ABCB1 variants and sex affect serotonin transporter occupancy in the brain.

Strategies to personalize psychopharmacological treatment promise to improve efficacy and tolerability. We measured serotonin transporter occupancy immediately after infusion of the widely prescribed P-glycoprotein substrate citalopram and assessed to what extent variants of the ABCB1 gene affect drug target engagement in the brain in vivo. A total of 79 participants (39 female) including 31 patients with major depression and 48 healthy volunteers underwent two PET/MRI scans with the tracer [11C]DASB and placebo-controlled infusion of citalopram (8 mg) in a cross-over design. We tested the effect of six ABCB1 single nucleotide polymorphisms and found lower SERT occupancy in ABCB1 rs2235015 minor allele carriers (n = 26, MAF = 0.18) compared to major allele homozygotes (t73 = 2.73, pFWE < 0.05) as well as in men compared to women (t73 = 3.33, pFWE < 0.05). These effects were robust to correction for citalopram plasma concentration, age and diagnosis. From occupancy we derived the ratio of occupied to unoccupied SERT, because in theory this measure is equal to the product of drug affinity and concentration at target sites. A model combining genotype with basic clinical variables, predicted that, at the same dosage, occupied to unoccupied SERT ratio was -14.48 ± 5.38% lower in rs2235015 minor allele carriers, +19.10 ± 6.95% higher in women, -4.83 ± 2.70% lower per 10 kg bodyweight, and -2.68 ± 3.07% lower per 10 years of age. Our results support the exploration of clinical algorithms with adjustment of initial citalopram dosing and highlight the potential of imaging-genetics for precision pharmacotherapy in psychiatry.

Biodistribution and dosimetry of the GluN2B-specific NMDA receptor PET radioligand (R)-[11C]Me-NB1.

BACKGROUND: The NMDA receptor (NMDAR) plays a key role in the central nervous system, e.g., for synaptic transmission. While synaptic NMDARs are thought to have protective characteristics, activation of extrasynaptic NMDARs might trigger excitotoxic processes linked to neuropsychiatric disorders. Since extrasynaptic NMDARs are typically GluN2B-enriched, the subunit is an interesting target for drug development and treatment monitoring. Recently, the novel GluN2B-specific PET radioligand (R)-[11C]Me-NB1 was investigated in rodents and for the first time successfully translated to humans. To assess whether (R)-[11C]Me-NB1 is a valuable radioligand for (repeated) clinical applications, we evaluated its safety, biodistribution and dosimetry. METHODS: Four healthy subjects (two females, two males) underwent one whole-body PET/MR measurement lasting for more than 120 min. The GluN2B-specific radioligand (R)-[11C]Me-NB1 was administered simultaneously with the PET start. Subjects were measured in nine passes and six bed positions from head to mid-thigh. Regions of interest was anatomically defined for the brain, thyroid, lungs, heart wall, spleen, stomach contents, pancreas, liver, kidneys, bone marrow and urinary bladder contents, using both PET and MR images. Time-integrated activity coefficients were estimated to calculate organ equivalent dose coefficients and the effective dose coefficient. Additionally, standardized uptake values (SUV) were computed to visualize the biodistribution. RESULTS: Administration of the radioligand was safe without adverse events. The organs with the highest uptake were the urinary bladder, spleen and pancreas. Organ equivalent dose coefficients were higher in female in almost all organs, except for the urinary bladder of male. The effective dose coefficient was 6.0 µSv/MBq. CONCLUSION: The GluN2B-specific radioligand (R)-[11C]Me-NB1 was well-tolerated without reported side effects. Effective dose was estimated to 1.8 mSv when using 300 MBq of presented radioligand. The critical organ was the urinary bladder. Due to the low effective dose coefficient of this radioligand, longitudinal studies for drug development and treatment monitoring of neuropsychiatric disorders including neurodegenerative diseases are possible. Trial registration Registered on 11th of June 2019 at https://www.basg.gv.at (EudraCT: 2018-002933-39).

Learning induces coordinated neuronal plasticity of metabolic demands and functional brain networks.

The neurobiological basis of learning is reflected in adaptations of brain structure, network organization and energy metabolism. However, it is still unknown how different neuroplastic mechanisms act together and if cognitive advancements relate to general or task-specific changes. Therefore, we tested how hierarchical network interactions contribute to improvements in the performance of a visuo-spatial processing task by employing simultaneous PET/MR neuroimaging before and after a 4-week learning period. We combined functional PET and metabolic connectivity mapping (MCM) to infer directional interactions across brain regions. Learning altered the top-down regulation of the salience network onto the occipital cortex, with increases in MCM at resting-state and decreases during task execution. Accordingly, a higher divergence between resting-state and task-specific effects was associated with better cognitive performance, indicating that these adaptations are complementary and both required for successful visuo-spatial skill learning. Simulations further showed that changes at resting-state were dependent on glucose metabolism, whereas those during task performance were driven by functional connectivity between salience and visual networks. Referring to previous work, we suggest that learning establishes a metabolically expensive skill engram at rest, whose retrieval serves for efficient task execution by minimizing prediction errors between neuronal representations of brain regions on different hierarchical levels.

Simultaneous radiomethylation of [11C]harmine and [11C]DASB and kinetic modeling approach for serotonergic brain imaging in the same individual.

Simultaneous characterization of pathologies by multi-tracer positron emission tomography (PET) is among the most promising applications in nuclear medicine. Aim of this work was the simultaneous production of two PET-tracers in one module and test the relevance for human application. [11C]harmine and [11C]DASB were concurrently synthesized in a 'two-in-one-pot' reaction in quality for application. Dual-tracer protocol was simulated using 16 single PET scans in different orders of tracer application separated by different time intervals. Volume of distribution was calculated for single- and dual-tracer measurements using Logan's plot and arterial input function in 13 brain regions. The 'two-in-one-pot' reaction yielded equivalent amounts of both radiotracers with comparable molar activities. The simulations of the dual-tracer application were comparable to the single bolus injections in 13 brain regions, when [11C]harmine was applied first and [11C]DASB second, with an injection time interval of 45 min (rxy = 0.90). Our study shows the successful simultaneous dual-tracer production leading to decreased radiation burden and costs. The simulation of dual subject injection to quantify the monoamine oxidase-A and serotonin transporter distribution proved its high potential. Multi-tracer imaging may drive more sophisticated study designs and diminish the day-to-day differences in the same individual as well as increase PET scanner efficiency.

First-in-Humans Brain PET Imaging of the GluN2B-Containing N-methyl-d-aspartate Receptor with (R)-11C-Me-NB1.

The N-methyl-d-aspartate receptor (NMDAR) plays a crucial role in neurodegenerative diseases such as Alzheimer disease and in the treatment of major depression by fast-acting antidepressants such as ketamine. Given their broad implications, GluN2B-containing NMDARs have been of 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 radioligand in a first-in-humans 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 SUVs. Test-retest reliability was assessed with the absolute percentage difference and the coefficient of variation. Exploratory total volumes of distribution (VT) were computed using an arterial input function and the Logan plot as well as a constrained 2-tissue-compartment model with the ratio of rate constants between plasma and tissue compartments (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 absolute percentage difference ranged from 6.9% to 8.5% and coefficient of variation from 4.9% to 6.0%, indicating a high test-retest reliability. A moderate correlation was found between SUV averaged from 70 to 90 min and VT using Logan plot (Spearman ρ = 0.44). Correlation between VT Logan and 2TCM was r = 0.76. Conclusion: The 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 NMDAR in the pathophysiology and treatment of neuropsychiatric disease such as Alzheimer disease and major depression. Additionally, it could help in the selection of appropriate doses of GluN2B-targeting drugs.

High-dose testosterone treatment reduces monoamine oxidase A levels in the human brain: A preliminary report.

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<0.05)). MAO-A VT did not change in TW receiving estrogen treatment. Despite the limited sample size, pronounced MAO-A VT reduction could be observed, pointing towards a potential effect of testosterone. Considering MAO-A's central role in regulation of serotonergic neurotransmission, changes to MAO-A VT should be further investigated as a possible mechanism by which testosterone mediates risk for, symptomatology of, and treatment response in affective disorders.

Dissociations between glucose metabolism and blood oxygenation in the human default mode network revealed by simultaneous PET-fMRI.

The finding of reduced functional MRI (fMRI) activity in the default mode network (DMN) during externally focused cognitive control has been highly influential to our understanding of human brain function. However, these negative fMRI responses, measured as relative decreases in the blood-oxygenation-level-dependent (BOLD) response between rest and task, have also prompted major questions of interpretation. Using hybrid functional positron emission tomography (PET)-MRI, this study shows that task-positive and -negative BOLD responses do not reflect antagonistic patterns of synaptic metabolism. Task-positive BOLD responses in attention and control networks were accompanied by concomitant increases in glucose metabolism during cognitive control, but metabolism in widespread DMN remained high during rest and task despite negative BOLD responses. Dissociations between glucose metabolism and the BOLD response specific to the DMN reveal functional heterogeneity in this network and demonstrate that negative BOLD responses during cognitive control should not be interpreted to reflect relative increases in metabolic activity during rest. Rather, neurovascular coupling underlying BOLD response patterns during rest and task in DMN appears fundamentally different from BOLD responses in other association networks during cognitive control.

Reliability of task-specific neuronal activation assessed with functional PET, ASL and BOLD imaging.

Mapping the neuronal response during cognitive processing is of crucial importance to gain new insights into human brain function. BOLD imaging and ASL are established MRI methods in this endeavor. Recently, the novel approach of functional PET (fPET) was introduced, enabling absolute quantification of glucose metabolism at rest and during task execution in a single measurement. Here, we report test-retest reliability of fPET in direct comparison to BOLD imaging and ASL. Twenty healthy subjects underwent two PET/MRI measurements, providing estimates of glucose metabolism, cerebral blood flow (CBF) and blood oxygenation. A cognitive task was employed with different levels of difficulty requiring visual-motor coordination. Task-specific neuronal activation was robustly detected with all three imaging approaches. The highest reliability was obtained for glucose metabolism at rest. Although this dropped during task performance it was still comparable to that of CBF. In contrast, BOLD imaging yielded high performance only for qualitative spatial overlap of task effects but not for quantitative comparison. Hence, the combined assessment of fPET and ASL offers reliable and simultaneous absolute quantification of glucose metabolism and CBF at rest and task.

Functional dynamics of dopamine synthesis during monetary reward and punishment processing.

The assessment of dopamine release with the PET competition model is thoroughly validated but entails disadvantages for the investigation of cognitive processes. We introduce a novel approach incorporating 6-[18F]FDOPA uptake as index of the dynamic regulation of dopamine synthesis enzymes by neuronal firing. The feasibility of this approach is demonstrated by assessing widely described sex differences in dopamine neurotransmission. Reward processing was behaviorally investigated in 36 healthy participants, of whom 16 completed fPET and fMRI during the monetary incentive delay task. A single 50 min fPET acquisition with 6-[18F]FDOPA served to quantify task-specific changes in dopamine synthesis. In men monetary gain induced stronger increases in ventral striatum dopamine synthesis than loss. Interestingly, the opposite effect was discovered in women. These changes were further associated with reward (men) and punishment sensitivity (women). As expected, fMRI showed robust task-specific neuronal activation but no sex difference. Our findings provide a neurobiological basis for known behavioral sex differences in reward and punishment processing, with important implications in psychiatric disorders showing sex-specific prevalence, altered reward processing and dopamine signaling. The high temporal resolution and magnitude of task-specific changes make fPET a promising tool to investigate functional neurotransmitter dynamics during cognitive processing and in brain disorders.

Conditional Generative Adversarial Networks Aided Motion Correction of Dynamic 18F-FDG PET Brain Studies.

This work set out to develop a motion-correction approach aided by conditional generative adversarial network (cGAN) methodology that allows reliable, data-driven determination of involuntary subject motion during dynamic 18F-FDG brain studies. Methods: Ten healthy volunteers (5 men/5 women; mean age ± SD, 27 ± 7 y; weight, 70 ± 10 kg) underwent a test-retest 18F-FDG PET/MRI examination of the brain (n = 20). The imaging protocol consisted of a 60-min PET list-mode acquisition contemporaneously acquired with MRI, including MR navigators and a 3-dimensional time-of-flight MR angiography sequence. Arterial blood samples were collected as a reference standard representing the arterial input function (AIF). Training of the cGAN was performed using 70% of the total datasets (n = 16, randomly chosen), which was corrected for motion using MR navigators. The resulting cGAN mappings (between individual frames and the reference frame [55-60 min after injection]) were then applied to the test dataset (remaining 30%, n = 6), producing artificially generated low-noise images from early high-noise PET frames. These low-noise images were then coregistered to the reference frame, yielding 3-dimensional motion vectors. Performance of cGAN-aided motion correction was assessed by comparing the image-derived input function (IDIF) extracted from a cGAN-aided motion-corrected dynamic sequence with the AIF based on the areas under the curves (AUCs). Moreover, clinical relevance was assessed through direct comparison of the average cerebral metabolic rates of glucose (CMRGlc) values in gray matter calculated using the AIF and the IDIF. Results: The absolute percentage difference between AUCs derived using the motion-corrected IDIF and the AIF was (1.2% + 0.9%). The gray matter CMRGlc values determined using these 2 input functions differed by less than 5% (2.4% + 1.7%). Conclusion: A fully automated data-driven motion-compensation approach was established and tested for 18F-FDG PET brain imaging. cGAN-aided motion correction enables the translation of noninvasive clinical absolute quantification from PET/MR to PET/CT by allowing the accurate determination of motion vectors from the PET data itself.

Predicting Antidepressant Citalopram Treatment Response via Changes in Brain Functional Connectivity After Acute Intravenous Challenge.

Introduction: The early and therapy-specific prediction of treatment success in major depressive disorder is of paramount importance due to high lifetime prevalence, and heterogeneity of response to standard medication and symptom expression. Hence, this study assessed the predictability of long-term antidepressant effects of escitalopram based on the short-term influence of citalopram on functional connectivity. Methods: Twenty nine subjects suffering from major depression were scanned twice with resting-state functional magnetic resonance imaging under the influence of intravenous citalopram and placebo in a randomized, double-blinded cross-over fashion. Symptom factors were identified for the Hamilton depression rating scale (HAM-D) and Beck's depression inventory (BDI) taken before and after a median of seven weeks of escitalopram therapy. Predictors were calculated from whole-brain functional connectivity, fed into robust regression models, and cross-validated. Results: Significant predictive power could be demonstrated for one HAM-D factor describing insomnia and the total score (r = 0.45-0.55). Remission and response could furthermore be predicted with an area under the receiver operating characteristic curve of 0.73 and 0.68, respectively. Functional regions with high influence on the predictor were located especially in the ventral attention, fronto-parietal, and default mode networks. Conclusion: It was shown that medication-specific antidepressant symptom improvements can be predicted using functional connectivity measured during acute pharmacological challenge as an easily assessable imaging marker. The regions with high influence have previously been related to major depression as well as the response to selective serotonin reuptake inhibitors, corroborating the advantages of the current approach of focusing on treatment-specific symptom improvements.

Reconfiguration of functional brain networks and metabolic cost converge during task performance.

The ability to solve cognitive tasks depends upon adaptive changes in the organization of whole-brain functional networks. However, the link between task-induced network reconfigurations and their underlying energy demands is poorly understood. We address this by multimodal network analyses integrating functional and molecular neuroimaging acquired concurrently during a complex cognitive task. Task engagement elicited a marked increase in the association between glucose consumption and functional brain network reorganization. This convergence between metabolic and neural processes was specific to feedforward connections linking the visual and dorsal attention networks, in accordance with task requirements of visuo-spatial reasoning. Further increases in cognitive load above initial task engagement did not affect the relationship between metabolism and network reorganization but only modulated existing interactions. Our findings show how the upregulation of key computational mechanisms to support cognitive performance unveils the complex, interdependent changes in neural metabolism and neuro-vascular responses.

Fully Integrated PET/MR Imaging for the Assessment of the Relationship Between Functional Connectivity and Glucose Metabolic Rate.

In the past, determination of absolute values of cerebral metabolic rate of glucose (CMRGlc) in clinical routine was rarely carried out due to the invasive nature of arterial sampling. With the advent of combined PET/MR imaging technology, CMRGlc values can be obtained non-invasively, thereby providing the opportunity to take advantage of fully quantitative data in clinical routine. However, CMRGlc values display high physiological variability, presumably due to fluctuations in the intrinsic activity of the brain at rest. To reduce CMRGlc variability associated with these fluctuations, the objective of this study was to determine whether functional connectivity measures derived from resting-state fMRI (rs-fMRI) could be used to correct for these fluctuations in intrinsic brain activity. METHODS: We studied 10 healthy volunteers who underwent a test-retest dynamic [18F]FDG-PET study using a fully integrated PET/MR system (Siemens Biograph mMR). To validate the non-invasive derivation of an image-derived input function based on combined analysis of PET and MR data, arterial blood samples were obtained. Using the arterial input function (AIF), parametric images representing CMRGlc were determined using the Patlak graphical approach. Both directed functional connectivity (dFC) and undirected functional connectivity (uFC) were determined between nodes in six major networks (Default mode network, Salience, L/R Executive, Attention, and Sensory-motor network) using either a bivariate-correlation (R coefficient) or a Multi-Variate AutoRegressive (MVAR) model. In addition, the performance of a regional connectivity measure, the fractional amplitude of low frequency fluctuations (fALFF), was also investigated. RESULTS: The average intrasubject variability for CMRGlc values between test and retest was determined as (14 ±8%) with an average inter-subject variability of 25% at test and 15% at retest. The average CMRGlc value (umol/100 g/min) across all networks was 39 ±10 at test and increased slightly to 43 ±6 at retest. The R, MVAR and fALFF coefficients showed relatively large test-retest variability in comparison to the inter-subjects variability, resulting in poor reliability (intraclass correlation in the range of 0.11-0.65). More importantly, no significant relationship was found between the R coefficients (for uFC), MVAR coefficients (for dFC) or fALFF and corresponding CMRGlc values for any of the six major networks. DISCUSSION: Measurement of functional connectivity within established brain networks did not provide a means to decrease the inter- or intrasubject variability of CMRGlc values. As such, our results indicate that connectivity measured derived from rs-fMRI acquired contemporaneously with PET imaging are not suited for correction of CMRGlc variability associated with intrinsic fluctuations of resting-state brain activity. Thus, given the observed substantial inter- and intrasubject variability of CMRGlc values, the relevance of absolute quantification for clinical routine is presently uncertain.

Utility of Absolute Quantification in Non-lesional Extratemporal Lobe Epilepsy Using FDG PET/MR Imaging.

The purpose of this study was to establish a non-invasive clinical PET/MR protocol using [18F]-labeled deoxyglucose (FDG) that provides physicians with regional metabolic rate of glucose (MRGlc) values and to clarify the contribution of absolute quantification to clinical management of patients with non-lesional extratemporal lobe epilepsy (ETLE). The study included a group of 15 patients with non-lesional ETLE who underwent a dynamic FDG PET study using a fully-integrated PET/MRI system (Siemens Biograph). FDG tracer uptake images were converted to MRGlc (µmol/100 g/min) maps using an image derived input function that was extracted based on the combined analysis of PET and MRI data. In addition, the same protocol was applied to a group of healthy controls, yielding a normative database. Abnormality maps for ETLE patients were created with respect to the normative database, defining significant hypo- or hyper-metabolic regions that exceeded ±2 SD of normal regional mean MRGlc values. Abnormality maps derived from MRGlc images of ETLE patients contributed to the localization of hypo-metabolic areas against visual readings in 53% and increased the confidence in the original clinical readings in 33% of all cases. Moreover, quantification allowed identification of hyper-metabolic areas that are associated with frequently spiking cortex, rarely acknowledged in clinical readings. Overall, besides providing some confirmatory information to visual readings, quantitative PET imaging demonstrated only a moderate impact on clinical management of patients with complex pathology that leads to epileptic seizures, failing to provide new decisive information that would have changed classification of patients from being rejected to being considered for surgical intervention.

Promise of Fully Integrated PET/MRI: Noninvasive Clinical Quantification of Cerebral Glucose Metabolism.

We describe a fully automated processing pipeline to support the noninvasive absolute quantification of the cerebral metabolic rate for glucose (CMRGlc) in a clinical setting. This pipeline takes advantage of "anatometabolic" information associated with fully integrated PET/MRI. Methods: Ten healthy volunteers (5 men and /5 women; 27 ± 7 y old; 70 ± 10 kg) underwent a test-retest 18F-FDG PET/MRI examination of the brain. The imaging protocol consisted of a 60-min PET list-mode acquisition with parallel MRI acquisitions, including 3-dimensional time-of-flight MR angiography, MRI navigators, and a T1-weighted MRI scan. State-of-the-art MRI-based attenuation correction was derived from T1-weighted MRI (pseudo-CT [pCT]). For validation purposes, a low-dose CT scan was also performed. Arterial blood samples were collected as the reference standard (arterial input function [AIF]). The developed pipeline allows the derivation of an image-derived input function (IDIF), which is subsequently used to create CMRGlc maps by means of a Patlak analysis. The pipeline also includes motion correction using the MRI navigator sequence as well as a novel partial-volume correction that accounts for background heterogeneity. Finally, CMRGlc maps are used to generate a normative database to facilitate the detection of metabolic abnormalities in future patient scans. To assess the performance of the developed pipeline, IDIFs extracted by both CT-based attenuation correction (CT-IDIF) and MRI-based attenuation correction (pCT-IDIF) were compared with the reference standard (AIF) using the absolute percentage difference between the areas under the curves as well as the absolute percentage difference in regional CMRGlc values. Results: The absolute percentage differences between the areas under the curves for CT-IDIF and pCT-IDIF were determined to be 1.4% ± 1.0% and 3.4% ± 2.6%, respectively. The absolute percentage difference in regional CMRGlc values based on CT-IDIF and pCT-IDIF differed by less than 6% from the reference values obtained from the AIF. Conclusion: By taking advantage of the capabilities of fully integrated PET/MRI, we developed a fully automated computational pipeline that allows the noninvasive determination of regional CMRGlc values in a clinical setting. This methodology might facilitate the proliferation of fully quantitative imaging into the clinical arena and, as a result, might contribute to improved diagnostic efficacy.

Attenuation Correction Approaches for Serotonin Transporter Quantification With PET/MRI.

BACKGROUND: Several MR-based attenuation correction (AC) approaches were developed to conquer the challenging AC in hybrid PET/MR imaging. These AC methods are commonly evaluated on standardized uptake values or tissue concentration. However, in neurotransmitter system studies absolute quantification is more favorable due to its accuracy. Therefore, our aim was to investigate the accuracy of segmentation- and atlas-based MR AC approaches on serotonin transporter (SERT) distribution volumes and occupancy after a drug challenge. METHODS: 18 healthy subjects (7 male) underwent two [11C]DASB PET/MRI measurements in a double-blinded, placebo controlled, cross-over design. After 70 min the selective serotonin reuptake inhibitor (SSRI) citalopram or a placebo was infused. The parameters total and specific volume of distribution (VT, VS = BPP) and occupancy were quantified. All subjects underwent a low-dose CT scan as reference AC method. Besides the standard AC approaches DIXON and UTE, a T1-weighted structural image was recorded to estimate a pseudo-CT based on an MR/CT database (pseudoCT). Another evaluated AC approach superimposed a bone model on AC DIXON. Lastly, an approach optimizing the segmentation of UTE images was analyzed (RESOLUTE). PET emission data were reconstructed with all 6 AC methods. The accuracy of the AC approaches was evaluated on a region of interest-basis for the parameters VT, BPP, and occupancy with respect to the results of AC CT. RESULTS: Variations for VT and BPP were found with all AC methods with bias ranging from -15 to 17%. The smallest relative errors for all regions were found with AC pseudoCT (<|5%|). Although the bias between BPP SSRI and BPP placebo varied markedly with AC DIXON (<|12%|) and AC UTE (<|9%|), a high correlation to AC CT was obtained (r 2∼1). The relative difference of the occupancy for all tested AC methods was small for SERT high binding regions (<|4%|). CONCLUSION: The high correlation might offer a rescaling from the biased parameters VT and BPP to the true values. Overall, the pseudoCT approach yielded smallest errors and the best agreement with AC CT. For SERT occupancy, all AC methods showed little bias in high binding regions, indicating that errors may cancel out in longitudinal assessments.

Serotonin Transporter Binding in the Human Brain After Pharmacological Challenge Measured Using PET and PET/MR.

Introduction: In-vivo quantification of the serotonin transporter (SERT) guided our understanding of many neuropsychiatric disorders. A recently introduced bolus plus constant infusion protocol has been shown to allow the reliable determination of SERT binding with reduced scan time. In this work, the outcomes of two methods, a bolus injection paradigm on a GE PET camera, and a bolus plus infusion paradigm on a combined Siemens PET/MR camera were compared. Methods: A total of seven healthy subjects underwent paired PET and paired PET/MR scans each with intravenous double-blind application of 7.5 mg citalopram or saline in a randomized cross-over study design. While PET scans were performed according to standard protocols and non-displaceable binding potentials (BPND) were calculated using the multi-linear reference tissue model, during PET/MR measurements [11C]DASB was applied as bolus plus constant infusion, and BPND was calculated using the steady state method and data acquired at tracer equilibrium. Occupancies were calculated as the relative decrease in BPND between saline and citalopram scans. Results: During placebo scans, a mean difference in BPND of -0.08 (-11.71%) across all ROIs was found between methods. PET/MR scans resulted in higher BPND estimates than PET scans in all ROIs except the midbrain. A mean difference of -0.19 (-109.40%) across all ROIs between methods was observed for citalopram scans. PET/MR scans resulted in higher BPND estimates than PET scans in all ROIs. For occupancy, a mean difference of 23.12% (21.91%) was observed across all ROIs. PET/MR scans resulted in lower occupancy compared to PET scans in all ROIs except the temporal cortex. While for placebo, BPND of high-binding regions (thalamus and striatum) exhibited moderate reliability (ICC = 0.66), during citalopram scans ICC decreased (0.36-0.46). However, reliability for occupancy remained high (0.57-0.82). Conclusion: Here, we demonstrated the feasibility of reliable and non-invasive SERT quantification using a [11C]DASB bolus plus constant infusion protocol at a hybrid PET/MR scanner, which might facilitate future pharmacological imaging studies. Highest agreement with established methods for quantification of occupancy and SERT BPND at baseline was observed in subcortical high-binding regions.

Modeling the acute pharmacological response to selective serotonin reuptake inhibitors in human brain using simultaneous PET/MR imaging.

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 ±â€¯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.

Dynamic [18F]FET-PET/MRI using standard MRI-based attenuation correction methods.

AIM: 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. 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. RESULTS: 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. CONCLUSION: 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. KEY POINTS: • 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.

Towards quantitative [18F]FDG-PET/MRI of the brain: Automated MR-driven calculation of an image-derived input function for the non-invasive determination of cerebral glucose metabolic rates.

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 < 10%). High test-retest intravariability was observed between CMRGlc values obtained from AIF (14%) and IDIF (17%). The proposed approach provides an IDIF, which can be effectively used in lieu of AIF.