carbon-11-labeled ligands. Overall, 11C-UCB-J can be used safely in adolescents, as in adults, to measure synaptic density in various neuropsychiatric and other relevant disorders.

Neuroinflammation has been proposed to accompany the peripheral inflammation observed in PTSD. Here, authors find lower in vivo and postmortem levels of neuroimmune marker TSPO (translocator protein) in PTSD, in association with greater PTSD severity and higher plasma CRP.

Abstract Background Metabotropic glutamate subtype 5 receptors (mGluR5) modulate synaptic transmission and may constitute an important therapeutic target in Alzheimer’s disease (AD) by mediating the synaptotoxic action of amyloid-β oligomers. We utilized the positron emission tomography (PET) radioligand [18F]FPEB to investigate mGluR5 binding in early AD. Methods Sixteen individuals with amnestic mild cognitive impairment (MCI) due to AD or mild AD dementia who were positive for brain amyloid were compared to 15 cognitively normal (CN) participants who were negative for brain amyloid. Diagnostic groups were well balanced for age, sex, and education. Dynamic PET scans were acquired for 60 min, starting at 60 min after the initial administration of up to 185 MBq of [18F]FPEB using a bolus-plus-constant-infusion method (K bol = 190 min). Equilibrium modeling with a cerebellum reference region was used to estimate [18F]FPEB binding (BP ND) to mGluR5. Analyses were performed with and without corrections for gray matter atrophy and partial volume effects. Results Linear mixed model analysis demonstrated a significant effect of group (p = 0.011) and the group × region interaction (p = 0.0049) on BP ND. Post hoc comparisons revealed a significant reduction (43%) in mGluR5 binding in the hippocampus of AD (BP ND = 0.76 ± 0.41) compared to CN (BP ND = 1.34 ± 0.58, p = 0.003, unpaired t test) participants, and a nonsignificant trend for a reduction in a composite association cortical region in AD (BP ND = 1.57 ± 0.25) compared to CN (BP ND = 1.86 ± 0.63, p = 0.093) participants. Exploratory analyses suggested additional mGluR5 reductions in the entorhinal cortex and parahippocampal gyrus in the AD group. In the overall sample, hippocampal mGluR5 binding was associated with episodic memory scores and global function. Conclusions [18F]FPEB-PET revealed reductions in hippocampal mGluR5 binding in early AD. Quantification of mGluR5 binding in AD may expand our understanding of AD pathogenesis and accelerate the development of novel biomarkers and treatments.

Glycogen synthase kinase 3 (GSK-3) is a potential therapeutic target for a range of neurodegenerative and psychiatric disorders. The goal of this work was to evaluate two leading GSK-3 positron emission tomography (PET) radioligands, [11C]OCM-44 and [18F]OCM-50, in non-human primates to assess their potential for clinical translation. A total of nine PET scans were performed with the two radiotracers using arterial blood sampling in adult rhesus macaques. Brain regional time-activity curves were extracted and fitted with one- and two-tissue compartment models using metabolite-corrected arterial input functions. Target selectivity was assessed after pre-administration of the GSK-3 inhibitor PF-04802367 (PF-367, 0.03–0.25 mg/kg). Both radiotracers showed good brain uptake and distribution throughout grey matter. [11C]OCM-44 had a free fraction in the plasma of 3% at baseline and was metabolized quickly. The [11C]OCM-44 volume of distribution (VT) values in the brain increased with time; VT values from models fitted to truncated 60-min scan data were 1.4–2.9 mL/cm3 across brain regions. The plasma free fraction was 0.6% for [18F]OCM-50 and VT values (120-min) were 0.39–0.87 mL/cm3 in grey matter regions. After correcting for plasma free fraction increases during blocking scans, reductions in regional VT indicated >80% target occupancy by 0.1 mg/kg of PF-367 for both radiotracers, supporting target selectivity in vivo. [11C]OCM-44 and [18F]OCM-50 warrant further evaluation as radioligands for imaging GSK-3 in the brain, though radio-metabolite accumulation may confound image analysis.

Objective: Metabotropic glutamate receptor subtype 5 (mGluR5) is integral to the brain glutamatergic system and cognitive function. This study investigated whether aging is associated with decreased brain mGluR5 availability. Methods: Cognitively normal participants (n = 45), aged 18 to 84 years, underwent [18F]FPEB positron emission tomography scans to quantify brain mGluR5. Distribution volume (VT) was computed using a venous or arterial input function and equilibrium modeling from 90 to 120 min. In the primary analysis, the association between age and VT in the hippocampus and association cortex was evaluated using a linear mixed model. Exploratory analyses assessed the association between age and VT in multiple brain regions. The contribution of gray matter tissue alterations and partial volume effects to associations with age was also examined. Results: In the primary analysis, older age was associated with lower [18F]FPEB binding to mGluR5 (P = 0.026), whereas this association was not significant after gray matter masking or partial volume correction to account for age-related tissue loss. Post hoc analyses revealed an age-related decline in mGluR5 availability in the hippocampus of 4.5% per decade (P = 0.007) and a non-significant trend in the association cortex (P = 0.085). An exploratory analysis of multiple brain regions revealed broader inverse associations of age with mGluR5 availability, but not after partial volume correction. Conclusion: Reductions in mGluR5 availability with age appear to be largely mediated by tissue loss. Quantification of [18F]FPEB binding to mGluR5 may expand our understanding of age-related molecular changes and the relationship with brain tissue loss.

Purpose: 11C-UCB-J PET imaging, targeting synaptic vesicle glycoprotein 2A (SV2A), has been shown to be a useful indicator of synaptic density in Alzheimer's disease (AD). For SV2A imaging, a decrease in apparent tracer uptake is often due to the combination of gray-matter (GM) atrophy and SV2A decrease in the remaining tissue. Our aim is to reveal the true SV2A change by performing partial volume correction (PVC). Methods: We performed two PVC algorithms, Müller-Gärtner (MG) and ‘iterative Yang’ (IY), on 17 AD participants and 11 cognitive normal (CN) participants using the brain-dedicated HRRT scanner. Distribution volume VT, the rate constant K1, binding potential BPND (centrum semiovale as reference region), and tissue volume were compared. Results: In most regions, both PVC algorithms reduced the between-group differences. Alternatively, in hippocampus, IY increased the significance of between-group differences while MG reduced it (VT, BPND and K1 group differences: uncorrected: 20%, 27%, 17%; MG: 18%, 22%, 14%; IY: 22%, 28%, 17%). The group difference in hippocampal volume (10%) was substantially smaller than any PET measures. MG increased GM binding values to a greater extent than IY due to differences in algorithm assumptions. Conclusion: 11C-UCB-J binding is significantly reduced in AD hippocampus, but PVC is important to adjust for significant volume reduction. After correction, PET measures are substantially more sensitive to group differences than volumetric MRI measures. Assumptions of each PVC algorithm are important and should be carefully examined and validated. For 11C-UCB-J, the less stringent assumptions of IY support its use as a PVC algorithm over MG.

Background: The human brain is inherently organized into distinct networks, as reported widely by resting-state functional magnetic resonance imaging (rs-fMRI), which are based on blood-oxygen-level-dependent (BOLD) signal fluctuations. 11C-UCB-J PET maps synaptic density via synaptic vesicle protein 2A, which is a more direct structural measure underlying brain networks than BOLD rs-fMRI. Methods: The aim of this study was to identify maximally independent brain source networks, i.e., “spatial patterns with common covariance across subjects”, in 11C-UCB-J data using independent component analysis (ICA), a data-driven analysis method. Using a population of 80 healthy controls, we applied ICA to two 40-sample subsets and compared source network replication across samples. We examined the identified source networks at multiple model orders, as the ideal number of maximally independent components (IC) is unknown. In addition, we investigated the relationship between the strength of the loading weights for each source network and age and sex. Results: Thirteen source networks replicated across both samples. We determined that a model order of 18 components provided stable, replicable components, whereas estimations above 18 were not stable. Effects of sex were found in two ICs. Nine ICs showed age-related change, with 4 remaining significant after correction for multiple comparison. Conclusion: This study provides the first evidence that human brain synaptic density can be characterized into organized covariance patterns. Furthermore, we demonstrated that multiple synaptic density source networks are associated with age, which supports the potential utility of ICA to identify biologically relevant synaptic density source networks.

Lowered synaptic density is believed to occur in major depressive disorder and PTSD, possibly as an effect of stress. Here, the authors use positron emission tomography (PET) to measure levels of the synaptic marker SV2A and show that SV2A density is lower in those with more severe symptoms of depression.

Development of medications selective for dopamine D2 or D3 receptors is an active area of research in numerous neuropsychiatric disorders including addiction and Parkinson’s disease. The positron emission tomography (PET) radiotracer [11C]-(+)-PHNO, an agonist that binds with high affinity to both D2 and D3 receptors, has been used to estimate relative receptor subtype occupancy by drugs based on a priori knowledge of regional variation in the expression of D2 and D3 receptors. The objective of this work was to use a data-driven independent component analysis (ICA) of receptor blocking scans to separate D2-and D3-related signal in [11C]-(+)-PHNO binding data in order to improve the precision of subtype specific measurements of binding and occupancy. Eight healthy volunteers underwent [11C]-(+)-PHNO PET scans at baseline and at two time points following administration of the D3-preferring antagonist ABT-728 (150–1000 ​mg). Parametric binding potential (BPND) images were analyzed as four-dimensional image series using ICA to extract two independent sources of variation in [11C]-(+)-PHNO BPND. Spatial source maps for each component were consistent with respective regional patterns of D2-and D3-related binding. ICA-derived occupancy estimates from each component were similar to D2-and D3-specific occupancy estimated from a region-based approach (intraclass correlation coefficients ​> ​0.95). ICA-derived estimates of D3 receptor occupancy improved quality of fit to a single site binding model. Furthermore, ICA-derived estimates of the regional fraction of [11C]-(+)-PHNO binding related to D3 receptors was generated for each subject and values showed good agreement with region-based model estimates and prior literature values. In summary, ICA successfully separated D2-and D3-related components of the [11C]-(+)-PHNO binding signal, establishing this approach as a powerful data-driven method to quantify distinct biological features from PET data composed of mixed data sources. Editor highlights: • ICA of [11C]-(+)-PHNO PET competition binding data with a D3-selective drug. • Produced individual maps of D2-and D3-receptor binding patterns. • More precise D3 occupancy and EC50 estimates compared to conventional methods. • ICA offers a data-driven method to separate signals from multi-target PET tracers.

Abstract Background The 18-kDa translocator protein (TSPO) is an important target for assessing neuroimmune function in brain with positron-emission tomography (PET) imaging. The goal of this work was to assess two [11C]PBR28 imaging paradigms for measuring dynamic microglia changes in Macaca mulatta. Methods Dynamic [11C]PBR28 PET imaging data with arterial blood sampling were acquired to quantify TSPO levels as [11C]PBR28 V T. Scans were acquired at three timepoints: baseline, immediately post-drug, and prolonged post-drug. Results In one animal, a colony-stimulating factor 1 receptor kinase inhibitor, previously shown to deplete brain microglia, reduced [11C]PBR28 V T in brain by 46 ± 3% from baseline, which recovered after 12 days to 7 ± 5% from baseline. In a different animal, acute lipopolysaccharide administration, shown to activate brain microglia, increased [11C]PBR28 V T in brain by 39 ± 9% from baseline, which recovered after 14 days to −11 ± 3% from baseline. Conclusions These studies provide preliminary evidence of complementary paradigms to assess microglia dynamics via in vivo TSPO imaging.

Alzheimer's disease (AD), including its mild cognitive impairment (MCI) phase that may or may not progress into the AD, is the most ordinary form of dementia. It is extremely important to correctly identify patients during the MCI stage because this is the phase where AD may or may not develop. Thus, it is crucial to predict outcomes during this phase. Thus far, many researchers have worked on only using a single modality of a biomarker for the diagnosis of AD or MCI. Although recent studies show that a combination of one or more different biomarkers may provide complementary information for the diagnosis, it also increases the classification accuracy distinguishing between different groups. In this paper, we propose a novel machine learning-based framework to discriminate subjects with AD or MCI utilizing a combination of four different biomarkers: fluorodeoxyglucose positron emission tomography (FDG-PET), structural magnetic resonance imaging (sMRI), cerebrospinal fluid (CSF) protein levels, and Apolipoprotein-E (APOE) genotype. The Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset was used in this study. In total, there were 158 subjects for whom all four modalities of biomarker were available. Of the 158 subjects, 38 subjects were in the AD group, 82 subjects were in MCI groups (including 46 in MCIc [MCI converted; conversion to AD within 24 months of time period], and 36 in MCIs [MCI stable; no conversion to AD within 24 months of time period]), and the remaining 38 subjects were in the healthy control (HC) group. For each image, we extracted 246 regions of interest (as features) using the Brainnetome template image and NiftyReg toolbox, and later we combined these features with three CSF and two APOE genotype features obtained from the ADNI website for each subject using early fusion technique. Here, a different kernel-based multiclass support vector machine (SVM) classifier with a grid-search method was applied. Before passing the obtained features to the classifier, we have used truncated singular value decomposition (Truncated SVD) dimensionality reduction technique to reduce high dimensional features into a lower-dimensional feature. As a result, our combined method achieved an area under the receiver operating characteristic (AU-ROC) curve of 98.33, 93.59, 96.83, 94.64, 96.43, and 95.24% for AD vs. HC, MCIs vs. MCIc, AD vs. MCIs, AD vs. MCIc, HC vs. MCIc, and HC vs. MCIs subjects which are high relative to single modality results and other state-of-the-art approaches. Moreover, combined multimodal methods have improved the classification performance over the unimodal classification.

Mild cognitive impairment (MCI) is a transitional state between the cognitive changes in normal aging and Alzheimer’s disease (AD), which induces abnormalities in specific brain regions. Previous studies showed that paired helical filaments Tau (PHF-Tau) protein is a potential pathogenic protein which may cause abnormal brain function and structure in MCI and AD patients. However, the understanding of the PHF-Tau protein network in MCI patients is limited. In this study, 225 subjects with PHF-Tau Positron Emission Tomography (PET) images were divided into four groups based on whether they carried Apolipoprotein E ε4 (APOE 4) or abnormal cerebrospinal fluid Total-Tau (CSF T-Tau). They are two important pathogenic factors that might cause cognitive function impairment. The four groups were: individuals harboring CSF T-Tau pathology but no APOE 4 (APOE 4−T+); APOE 4 carriers with normal CSF T-Tau (APOE 4+T−); APOE 4 carriers with abnormal CSF T-Tau (APOE 4+T+); and APOE 4 noncarriers with abnormal CSF T-Tau (APOE 4−T−). We explored the topological organization of PHF-Tau networks in these four groups and calculated five kinds of network properties: clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Our findings showed that compared with APOE 4−T− group, the other three groups showed different alterations in the clustering coefficient, shortest path length, Q value of modularity, nodal centrality and degree. Simultaneously, voxel-level analysis was conducted and the results showed that compared with APOE 4−T− group, the other three groups were found increased PHF-Tau distribution in some brain regions. For APOE 4+T+ group, positive correlation was found between the value of PHF-Tau distribution in altered regions and Functional Assessment Questionnaire (FAQ) score. Our results indicated that the effects of APOE 4 and abnormal CSF T-Tau may induce abnormalities of PHF-Tau protein and APOE 4 has a greater impact on PHF-Tau than abnormal CSF T-Tau. Our results may be particularly helpful in uncovering the pathophysiology underlying the cognitive dysfunction in MCI patients.

BackgroundNon-invasive brain stimulation (NIBS) has been widely used to treat mild cognitive impairment (MCI). However, there exists no consensus on the best stimulation sites.ObjectiveTo explore potential stimulation locations for NIBS treatment in patients with MCI, combining meta- and resting state functional connectivity (rsFC) analyses.MethodsThe meta-analysis was conducted to identify brain regions associated with MCI. Regions of interest (ROIs) were extracted based on this meta-analysis. The rsFC analysis was applied to 45 MCI patients to determine brain surface regions that are functionally connected with the above ROIs.ResultsWe found that the dorsolateral prefrontal cortex (DLPFC) and inferior frontal gyrus (IFG) were the overlapping brain regions between our results and those of previous studies. In addition, we recommend that the temporoparietal junction (including the angular gyrus), which was found in both the meta- and rsFC analysis, should be considered in NIBS treatment of MCI. Furthermore, the bilateral orbital prefrontal gyrus, inferior temporal gyrus, medial superior frontal gyrus, and right inferior occipital gyrus may be potential brain stimulation sites for NIBS treatment of MCI.ConclusionOur results provide several potential sites for NIBS, such as the DLFPC and IFG, and may shed light on the locations of NIBS sites in the treatment of patients with MCI.

Collecting multiple modalities of neuroimaging data on the same subject is increasingly becoming the norm in clinical practice and research. Fusing multiple modalities to find related patterns is a challenge in neuroimaging analysis. Canonical correlation analysis (CCA) is commonly used as a symmetric data fusion technique to find related patterns among multiple modalities. In CCA-based data fusion, principal component analysis (PCA) is frequently applied as a preprocessing step to reduce data dimension followed by CCA on dimension-reduced data. PCA, however, does not differentiate between informative voxels from non-informative voxels in the dimension reduction step. Sparse PCA (sPCA) extends traditional PCA by adding sparse regularization that assigns zero weights to non-informative voxels. In this study, sPCA is incorporated into CCA-based fusion analysis and applied on neuroimaging data. A cross-validation method is developed and validated to optimize the parameters in sPCA. Different simulations are carried out to evaluate the improvement by introducing sparsity constraint to PCA. Four fusion methods including sPCA+CCA, PCA+CCA, parallel ICA and sparse CCA were applied on structural and functional magnetic resonance imaging data of mild cognitive impairment subjects and normal controls. Our results indicate that sPCA significantly can reduce the impact of non-informative voxels and lead to improved statistical power in uncovering disease-related patterns by a fusion analysis.

Recent developments of tau Positron Emission Tomography (PET) allows assessment of regional neurofibrillary tangles (NFTs) deposition in human brain. Among the tau PET molecular probes, 18F-AV1451 is characterized by high selectivity for pathologic tau aggregates over amyloid plaques, limited non-specific binding in white and gray matter, and confined off-target binding. The objectives of the study are (1) to quantitatively characterize regional brain tau deposition measured by 18F-AV1451 PET in cognitively normal older adults (CN), mild cognitive impairment (MCI), and AD participants; (2) to evaluate the correlations between cerebrospinal fluid (CSF) biomarkers or Mini-Mental State Examination (MMSE) and 18F-AV1451 PET standardized uptake value ratio (SUVR); and (3) to evaluate the partial volume effects on 18F-AV1451 brain uptake.Methods: The study included total 115 participants (CN = 49, MCI = 58, and AD = 8) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Preprocessed 18F-AV1451 PET images, structural MRIs, and demographic and clinical assessments were downloaded from the ADNI database. A reblurred Van Cittertiteration method was used for voxelwise partial volume correction (PVC) on PET images. Structural MRIs were used for PET spatial normalization and region of interest (ROI) definition in standard space. The parametric images of 18F-AV1451 SUVR relative to cerebellum were calculated. The ROI SUVR measurements from PVC and non-PVC SUVR images were compared. The correlation between ROI 18F-AV1451 SUVR and the measurements of MMSE, CSF total tau (t-tau), and phosphorylated tau (p-tau) were also assessed.Results:18F-AV1451 prominently specific binding was found in the amygdala, entorhinal cortex, parahippocampus, fusiform, posterior cingulate, temporal, parietal, and frontal brain regions. Most regional SUVRs showed significantly higher uptake of 18F-AV1451 in AD than MCI and CN participants. SUVRs of small regions like amygdala, entorhinal cortex and parahippocampus were statistically improved by PVC in all groups (p < 0.01). Although there was an increasing tendency of 18F-AV-1451 SUVRs in MCI group compared with CN group, no significant difference of 18F-AV1451 deposition was found between CN and MCI brains with or without PVC (p > 0.05). Declined MMSE score was observed with increasing 18F-AV1451 binding in amygdala, entorhinal cortex, parahippocampus, and fusiform. CSF p-tau was positively correlated with 18F-AV1451 deposition. PVC improved the results of 18F-AV-1451 tau deposition and correlation studies in small brain regions.Conclusion: The typical deposition of 18F-AV1451 tau PET imaging in AD brain was found in amygdala, entorhinal cortex, fusiform and parahippocampus, and these regions were strongly associated with cognitive impairment and CSF biomarkers. Although more deposition was observed in MCI group, the 18F-AV-1451 PET imaging could not differentiate the MCI patients from CN population. More tau deposition related to decreased MMSE score and increased level of CSF p-tau, especially in ROIs of amygdala, entorhinal cortex and parahippocampus. PVC did improve the results of tau deposition and correlation studies in small brain regions and suggest to be routinely used in 18F-AV1451 tau PET quantification.

The myriad physiological functions of γ-amino butyric acid (GABA) are mediated by the GABA-benzodiazepine receptor complex comprising of the GABA A , GABA B , and GABA C groups. The various GABA A subunits with region-specific distributions in the brain subserve different functional and physiological roles. For example, the sedative and anticonvulsive effects of classical benzodiazepines are attributed to the α 1 subunit, and the α 2 and α 3 subunits mediate the anxiolytic effect. To optimize pharmacotherapies with improved efficacy and devoid of undesirable side effects for the treatment of anxiety disorders, subtype-selective imaging radiotracers are required to assess target engagement at GABA sites and determine the dose–receptor occupancy relationships. The goal of this work was to characterize, in nonhuman primates, the in vivo binding profile of a novel positron emission tomography (PET) radiotracer, [ 11 C]ADO, which has been indicated to have functional selectivity for the GABA A α 2 /α 3 subunits. High specific activity [ 11 C]ADO was administrated to 3 rhesus monkeys, and PET scans of 120-minute duration were performed on the Focus-220 scanner. In the blood, [ 11 C]ADO metabolized at a fairly rapid rate, with ∼36% of the parent tracer remaining at 30 minutes postinjection. Uptake levels of [ 11 C]ADO in the brain were high (peak standardized uptake value of ∼3.0) and consistent with GABA A distribution, with highest activity levels in cortical areas, intermediate levels in cerebellum and thalamus, and lowest uptake in striatal regions and amygdala. Tissue kinetics was fast, with peak uptake in all brain regions within 20 minutes of tracer injection. The one-tissue compartment model provided good fits to regional time–activity curves and reliable measurement of kinetic parameters. The absolute test–retest variability of regional distribution volumes ( V T ) was low, ranging from 4.5% to 8.7%. Pretreatment with flumazenil (a subtype nonselective ligand, 0.2 mg/kg, intravenous [IV], n = 1), Ro15-4513 (an α 5 -selective ligand, 0.03 mg/kg, IV, n = 2), and zolpidem (an α 1 -selective ligand, 1.7 mg/kg, IV, n = 1) led to blockade of [ 11 C]ADO binding by 96.5%, 52.5%, and 76.5%, respectively, indicating the in vivo binding specificity of the radiotracer. Using the nondisplaceable volume of distribution ( V ND ) determined from the blocking studies, specific binding signals, as measured by values of regional binding potential ( BP ND ), ranged from 0.6 to 4.4, which are comparable to those of [ 11 C]flumazenil. In conclusion, [ 11 C]ADO was demonstrated to be a specific radiotracer for the GABA A receptors with several favorable properties: high brain uptake, fast tissue kinetics, and high levels of specific binding in nonhuman primates. However, subtype selectivity in vivo is not obvious for the radiotracer, and thus, the search for subtype-selective GABA A radiotracers continues.

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease.

Although there is growing evidence that estradiol modulates female perception of male sexual signals, relatively little research has focused on female auditory processing. We used in vivo 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) imaging to examine the neuronal effects of estradiol and conspecific song in female house sparrows (Passer domesticus). We assessed brain glucose metabolism, a measure of neuronal activity, in females with empty implants, estradiol implants, and empty implants ~1 month after estradiol implant removal. Females were exposed to conspecific or heterospecific songs immediately prior to imaging. The activity of brain regions involved in auditory perception did not differ between females with empty implants exposed to conspecific vs. heterospecific song, but neuronal activity was significantly reduced in females with estradiol implants exposed to heterospecific song. Furthermore, our within-individual design revealed that changes in brain activity due to high estradiol were actually greater several weeks after peak hormone exposure. Overall, this study demonstrates that PET imaging is a powerful tool for assessing large-scale changes in brain activity in living songbirds, and suggests that after breeding is done, specific environmental and physiological cues are necessary for estradiol-stimulated females to lose the selectivity they display in neural response to conspecific song.