Simple and rapid quantification of serotonin transporter binding using [11C]DASB bolus plus constant infusion

Comparison of cardiac image-derived input functions for quantitative whole body [18F]FDG imaging with arterial blood sampling

Introduction: Dynamic positron emission tomography (PET) and the application of kinetic models can provide important quantitative information based on its temporal information. This however requires arterial blood sampling, which can be challenging to acquire. Nowadays, state-of-the-art PET/CT systems offer fully automated, whole-body (WB) kinetic modelling protocols using image-derived input functions (IDIF) to replace arterial blood sampling. Here, we compared the validity of an automatic WB kinetic model protocol to the reference standard arterial input function (AIF) for both clinical and research settings. Methods: Sixteen healthy participants underwent dynamic WB [18F]FDG scans using a continuous bed motion PET/CT system with simultaneous arterial blood sampling. Multiple processing pipelines that included automatic and manually generated IDIFs derived from the aorta and left ventricle, with and without motion correction were compared to the AIF. Subsequently generated quantitative images of glucose metabolism were compared to evaluate performance of the different input functions. Results: We observed moderate to high correlations between IDIFs and the AIF regarding area under the curve (r = 0.49-0.89) as well as for the cerebral metabolic rate of glucose (CMRGlu) (r = 0.68-0.95). Manual placing of IDIFs and motion correction further improved their similarity to the AIF. Discussion: In general, the automatic vendor protocol is a feasible approach for the quantification of CMRGlu for both, clinical and research settings where expertise or time is not available. However, we advise on a rigorous inspection of the placement of the volume of interest, the resulting IDIF, and the quantitative values to ensure valid interpretations. In protocols requiring longer scan times or where cohorts are prone to involuntary movement, manual IDIF definition with additional motion correction is recommended, as this has greater accuracy and reliability.

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.

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, p_FWE < 0.05) as well as in men compared to women (t₇₃ = 3.33, p_FWE < 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.

Autonomic failure in Parkinson's disease is associated with striatal dopamine deficiencies

Autonomic dysfunction is a common non-motor symptom in Parkinson's disease (PD). Dopamine and serotonin are known to play a role in autonomic regulation, and, therefore, PD-related degeneration of serotonergic and dopaminergic neurons in these regions may be associated with autonomic dysfunction. We sought to clarify the association between extrastriatal serotonergic and striatal dopaminergic degeneration and the severity of autonomic symptoms, including gastrointestinal, pupillomotor, thermoregulatory, cardiovascular, and urinary dysfunction. We performed hierarchical multiple regression analyses to determine the relationships between (extra)striatal serotonergic and dopaminergic degeneration and autonomic dysfunction in 310 patients with PD. We used [¹²³I]FP-CIT SPECT binding to presynaptic serotonin (SERT) and dopamine (DAT) transporters as a measure of the integrity of these neurotransmitter systems, and the SCOPA-AUT (Scales for Outcomes in Parkinson's Disease-Autonomic) questionnaire to evaluate the perceived severity of autonomic dysfunction. Motor symptom severity, medication status, and sex were added to the model as covariates. Additional analyses were also performed using five subdomains of the SCOPA-AUT: cardiovascular, gastrointestinal, urinary, thermoregulatory, and pupillomotor symptoms. We found that autonomic symptoms were most significantly related to lower [¹²³I]FP-CIT binding ratios in the right caudate nucleus and were mainly driven by gastrointestinal and cardiovascular dysfunction. These results provide a first look into the modest role of dopaminergic projections towards the caudate nucleus in the pathophysiology of autonomic dysfunction in PD, but the underlying mechanism warrants further investigation.

Machine learning classification of ADHD and HC by multimodal serotonergic data

Serotonin neurotransmission may impact the etiology and pathology of attention-deficit and hyperactivity disorder (ADHD), partly mediated through single nucleotide polymorphisms (SNPs). We propose a multivariate, genetic and positron emission tomography (PET) imaging classification model for ADHD and healthy controls (HC). Sixteen patients with ADHD and 22 HC were scanned by PET to measure serotonin transporter (SERT') binding potential with [11C]DASB. All subjects were genotyped for thirty SNPs within the HTR1A, HTR1B, HTR2A and TPH2 genes. Cortical and subcortical regions of interest (ROI) were defined and random forest (RF) machine learning was used for feature selection and classification in a five-fold cross-validation model with ten repeats. Variable selection highlighted the ROI posterior cingulate gyrus, cuneus, precuneus, pre-, para- and postcentral gyri as well as the SNPs HTR2A rs1328684 and rs6311 and HTR1B rs130058 as most discriminative between ADHD and HC status. The mean accuracy for the validation sets across repeats was 0.82 (±0.09) with balanced sensitivity and specificity of 0.75 and 0.86, respectively. With a prediction accuracy above 0.8, the findings underlying the proposed model advocate the relevance of the SERT as well as the HTR1B and HTR2A genes in ADHD and hint towards disease-specific effects. Regarding the high rates of comorbidities and difficult differential diagnosis especially for ADHD, a reliable computer-aided diagnostic tool for disorders anchored in the serotonergic system will support clinical decisions.

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 (V_T, V_S = BP_P) 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 V_T, BP_P, and occupancy with respect to the results of AC CT.

Results

Variations for V_T and BP_P 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 BP_P SSRI and BP_P 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 V_T and BP_P 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 (BP_ND) were calculated using the multi-linear reference tissue model, during PET/MR measurements [¹¹C]DASB was applied as bolus plus constant infusion, and BP_ND was calculated using the steady state method and data acquired at tracer equilibrium. Occupancies were calculated as the relative decrease in BP_ND between saline and citalopram scans. Results: During placebo scans, a mean difference in BP_ND of -0.08 (-11.71%) across all ROIs was found between methods. PET/MR scans resulted in higher BP_ND 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 BP_ND 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, BP_ND 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 BP_ND 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 ± 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.

Optimization of preprocessing strategies in Positron Emission Tomography (PET) neuroimaging: A [11C]DASB PET study

Positron Emission Tomography (PET) is an important neuroimaging tool to quantify the distribution of specific molecules in the brain. The quantification is based on a series of individually designed data preprocessing steps (pipeline) and an optimal preprocessing strategy is per definition associated with less noise and improved statistical power, potentially allowing for more valid neurobiological interpretations. In spite of this, it is currently unclear how to design the best preprocessing pipeline and to what extent the choice of each preprocessing step in the pipeline minimizes subject-specific errors. To evaluate the impact of various preprocessing strategies, we systematically examined 384 different pipeline strategies in data from 30 healthy participants scanned twice with the serotonin transporter (5-HTT) radioligand [¹¹C]DASB. Five commonly used preprocessing steps with two to four options were investigated: (1) motion correction (MC) (2) co-registration (3) delineation of volumes of interest (VOI's) (4) partial volume correction (PVC), and (5) kinetic modeling. To quantitatively compare and evaluate the impact of various preprocessing strategies, we used the performance metrics: test-retest bias, within- and between-subject variability, the intraclass-correlation coefficient, and global signal-to-noise ratio. We also performed a power analysis to estimate the required sample size to detect either a 5% or 10% difference in 5-HTT binding as a function of preprocessing pipeline. The results showed a complex downstream dependency between the various preprocessing steps on the performance metrics. The choice of MC had the most profound effect on 5-HTT binding, prior to the effects caused by PVC and kinetic modeling, and the effects differed across VOI's. Notably, we observed a negative bias in 5-HTT binding across test and retest in 98% of pipelines, ranging from 0 to 6% depending on the pipeline. Optimization of the performance metrics revealed a trade-off in within- and between-subject variability at the group-level with opposite effects (i.e. minimization of within-subject variability increased between-subject variability and vice versa). The sample size required to detect a given effect size was also compromised by the preprocessing strategy, resulting in up to 80% increases in sample size needed to detect a 5% difference in 5-HTT binding. This is the first study to systematically investigate and demonstrate the effect of choosing different preprocessing strategies on the outcome of dynamic PET studies. We provide a framework to show how optimal and maximally powered neuroimaging results can be obtained by choosing appropriate preprocessing strategies and we provide recommendations depending on the study design. In addition, the results contribute to a better understanding of methodological uncertainty and variability in preprocessing decisions for future group- and/or longitudinal PET studies.

Structural changes in amygdala nuclei, hippocampal subfields and cortical thickness following electroconvulsive therapy in treatment-resistant depression: longitudinal analysis

BACKGROUND

Electroconvulsive therapy (ECT) is the treatment of choice for severe mental illness including treatment-resistant depression (TRD). Increases in volume of the hippocampus and amygdala following ECT have consistently been reported.AimsTo investigate neuroplastic changes after ECT in specific hippocampal subfields and amygdala nuclei using high-resolution structural magnetic resonance imaging (MRI) (trial registration: clinicaltrials.gov - NCT02379767).

METHOD

MRI scans were carried out in 14 patients (11 women, 46.9 years (s.d. = 8.1)) with unipolar TRD twice before and once after a series of right unilateral ECT in a pre-post study design. Volumes of subcortical structures, including subfields of the hippocampus and amygdala, and cortical thickness were extracted using FreeSurfer. The effect of ECT was tested using repeated-measures ANOVA. Correlations of imaging and clinical parameters were explored.

RESULTS

Increases in volume of the right hippocampus by 139.4 mm3 (s.d. = 34.9), right amygdala by 82.3 mm3 (s.d. = 43.9) and right putamen by 73.9 mm3 (s.d. = 77.0) were observed. These changes were localised in the basal and lateral nuclei, and the corticoamygdaloid transition area of the amygdala, the hippocampal-amygdaloid transition area and the granule cell and molecular layer of the dentate gyrus. Cortical thickness increased in the temporal, parietal and insular cortices of the right hemisphere.

CONCLUSIONS

Following ECT structural changes were observed in hippocampal subfields and amygdala nuclei that are specifically implicated in the pathophysiology of depression and stress-related disorders and retain a high potential for neuroplasticity in adulthood.Declaration of interestS.K. has received grants/research support, consulting fees and/or honoraria within the past 3 years from Angelini, AOP Orphan Pharmaceuticals AG, AstraZeneca, Celegne GmbH, Eli Lilly, Janssen-Cilag Pharma GmbH, KRKA-Pharma, Lundbeck A/S, Neuraxpharm, Pfizer, Pierre Fabre, Schwabe and Servier. R.L. received travel grants and/or conference speaker honoraria from Shire, AstraZeneca, Lundbeck A/S, Dr. Willmar Schwabe GmbH, Orphan Pharmaceuticals AG, Janssen-Cilag Pharma GmbH, and Roche Austria GmbH.

Parcellation of the Human Cerebral Cortex Based on Molecular Targets in the Serotonin System Quantified by Positron Emission Tomography In vivo

Parcellation of distinct areas in the cerebral cortex has a long history in neuroscience and is of great value for the study of brain function, specialization, and alterations in neuropsychiatric disorders. Analysis of cytoarchitectonical features has revealed their close association with molecular profiles based on protein density. This provides a rationale for the use of in vivo molecular imaging data for parcellation of the cortex with the advantage of whole-brain coverage. In the current work, parcellation was based on expression of key players of the serotonin neurotransmitter system. Positron emission tomography was carried out for the quantification of serotonin 1A (5-HT1A, n = 30) and 5-HT2A receptors (n = 22), the serotonin-degrading enzyme monoamine oxidase A (MAO-A, n = 32) and the serotonin transporter (5-HTT, n = 24) in healthy participants. Cortical protein distribution maps were obtained using surface-based quantification. Based on k-means clustering, silhouette criterion and bootstrapping, five distinct clusters were identified as the optimal solution. The defined clusters proved of high explanatory value for the effects of psychotropic drugs acting on the serotonin system, such as antidepressants and psychedelics. Therefore, the proposed method constitutes a sensible approach towards integration of multimodal imaging data for research and development in neuropharmacology and psychiatry.