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Background: Amyloid-β (Aβ) PET has emerged as clinically useful for more accurate diagnosis of patients with cognitive decline. Aβ deposition is a necessary cause or response to the cellular pathology of Alzheimer's disease (AD). Usual clinical and research interpretation of amyloid PET does not fully utilise all information regarding the spatial distribution of signal. We present a data-driven, spatially informed classifier to boost the diagnostic power of amyloid PET in AD. Methods: Voxel-wise k-means clustering of amyloid-positive voxels was performed; clusters were mapped to brain anatomy and tested for their associations by diagnostic category and disease severity with 758 amyloid PET scans from volunteers in the AD continuum from the Alzheimer's Disease Neuroimaging Initiative (ADNI). A machine learning approach based on this spatially constrained model using an optimised quadratic support vector machine was developed for automatic classification of scans for AD vs non-AD pathology. Results: This classifier boosted the accuracy of classification of AD scans to 81% using the amyloid PET alone with an area under the curve (AUC) of 0.91 compared to other spatial methods. This increased sensitivity to detect AD by 15% and the AUC by 9% compared to the use of a composite region of interest SUVr. Conclusions: The diagnostic classification accuracy of amyloid PET was improved using an automated data-driven spatial classifier. Our classifier highlights the importance of considering the spatial variation in Aβ PET signal for optimal interpretation of scans. The algorithm now is available to be evaluated prospectively as a tool for automated clinical decision support in research settings. [ABSTRACT FROM AUTHOR]

The current rise in the prevalence of magnetic resonance spectroscopy experiments to measure γ-aminobutyric acid in the living human brain is an exciting and productive area of research. As research spreads into clinical populations and cognitive research, it is important to fully understand the source of the magnetic resonance spectroscopy signal and apply appropriate interpretation to the results of the experiments. γ-aminobutyric acid is present in the brain not only as a neurotransmitter, but also in high intracellular concentrations, both as a transmitter precursor and a metabolite. γ-aminobutyric acid concentrations measured by magnetic resonance spectroscopy are not necessarily implicated in neurotransmission and therefore may reflect a very different brain activity to that commonly suggested. In this perspective, we examine some of the considerations to be taken in the interpretation of any γ-aminobutyric acid signal measured by magnetic resonance spectroscopy. [ABSTRACT FROM AUTHOR]

The rewarding properties of some abused drugs are thought to reside in their ability to increase striatal dopamine levels. Similar increases have been shown in response to expectation of a positive drug effect. The actions of opioid drugs on striatal dopamine release are less well characterized. We examined whether heroin and the expectation of heroin reward increases striatal dopamine levels in human opioid addiction. Ten opioid-dependent participants maintained on either methadone or buprenorphine underwent [(11) C]raclopride positron emission tomography imaging. Opioid-dependent participants were scanned three times, receiving reward from 50-mg intravenous heroin (diamorphine; pharmaceutical heroin) during the first scan to generate expectation of the same reward at the second scan, during which they only received 0.1-mg intravenous heroin. There was no heroin injection during the third scan. Intravenous 50-mg heroin during the first scan induced pronounced effects leading to high levels of expectation at the second scan. There was no detectable increase in striatal dopamine levels to either heroin reward or expectation of reward. We believe this is the first human study to examine whether expectation of heroin reward increases striatal dopamine levels in opioid addiction. The absence of detectable increased dopamine levels to both the expectation and delivery of a heroin-related reward may have been due to the impact of substitute medication. It does however contrast with the changes seen in abstinent stimulant users, suggesting that striatal dopamine release alone may not play such a pivotal role in opioid-maintained individuals. [ABSTRACT FROM AUTHOR]

The rewarding properties of some abused drugs are thought to reside in their ability to increase striatal dopamine levels. Similar increases have been shown in response to expectation of a positive drug effect. The actions of opioid drugs on striatal dopamine release are less well characterized. We examined whether heroin and the expectation of heroin reward increases striatal dopamine levels in human opioid addiction. Ten opioid-dependent participants maintained on either methadone or buprenorphine underwent [11 C]raclopride positron emission tomography imaging. Opioid-dependent participants were scanned three times, receiving reward from 50-mg intravenous heroin (diamorphine; pharmaceutical heroin) during the first scan to generate expectation of the same reward at the second scan, during which they only received 0.1-mg intravenous heroin. There was no heroin injection during the third scan. Intravenous 50-mg heroin during the first scan induced pronounced effects leading to high levels of expectation at the second scan. There was no detectable increase in striatal dopamine levels to either heroin reward or expectation of reward. We believe this is the first human study to examine whether expectation of heroin reward increases striatal dopamine levels in opioid addiction. The absence of detectable increased dopamine levels to both the expectation and delivery of a heroin-related reward may have been due to the impact of substitute medication. It does however contrast with the changes seen in abstinent stimulant users, suggesting that striatal dopamine release alone may not play such a pivotal role in opioid-maintained individuals. [ABSTRACT FROM AUTHOR]

Background: We measured whole body distribution of 11C-BU99008, a new PET biomarker for non-invasive identification of the imidazoline2 binding site. The purpose of this phase I study was to evaluate the biodistribution and radiation dosimetry of 11C-BU99008 in healthy human subjects.Methods: A single bolus injection of 11C-BU99008 (296 ± 10.5 MBq) was administered to four healthy subjects who underwent whole-body PET/CT over 120 min from the cranial vertex to the mid-thigh. Volumes of interest were drawn around visually identifiable source organs to generate time-activity curves (TAC). Residence times were determined from time-activity curves. Absorbed doses to individual organs and the whole body effective dose were calculated using OLINDA/EXM 1.1 for each subject.Results: The highest measured activity concentration was in the kidney and spleen. The longest residence time was in the muscle at 0.100 ± 0.023 h, followed by the liver at 0.067 ± 0.015 h and lungs at 0.052 ± 0.010 h. The highest mean organ absorbed dose was within the heart wall (0.028 ± 0.002 mGy/MBq), followed by the kidneys (0.026 ± 0.005 mGy/MBq). The critical organ was the heart wall. The total mean effective dose averaged over subjects was estimated to be 0.0056 ± 0.0004 mSv/MBq for an injection of 11C-BU99008.Conclusions: The biodistribution of 11C-BU99008 has been shown here for the first time in humans. Our dosimetry data showed the total mean effective dose over all subjects was 0.0056 ± 0.0004 mSv/MBq, which would result in a total effective dose of 1.96 mSv for a typical injection of 350 MBq of 11C-BU99008. The effective dose is not appreciably different from those obtained with other 11C tracers. [ABSTRACT FROM AUTHOR]

GABA A receptors containing the α5 subunit mediate tonic inhibition and are widely expressed in the limbic system. In animals, activation of α5-containing receptors impairs hippocampus-dependent memory. Temporal lobe epilepsy is associated with memory impairments related to neuron loss and other changes. The less selective PET ligand [ 11 C]flumazenil has revealed reductions in GABA A receptors. The hypothesis that α5 subunit receptor alterations are present in temporal lobe epilepsy and could contribute to impaired memory is untested. We compared α5 subunit availability between individuals with temporal lobe epilepsy and normal structural MRI ('MRI-negative') and healthy controls, and interrogated the relationship between α5 subunit availability and episodic memory performance, in a cross-sectional study. Twenty-three healthy male controls (median ± interquartile age 49 ± 13 years) and 11 individuals with MRI-negative temporal lobe epilepsy (seven males; 40 ± 8) had a 90-min PET scan after bolus injection of [ 11 C]Ro15-4513, with arterial blood sampling and metabolite correction. All those with epilepsy and six controls completed the Adult Memory and Information Processing Battery on the scanning day. 'Bandpass' exponential spectral analyses were used to calculate volumes of distribution separately for the fast component [ V F ; dominated by signal from α1 (α2, α3)-containing receptors] and the slow component ( V S ; dominated by signal from α5-containing receptors). We made voxel-by-voxel comparisons between: the epilepsy and control groups; each individual case versus the controls. We obtained parametric maps of V F and V S measures from a single bolus injection of [ 11 C]Ro15-4513. The epilepsy group had higher V S in anterior medial and lateral aspects of the temporal lobes, the anterior cingulate gyri, the presumed area tempestas (piriform cortex) and the insulae, in addition to increases of ∼24% and ∼26% in the ipsilateral and contralateral hippocampal areas ( P  < 0.004). This was associated with reduced V F : V S ratios within the same areas ( P  < 0.009). Comparisons of V S for each individual with epilepsy versus controls did not consistently lateralize the epileptogenic lobe. Memory scores were significantly lower in the epilepsy group than in controls (mean ± standard deviation -0.4 ± 1.0 versus 0.7 ± 0.3; P  = 0.02). In individuals with epilepsy, hippocampal V S did not correlate with memory performance on the Adult Memory and Information Processing Battery. They had reduced V F in the hippocampal area, which was significant ipsilaterally ( P  = 0.03), as expected from [ 11 C]flumazenil studies. We found increased tonic inhibitory neurotransmission in our cohort of MRI-negative temporal lobe epilepsy who also had co-morbid memory impairments. Our findings are consistent with a subunit shift from α1/2/3 to α5 in MRI-negative temporal lobe epilepsy., (© The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain.)

Though GABA is the major inhibitory neurotransmitter in the brain, involved in a wide variety of brain functions and many neuropsychiatric disorders, its intracellular and metabolic presence provides uncertainty in the interpretation of the GABA signal measured by (1)H-MRS. Previous studies demonstrating the sensitivity of this technique to pharmacological manipulations of GABA have used nonspecific challenges that make it difficult to infer the exact source of the changes. In this study, the synaptic GABA reuptake inhibitor tiagabine, which selectively blocks GAT1, was used to test the sensitivity of J-difference edited (1)H-MRS to changes in extracellular GABA concentrations. MEGA-PRESS was used to obtain GABA-edited spectra in 10 male individuals, before and after a 15-mg oral dose of tiagabine. In the three voxels measured, no significant changes were found in GABA+ concentration after the challenge compared to baseline. This dose of tiagabine is known to modulate synaptic GABA and neurotransmission through studies using other imaging modalities, and significant increases in self-reported sleepiness scales were observed. Therefore, it is concluded that recompartmentalization of GABA through transport block does not have a significant impact on total GABA concentration. Furthermore, it is likely that the majority of the magnetic resonance spectroscopy (MRS)-derived GABA signal is intracellular. It should be considered, in individual interpretation of GABA MRS studies, whether it is appropriate to attribute observed effects to changes in neurotransmission., (© 2014 Wiley Periodicals, Inc.)

This positron emission tomography (PET) study aimed to further define selectivity of [(11)C]Ro15-4513 binding to the GABARα5 relative to the GABARα1 benzodiazepine receptor subtype. The impact of zolpidem, a GABARα1-selective agonist, on [(11)C]Ro15-4513, which shows selectivity for GABARα5, and the nonselective benzodiazepine ligand [(11)C]flumazenil binding was assessed in humans. Compartmental modelling of the kinetics of [(11)C]Ro15-4513 time-activity curves was used to describe distribution volume (V(T)) differences in regions populated by different GABA receptor subtypes. Those with low α5 were best fitted by one-tissue compartment models; and those with high α5 required a more complex model. The heterogeneity between brain regions suggested spectral analysis as a more appropriate method to quantify binding as it does not a priori specify compartments. Spectral analysis revealed that zolpidem caused a significant V(T) decrease (~10%) in [(11)C]flumazenil, but no decrease in [(11)C]Ro15-4513 binding. Further analysis of [(11)C]Ro15-4513 kinetics revealed additional frequency components present in regions containing both α1 and α5 subtypes compared with those containing only α1. Zolpidem reduced one component (mean±s.d.: 71%±41%), presumed to reflect α1-subtype binding, but not another (13%±22%), presumed to reflect α5. The proposed method for [(11)C]Ro15-4513 analysis may allow more accurate selective binding assays and estimation of drug occupancy for other nonselective ligands.