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Abstract: The endocannabinoid system (ECS) is implicated as a regulator of homeostasis of several cerebral functions and is a novel target for drug treatment of neuropyschiatric disorders. So far, the cerebral cannabinoid-type 1 receptor (CB1R) has only been studied using in vitro, animal model, electrophysiological and post-mortem data. We have used positron emission tomography (PET) using a high-affinity, subtype-selective radioligand, [18F]MK-9470, to assess the in vivo cerebral CB1R distribution and its variation with healthy aging and gender. Fifty healthy volunteers (25 M/25 F, 18–69 years) underwent [18F]MK-9470 PET. Parametric [18F]MK-9470 binding maps were constructed, corrected for partial volume effects and analyzed using statistical parametric mapping in a combined categorical (gender) and covariate (age) design. We found that [18F]MK-9470 binding to CB1R increased with aging but only in women (p FWE<0.05, corrected for multiple comparisons); this was most pronounced in the basal ganglia, lateral temporal cortex and limbic system, especially in the hippocampus. Men showed higher [18F]MK-9470 binding then women (p <0.001, uncorrected), in clusters of the limbic system and cortico-striato-thalamic-cortical circuit. Region-dependent and gender-related upregulation of [18F]MK-9470 binding with aging is in line with ex vivo findings in rodent studies and may be associated with a changing homeostatic capacity or compensation mechanisms in the ECS that is modulated by sex hormones. In vivo PET of the CB1R will likely improve our understanding of the ECS in several neurological and psychiatric disorders. [Copyright &y& Elsevier]

Abstract: Increasing animal genetic, post-mortem and pharmacological evidence supports a role for the cerebral type 1 cannabinoid (CB1) receptor in the pathogenesis of schizophrenia (SCZ) and/or neural circuit dysfunctions responsible for its symptomatology. Moreover, since important interspecies differences are present in CB1 receptor expression, in vivo human data are of direct interest. We investigated an in vivo CB1 receptor expression in SCZ patients compared to healthy controls (CON), and in relation with psychopathological symptom severity using positron emission tomography (PET) and the selective high-affinity radioligand [18F]MK-9470. A total of sixty-seven patients with SCZ, with (SCZ-T, n=51) and without (SCZ-F, n=16) antipsychotic treatment, and 12 age and gender-matched CON were investigated with [18F]MK-9470 PET. Parametric modified standardized uptake value (mSUV) images, reflecting CB1 receptor binding, were compared and related to psychopathological symptoms. Compared to CON, there was a significant increase of CB1 receptor binding in SCZ patients in the nucleus accumbens, insula, cingulate cortex, inferior frontal cortex, parietal and mediotemporal lobe. Furthermore, in the SCZ-F group only, CB1 receptor binding was negatively correlated to negative symptoms and to depression scores, especially in the nucleus accumbens. Present findings strongly support that CB1 receptor binding is altered in the mesocorticolimbic circuitry of both SCZ-T and SCZ-F patients, especially in the nucleus accumbens. In SCZ-F patients, it is associated with negative symptoms and depression scores. [Copyright &y& Elsevier]

Abstract: 18F-flutemetamol is a positron emission tomography (PET) tracer for in vivo amyloid imaging. The ability to classify amyloid scans in a binary manner as ‘normal’ versus ‘Alzheimer-like’, is of high clinical relevance. We evaluated whether a supervised machine learning technique, support vector machines (SVM), can replicate the assignments made by visual readers blind to the clinical diagnosis, which image components have highest diagnostic value according to SVM and how 18F-flutemetamol-based classification using SVM relates to structural MRI-based classification using SVM within the same subjects. By means of SVM with a linear kernel, we analyzed 18F-flutemetamol scans and volumetric MRI scans from 72 cases from the 18F-flutemetamol phase 2 study (27 clinically probable Alzheimer''s disease (AD), 20 amnestic mild cognitive impairment (MCI), 25 controls). In a leave-one-out approach, we trained the 18F-flutemetamol based classifier by means of the visual reads and tested whether the classifier was able to reproduce the assignment based on visual reads and which voxels had the highest feature weights. The 18F-flutemetamol based classifier was able to replicate the assignments obtained by visual reads with 100% accuracy. The voxels with highest feature weights were in the striatum, precuneus, cingulate and middle frontal gyrus. Second, to determine concordance between the gray matter volume- and the 18F-flutemetamol-based classification, we trained the classifier with the clinical diagnosis as gold standard. Overall sensitivity of the 18F-flutemetamol- and the gray matter volume-based classifiers were identical (85.2%), albeit with discordant classification in three cases. Specificity of the 18F-flutemetamol based classifier was 92% compared to 68% for MRI. In the MCI group, the 18F-flutemetamol based classifier distinguished more reliably between converters and non-converters than the gray matter-based classifier. The visual read-based binary classification of 18F-flutemetamol scans can be replicated using SVM. In this sample the specificity of 18F-flutemetamol based SVM for distinguishing AD from controls is higher than that of gray matter volume-based SVM. [Copyright &y& Elsevier]

Abstract: Rodent studies suggest that prefrontal dopamine neurotransmission plays an important role in the neural processing of psychosocial stress. Human studies investigating stress-induced changes in dopamine levels, however, have focused solely on striatal dopamine transmission. The aim of this study was to investigate in vivo dopamine release in the human prefrontal cortex in response to a psychosocial stress challenge, using the highly selective dopamine D2/3 PET radioligand [18F]fallypride in healthy subjects. Twelve healthy subjects (age (y): 39.8; SD=15.8) underwent a single dynamic Positron Emission Tomography (PET) scanning session after intravenous administration of 185.2 (SD=10.2) MBq [18F]fallypride. Psychosocial stress was initiated at 100min postinjection. PET data were analyzed using the linearized simplified reference region model (LSRRM), which accounts for time-dependent changes in [18F]fallypride displacement. Voxel-based statistical maps, representing specific D2/3 binding changes, were computed to localize areas with increased ligand displacement after task initiation, reflecting dopamine release. The psychosocial stress challenge induced detectable amounts of dopamine release throughout the prefrontal cortex, with dopaminergic activity in bilateral ventromedial prefrontal cortex being associated with subjectively rated experiences of psychosocial stress. The novel finding that a mild psychosocial stress in humans induces increased levels of endogenous dopamine in the PFC indicates that the dynamics of the dopamine-related stress response cannot be interpreted by focusing on mesolimbic brain regions alone. [Copyright &y& Elsevier]

Unlabelled: FDG-PET contributes to the diagnosis and management of neurological diseases. In some of these diseases, pathological gray matter (GM) areas may have a reduced FDG uptake. Detection of these regions can be difficult and some remain undiscovered using visual assessment. The main reason for this detection problem is the relatively small thickness of GM compared to the spatial resolution of PET, known as the partial volume effect. We have developed an anatomy-based maximum-a-posteriori reconstruction algorithm (A-MAP) which corrects for this effect during the reconstruction using segmented magnetic resonance (MR) data. Monte-Carlo based 3-D brain software phantom simulations were used to investigate the influence of the strength of anatomy-based smoothing in GM, the influence of misaligned MR data, and the effect of local segmentation errors. A human observer study was designed to assess the detection performance of A-MAP versus post-smoothed maximum-likelihood (ML) reconstruction. We demonstrated the applicability of A-MAP using real patient data. The results for A-MAP showed improved recovery values and robustness for local segmentation errors. Misaligned MR data reduced the recovery values towards those obtained by post-smoothed ML, for small registration errors. In the human observer study, detection accuracy of hypometabolic regions was significantly improved using A-MAP, compared to post-smoothed ML (P < 0.004). The patient study confirmed the applicability of A-MAP in clinical practice., Conclusion: A-MAP is a promising technique for voxel-based partial volume correction of FDG-PET of the human brain.