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The N-methyl-D-aspartate receptor (NMDAR) plays a crucial role in neurodegenerative diseases such as Alzheimer’s disease and in the treatment of major depression by new fast-acting antidepressants such as ketamine. Given their broad implications, GluN2B-containing NMDARs have been of large interest as diagnostic and therapeutic targets. Recently, (R)-11C-Me-NB1 was investigated preclinically and shown to be a promising radioligand for imaging GluN2B subunits. Here, we report on the performance characteristics of this novel radioligand in a first-in-human PET study. Methods: Six healthy male subjects were scanned twice on a fully-integrated PET/MR scanner with (R)-11C-Me-NB1 for 120 min. Brain uptake and tracer distribution over time were investigated by standardized uptake values (SUV). Test-retest reliability was assessed with the absolute percentage difference (APD) and the coefficient of variation (COV). Exploratory total volumes of distribution (VT) were computed using an arterial input function and the Logan plot as well as a constrained two-tissue compartment model with K1/k2 coupled (2TCM). SUV was correlated with VT to investigate its potential as a surrogate marker of GluN2B expression. Results: High and heterogeneous radioligand uptake was observed across the entire gray matter with reversible kinetics within the scan time. SUV APD ranged from 6.8 - 8.5% and COV from 4.9 - 6.0%, indicating a high test-retest reliability. A moderate correlation was found between SUV averaged from 70-90 min and VT using Logan plot (Spearman’s rho = 0.44). Correlation between VT Logan and 2TCM was r= 0.76. Conclusion: The novel radioligand, (R)-11C-Me-NB1, was highly effective in mapping GluN2B-enriched NMDARs in the human brain. With a heterogeneous uptake and a high test-retest reliability, this radioligand offers promise to deepen our understanding of the GluN2B-containing NMDA receptor in the pathophysiology and treatment of neuropsychiatric disease such as Alzheimer’s disease and major depression. Additionally, it could help in the selection of appropriate doses of GluN2B-targeting drugs. ISSN:0097-9058 ISSN:0022-3123 ISSN:0161-5505 ISSN:2159-662X ISSN:1535-5667

Pharmacological imaging of the effects of selective serotonin reuptake inhibitors (SSRI) may aid the clarification of their mechanism of action and influence treatment of highly prevalent neuropsychiatric conditions if the detected effects could be related to patient outcomes. In a randomized double-blind design, 38 healthy participants received a constant infusion of 8 mg citalopram or saline during either their first or second of two PET/MR scans. Resting-state functional MRI (fMRI) was acquired simultaneously with PET data on the binding of serotonin transporters (5-HTT) using [11C]DASB. Three different approaches for modeling of pharmacological fMRI response were tested separately. These relied on the use of regressors corresponding to (1) the drug infusion paradigm, (2) time courses of citalopram plasma concentrations and (3) changes in 5-HTT binding measured in each individual, respectively. Furthermore, the replication of results of a widely used model-free analysis method was attempted which assesses the deviation of signal in discrete time bins of fMRI data acquired after start of drug infusion. Following drug challenge, average 5-HTT occupancy was 69±7% and peak citalopram plasma levels were 111.8 ± 21.1 ng/ml. None of the applied methods could detect significant differences in the pharmacological response between SSRI and placebo scans. The failed replication of SSRI effects reported in the literature despite a threefold larger sample size highlights the importance of appropriate correction for family-wise error in order to avoid spurious results in pharmacological imaging. This calls for the development of analysis methods which take regional specialization and the dynamics of brain activity into account.

The sex hormones testosterone and estradiol influence brain structure and function and are implicated in the pathogenesis, prevalence and disease course of major depression. Recent research employing gender-affirming hormone treatment (GHT) of gender dysphoric individuals and utilizing positron emission tomography (PET) indicates increased serotonin transporter binding upon high-dosages of testosterone treatment. Here, we investigated the effects of GHT on levels of monoamine oxidase A (MAO-A), another key target of antidepressant treatment. Participants underwent PET with the radioligand [11C]harmine to assess cerebral MAO-A distribution volumes (VT) before and four months after initiation of GHT. By the time this study was terminated for technical reasons, 18 transgender individuals undergoing GHT (11 transmen, TM and 7 transwomen, TW) and 17 cis-gender subjects had been assessed. Preliminary analysis of available data revealed statistically significant MAO-A VT reductions in TM under testosterone treatment in six of twelve a priori defined regions of interest (middle frontal cortex (-10%), anterior cingulate cortex (-9%), medial cingulate cortex (-10.5%), insula (-8%), amygdala (-9%) and hippocampus (-8.5%, all p

Background Selective serotonin reuptake inhibitors (SSRIs) are predominantly prescribed for people suffering from major depressive disorder. These antidepressants exert their effects by blocking the serotonin transporter (SERT), leading to increased levels of serotonin in the synaptic cleft and subsequently to an attenuation of depressive symptoms and elevation in mood. Although long-term studies investigating white matter (WM) alterations after exposure to antidepressant treatment exist, results on the acute effects on the brain’s WM microstructure are lacking. Methods In this interventional longitudinal study, 81 participants were included (33 patients and 48 healthy controls). All participants underwent diffusion weighted imaging on 2 separate days, receiving either citalopram or placebo using a randomized, double-blind, cross-over design. Fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity were calculated within the FMRIB software library and analyzed using tract-based spatial statistics. Results The repeated-measures ANOVA model revealed significant decreases after SSRI administration in mean diffusivity, axial diffusivity, and radial diffusivity regardless of the group (P Conclusions Our investigation provides the first evidence, to our knowledge, that fast WM microstructure adaptations within 1 hour after i.v. SSRI administration precede elevations in mood due to SSRI treatment. These results add a new facet to the complex mode of action of antidepressant therapy. This study was registered at clinicaltrials.gov with the identifier NCT02711215.

To assess if tumour grading based on dynamic [18F]FET positron emission tomography/magnetic resonance imaging (PET/MRI) studies is affected by different MRI-based attenuation correction (AC) methods. Twenty-four patients with suspected brain tumours underwent dynamic [18F]FET-PET/MRI examinations and subsequent low-dose computed tomography (CT) scans of the head. The dynamic PET data was reconstructed using the following AC methods: standard Dixon-based AC and ultra-short echo time MRI-based AC (MR-AC) and a model-based AC approach. All data were reconstructed also using CT-based AC (reference). For all lesions and reconstructions, time-activity curves (TACs) and time to peak (TTP) were extracted using different region-of-interest (ROI) and volume-of-interest (VOI) definitions. According to the most common evaluation approaches, TACs were categorised into two or three distinct curve patterns. Changes in TTP and TAC patterns compared to PET using CT-based AC were reported. In the majority of cases, TAC patterns did not change. However, TAC pattern changes as well as changes in TTP were observed in up to 8% and 17% of the cases when using different MR-AC methods and ROI/VOI definitions, respectively. However, these changes in TTP and TAC pattern were attributed to different delineations of the ROIs/VOIs in PET corrected with different AC methods. PET/MRI using different MR-AC methods can be used for the assessment of TAC patterns in dynamic [18F]FET studies, as long as a meaningful delineation of the area of interest within the tumour is ensured. • PET/MRI using different MR-AC methods can be used for dynamic [18F]FET studies. • A meaningful segmentation of the area of interest needs to be ensured, mandating a visual validation of the delineation by an experienced reader.

Introduction The brain's energy budget can be non-invasively assessed with different imaging modalities such as functional MRI (fMRI) and PET (fPET), which are sensitive to oxygen and glucose demands, respectively. The introduction of hybrid PET/MRI systems further enables the simultaneous acquisition of these parameters. Although a recently developed method offers the quantification of task-specific changes in glucose metabolism (CMRGlu) in a single measurement, direct comparison of the two imaging modalities is still difficult because of the different temporal resolutions. Thus, we optimized the protocol and systematically assessed shortened task durations of fPET to approach that of fMRI. Methods Twenty healthy subjects (9 male) underwent one measurement on a hybrid PET/MRI scanner. During the scan, tasks were completed in four blocks for fMRI (4 × 30 s blocks) and fPET: participants tapped the fingers of their right hand repeatedly to the thumb while watching videos of landscapes. For fPET, subjects were randomly assigned to groups of n = 5 with varying task durations of 10, 5, 2 and 1 min, where task durations were kept constant within a measurement. The radiolabeled glucose analogue [18F]FDG was administered as 20% bolus plus constant infusion. The bolus increases the signal-to-noise ratio and leaves sufficient activity to detect task-related effects but poses additional challenges due to a discontinuity in the tracer uptake. First, three approaches to remove task effects from the baseline term were evaluated: (1) multimodal, based on the individual fMRI analysis, (2) atlas-based by removing presumably activated regions and (3) model-based by fitting the baseline with exponential functions. Second, we investigated the need to capture the arterial input function peak with automatic blood sampling for the quantification of CMRGlu. We finally compared the task-specific activation obtained from fPET and fMRI qualitatively and statistically. Results CMRGlu quantified only with manual arterial samples showed a strong correlation to that obtained with automatic sampling (r = 0.9996). The multimodal baseline definition was superior to the other tested approaches in terms of residuals (p Conclusion Using a bolus plus constant infusion protocol, the necessary task duration for reliable quantification of task-specific CMRGlu could be reduced to 5 and 2 min, therefore, approaching that of fMRI. Important for valid quantification is a correct baseline definition, which was ideal when task-relevant voxels were determined with fMRI. The absence of a correlation and the different activation pattern between fPET and fMRI suggest that glucose metabolism and oxygen demand capture complementary aspects of energy demands.

Absolute quantification of PET brain imaging requires the measurement of an arterial input function (AIF), typically obtained invasively via an arterial cannulation. We present an approach to automatically calculate an image-derived input function (IDIF) and cerebral metabolic rates of glucose (CMRGlc) from the [18F]FDG PET data using an integrated PET/MRI system. Ten healthy controls underwent test–retest dynamic [18F]FDG-PET/MRI examinations. The imaging protocol consisted of a 60-min PET list-mode acquisition together with a time-of-flight MR angiography scan for segmenting the carotid arteries and intermittent MR navigators to monitor subject movement. AIFs were collected as the reference standard. Attenuation correction was performed using a separate low-dose CT scan. Assessment of the percentage difference between area-under-the-curve of IDIF and AIF yielded values within ±5%. Similar test–retest variability was seen between AIFs (9 ± 8) % and the IDIFs (9 ± 7) %. Absolute percentage difference between CMRGlc values obtained from AIF and IDIF across all examinations and selected brain regions was 3.2% (interquartile range: (2.4–4.3) %, maximum

Introduction In-vivo quantification of serotonin transporters (SERT) in human brain has been a mainstay of molecular imaging in the field of neuropsychiatric disorders and helped to explore the underpinnings of several medical conditions, therapeutic and environmental influences. The emergence of PET/MR hybrid systems and the heterogeneity of SERT binding call for the development of efficient methods making the investigation of larger or vulnerable populations with limited scanner time and simultaneous changes in molecular and functional measures possible. We propose [11C]DASB bolus plus constant infusion for these applications and validate it against standard analyses of dynamic PET data. Methods [11C]DASB bolus/infusion optimization was performed on data acquired after [11C]DASB bolus in 8 healthy subjects. Subsequently, 16 subjects underwent one scan using [11C]DASB bolus plus constant infusion with Kbol 160–179 min and one scan after [11C]DASB bolus for inter-method reliability analysis. Arterial blood sampling and metabolite analysis were performed for all scans. Distribution volumes (VT) were obtained using Logan plots for bolus scans and ratios between tissue and plasma parent activity for bolus plus infusion scans for different time spans of the scan (VT-70 for 60–70 min after start of tracer infusion, VT-90 for 75–90 min, VT-120 for 100–120 min) in 9 subjects. Omitting blood data, binding potentials (BPND) obtained using multilinear reference tissue modeling (MRTM2) and cerebellar gray matter as reference region were compared in 11 subjects. Results A Kbol of 160 min was observed to be optimal for rapid equilibration in thalamus and striatum. VT-70 showed good intraclass correlation coefficients (ICCs) of 0.61–0.70 for thalamus, striatal regions and olfactory cortex with bias ≤5.1% compared to bolus scans. ICCs increased to 0.72–0.78 for VT-90 and 0.77–0.93 for VT-120 in these regions. BPND-90 had negligible bias ≤2.5%, low variability ≤7.9% and ICCs of 0.74–0.87; BPND-120 had ICCs of 0.73–0.90. Low-binding cortical regions and cerebellar gray matter showed a positive bias of ~8% and ICCs 0.57–0.68 at VT-90. Cortical BPND suffered from high variability and bias, best results were obtained for olfactory cortex and anterior cingulate cortex with ICC=0.74–0.75 for BPND-90. High-density regions amygdala and midbrain had a negative bias of −5.5% and −22.5% at VT-90 with ICC 0.70 and 0.63, respectively. Conclusions We have optimized the equilibrium method with [11C]DASB bolus plus constant infusion and demonstrated good inter-method reliability with accepted standard methods and for SERT quantification using both VT and BPND in a range of different brain regions. With as little as 10–15 min of scanning valid estimates of SERT VT and BPND in thalamus, amygdala, striatal and high-binding cortical regions could be obtained. Blood sampling seems vital for valid quantification of SERT in low-binding cortical regions. These methods allow the investigation of up to three subjects with a single radiosynthesis.

The aim of this study was to compare attenuation-correction (AC) approaches for PET/MRI in clinical neurooncology. Methods: Forty-nine PET/MRI brain scans were included: brain tumor studies using 18F-fluoro-ethyl-tyrosine (18F-FET) (n = 31) and 68Ga-DOTANOC (n = 7) and studies of healthy subjects using 18F-FDG (n = 11). For each subject, MR-based AC maps (MR-AC) were acquired using the standard DIXON- and ultrashort echo time (UTE)-based approaches. A third MR-AC was calculated using a model-based, postprocessing approach to account for bone attenuation values (BD, noncommercial prototype software by Siemens Healthcare). As a reference, AC maps were derived from patient-specific CT images (CTref). PET data were reconstructed using standard settings after AC with all 4 AC methods. We report changes in diagnosis for all brain tumor patients and the following relative differences values (RDs [%]), with regards to AC-CTref: for 18F-FET (A)-SUVs as well as volumes of interest (VOIs) defined by a 70% threshold of all segmented lesions and lesion-to-background ratios; for 68Ga-DOTANOC (B)-SUVs as well as VOIs defined by a 50% threshold for all lesions and the pituitary gland; and for 18F-FDG (C)-RD of SUVs of the whole brain and 10 anatomic regions segmented on MR images. Results: For brain tumor imaging (A and B), the standard PET-based diagnosis was not affected by any of the 3 MR-AC methods. For A, the average RDs of SUVmean were -10%, -4%, and -3% and of the VOIs 1%, 2%, and 7% for DIXON, UTE, and BD, respectively. Lesion-to-background ratios for all MR-AC methods were similar to that of CTref. For B, average RDs of SUVmean were -11%, -11%, and -3% and of the VOIs 1%, -4%, and -3%, respectively. In the case of 18F-FDG PET/MRI (C), RDs for the whole brain were -11%, -8%, and -5% for DIXON, UTE, and BD, respectively. Conclusion: The diagnostic reading of PET/MR patients with brain tumors did not change with the chosen AC method. Quantitative accuracy of SUVs was clinically acceptable for UTE- and BD-AC for group A, whereas for group B BD was in accordance with CTref. Nevertheless, for the quantification of individual lesions large deviations to CTref can be observed independent of the MR-AC method used.

The investigation of cerebral metabolic rate of glucose (CMRGlu) at baseline and during specific tasks previously required separate scans with the drawback of high intrasubject variability. We aimed to validate a novel approach to assessing baseline glucose metabolism and task-specific changes in a single measurement with a constant infusion of 18F-FDG. Methods: Fifteen healthy subjects underwent two PET measurements with arterial blood sampling. As a reference, baseline CMRGlu was quantified from a 60-min scan after 18F-FDG bolus application using the Patlak plot (eyes closed). For the other scan, a constant radioligand infusion was applied for 95 min, during which the subjects opened their eyes at 10–20 min and 60–70 min and tapped their right thumb to their fingers at 35–45 min and 85–95 min. The constant-infusion scan was quantified in two steps. First, the general linear model was used to fit regional time–activity curves with regressors for baseline metabolism, task-specific changes for the eyes-open and finger-tapping conditions, and movement parameters. Second, the Patlak plot was used for quantification of CMRGlu. Multiplication of the baseline regressor by β-values from the general linear model yielded regionally specific time–activity curves for baseline metabolism. Further, task-specific changes in metabolism are directly proportional to changes in the slope of the time–activity curve and hence to changes in CMRGlu. Results: Baseline CMRGlu from the constant-infusion scan matched that from the bolus application (test–retest variability, 1.1% ± 24.7%), which was not the case for a previously suggested approach (variability, −39.9% ± 25.2%, P 0.99). Conclusion: Baseline glucose metabolism and task-specific changes can be quantified in a single measurement with constant infusion of 18F-FDG and venous blood sampling. The high sensitivity and regional specificity of the approach offer novel possibilities for functional and multimodal brain imaging.