Cerebral serotonin transporter measurements with [11C]DASB: A review on acquisition and preprocessing across 21 PET centres

The association between brain serotonin transporter binding and impulsivity and aggression in healthy individuals

The serotonin system plays a critical role in the modulation of impulsive aggression. Although serotonin transporters (SERT) are key in modulating synaptic serotonin levels, few studies have investigated the role of SERT levels in human impulsive aggression. The aim of this study was to investigate whether brain SERT levels are associated with trait impulsive aggression. We included 148 healthy individuals (mean age 29.3 ± 13.0, range 18-80 years, 91 females) who had undergone positron emission positron (PET) examinations with the SERT tracer [11C]DASB and filled in self-report questionnaires of trait aggression, trait impulsivity and state aggression. We evaluated the association between cerebral SERT binding (BPND) and trait impulsive aggression in a latent variable model, with one latent variable (LVSERT) modelled from SERT BPND in frontostriatal and frontolimbic networks implicated in impulsive aggression, and another latent variable (LVIA) modelled from various trait measures of impulsivity and aggression. The LVSERT was not significantly associated with the LVIA (p = 0.8). Post-hoc univariate analyses did not reveal any significant associations between regional SERT levels and trait aggression, trait impulsivity or state aggression, but we found that state aggression at the day of PET scan was significantly lower in LA/LA homozygotes vs S-carriers of the 5-HTTLPR gene (p = 0.008). We conclude that brain SERT binding was not related to variations in trait impulsive aggression or state aggression. Our findings do not support that SERT is involved in mediating the serotonergic effects on aggression and impulsivity, at least not in individuals with non-pathological levels of impulsive aggression.

Open and reproducible neuroimaging: From study inception to publication

Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources. Even experienced researchers in the topic find it hard to navigate the ecosystem of tools and to make sustainable choices. Here, we provide an integrated overview of community-developed resources that can support collaborative, open, reproducible, replicable, robust and generalizable neuroimaging throughout the entire research cycle from inception to publication and across different neuroimaging modalities. We review tools and practices supporting study inception and planning, data acquisition, research data management, data processing and analysis, and research dissemination. An online version of this resource can be found at https://oreoni.github.io. We believe it will prove helpful for researchers and institutions to make a successful and sustainable move towards open and reproducible science and to eventually take an active role in its future development.

Serotonin 1B receptor density mapping of the human brainstem using positron emission tomography and autoradiography

The serotonin 1B (5-HT_1B) receptor has lately received considerable interest in relation to psychiatric and neurological diseases, partly due to findings based on quantification using Positron Emission Tomography (PET). Although the brainstem is an important structure in this regard, PET radioligand binding quantification in brainstem areas often shows poor reliability. This study aims to improve PET quantification of 5-HT_1B receptor binding in the brainstem.Volumes of interest (VOIs) were selected based on a 3D [³H]AZ10419369 Autoradiography brainstem model, which visualized 5-HT_1B receptor distribution in high resolution. Two previously developed VOI delineation methods were tested and compared to a conventional manual method. For a method based on template data, a [¹¹C]AZ10419369 PET template was created by averaging parametric binding potential (BP_ND) images of 52 healthy subjects. VOIs were generated based on a predefined volume and BP_ND thresholding and subsequently applied to test-retest [¹¹C]AZ10419369 parametric BP_ND images of 8 healthy subjects. For a method based on individual subject data, VOIs were generated directly on each individual parametric image.Both methods showed improved reliability compared to a conventional manual VOI. The VOIs created with [¹¹C]AZ10419369 template data can be automatically applied to future PET studies measuring 5-HT_1B receptor binding in the brainstem.

Imaging Histamine H3 Receptors with Positron Emission Tomography

Positron emission tomography (PET) provides a unique tool to study the biochemistry of the human brain in vivo. By using PET probes that are binding selectively to certain receptor subtypes, brain PET allows the quantification of receptor levels in various brain areas of human subjects. This approach has the potential to reveal abnormal receptor expressions that may contribute to the physiopathology of some psychiatric and neurological disorders. This approach also has the potential to assist in the drug development process by determining receptor occupancy in vivo allowing selection of proper drug dosage to produce therapeutic effects. Several PET tracers have been developed for histamine H3 receptors (H3R). However, despite the potential of PET to elucidate the role of H3R in vivo, only limited work has been conducted so far. This article reviews the work that has been done in this area. Notably, we will cover the limitations of the first-generation PET radioligand for H3R and present the advantages of novel radioligands that promise an explosion of clinical PET research on the role of H3R in vivo.

In Vivo Cerebral Translocator Protein (TSPO) Binding and Its Relationship with Blood Adiponectin Levels in Treatment-Naïve Young Adults with Major Depression: A [11C]PK11195 PET Study

Adiponectin is an adipokine that mediates cellular cholesterol efflux and plays important roles in neuroinflammatory processes. In this study, we undertook positron emission tomography (PET) with the translocator protein (TSPO) ligand [¹¹C]PK11195 and measured serum adiponectin levels in groups of treatment-naïve young adult patients with major depressive disorder (MDD) and matched healthy controls. Thirty treatment-naïve MDD patients (median age: 24 years) and twenty-three healthy controls underwent [¹¹C]PK11195 PET. We quantified TSPO availability in brain as the [¹¹C]PK11195 binding potential (BP_ND) using a reference tissue model in conjunction with the supervised cluster analysis (SVCA4) algorithm. Age, sex distribution, body mass index, and serum adiponectin levels did not differ between the groups. Between-group analysis using a region-of-interest approach showed significantly higher [¹¹C]PK11195 BP_ND in the left anterior and right posterior cingulate cortices in MDD patients than in controls. Serum adiponectin levels had significant negative correlations with [¹¹C]PK11195 BP_ND in the bilateral hippocampus in MDD patients, but significant positive correlations in the bilateral hippocampus in the control group. Our results indicate significantly higher TSPO binding in the anterior and posterior cingulate cortices in treatment-naïve young MDD patients, suggesting microglial activation in these limbic regions, which are involved in cognitive and emotional processing. The opposite correlations between [¹¹C]PK11195 BP_ND in the hippocampus with serum adiponectin levels in MDD and control groups suggest that microglial activation in the hippocampus may respond differentially to adiponectin signaling in MDD and healthy subjects, possibly with respect to microglial phenotype.

Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge

The reproducibility of findings is a compelling methodological problem that the neuroimaging community is facing these days. The lack of standardized pipelines for image processing, quantification and statistics plays a major role in the variability and interpretation of results, even when the same data are analysed. This problem is well-known in MRI studies, where the indisputable value of the method has been complicated by a number of studies that produce discrepant results. However, any research domain with complex data and flexible analytical procedures can experience a similar lack of reproducibility. In this paper we investigate this issue for brain PET imaging. During the 2018 NeuroReceptor Mapping conference, the brain PET community was challenged with a computational contest involving a simulated neurotransmitter release experiment. Fourteen international teams analysed the same imaging dataset, for which the ground-truth was known. Despite a plurality of methods, the solutions were consistent across participants, although not identical. These results should create awareness that the increased sharing of PET data alone will only be one component of enhancing confidence in neuroimaging results and that it will be important to complement this with full details of the analysis pipelines and procedures that have been used to quantify data.

False positive rates in positron emission tomography (PET) voxelwise analyses

Issues with inflated false positive rates (FPRs) in brain imaging have recently received significant attention. However, to what extent FPRs present a problem for voxelwise analyses of Positron Emission Tomography (PET) data remains unknown. In this work, we evaluate the FPR using real PET data under group assignments that should yield no significant results after correcting for multiple comparisons. We used data from 159 healthy participants, imaged with the serotonin transporter ([¹¹C]DASB; N = 100) or the 5-HT₄ receptor ([¹¹C]SB207145; N = 59). Using this null data, we estimated the FPR by performing 1,000 group analyses with randomly assigned groups of either 10 or 20, for each tracer, and corrected for multiple comparisons using parametric Monte Carlo simulations (MCZ) or non-parametric permutation testing. Our analyses show that for group sizes of 10 or 20, the FPR for both tracers was 5-99% using MCZ, much higher than the expected 5%. This was caused by a heavier-than-Gaussian spatial autocorrelation, violating the parametric assumptions. Permutation correctly controlled the FPR in all cases. In conclusion, either a conservative cluster forming threshold and high smoothing levels, or a non-parametric correction for multiple comparisons should be performed in voxelwise analyses of brain PET data.

A dual-time-window protocol to reduce acquisition time of dynamic tau PET imaging using [18F]MK-6240

Background

[¹⁸F]MK-6240 is a PET tracer with sub-nanomolar affinity for neurofibrillary tangles. Therefore, tau quantification is possible with [¹⁸F]MK-6240 PET/CT scans, and it can be used for assessment of Alzheimer’s disease. However, long acquisition scans are required to provide fully quantitative estimates of pharmacokinetic parameters. Therefore, on the present study, dual-time-window (DTW) acquisitions was simulated to reduce PET/CT acquisition time, while taking into consideration perfusion changes and possible scanning protocol non-compliance. To that end, time activity curves (TACs) representing a 120-min acquisition (TAC₁₂₀) were simulated using a two-tissue compartment model with metabolite corrected arterial input function from 90-min dynamic [¹⁸F]MK-6240 PET scans of three healthy control subjects and five subjects with mild cognitive impairment or Alzheimer’s disease. Therefore, TACs corresponding to different levels of specific binding were generated and then various perfusion changes were simulated. Next, DTW acquisitions were simulated consisting of an acquisition starting at tracer injection, a break and a second acquisition starting at 90 min post-injection. Finally, non-compliance with the PET/CT scanning protocol were simulated to assess its impact on quantification. All TACs were quantified using reference Logan’s distribution volume ratio (DVR) and standardized uptake value ratio (SUVR₉₀) using the cerebellar cortex as reference region.

Results

It was found that DVR from a DTW protocol with a 60-min break between two 30-min dynamic scans closely approximates the DVR from the uninterrupted TAC₁₂₀, with a regional bias smaller than 2.5%. Moreover, SUVR₉₀ estimates were more susceptible (regional bias ≤ 19%) to changes in perfusion compared to DVR from a DTW TAC (regional bias ≤ 10%). Similarly, SUVR₉₀ was affected by late-time scanning protocol delays reaching an increase of 8% for a 20-min delay, while DVR was not affected (regional bias < 1.5%) by DTW protocol non-compliance.

Conclusions

Therefore, such DTW protocol has the potential to increase patient comfort and throughput without compromising quantitative accuracy and is more reliable against SUVR in terms of perfusion changes and protocol deviations, which could prove beneficial for drug effect assessment and patient follow-up using longitudinal [¹⁸F]MK-6240 PET imaging.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13550-021-00790-x.

Amyloid burden quantification depends on PET and MR image processing methodology

Quantification of amyloid load with positron emission tomography can be useful to assess Alzheimer's Disease in-vivo. However, quantification can be affected by the image processing methodology applied. This study's goal was to address how amyloid quantification is influenced by different semi-automatic image processing pipelines. Images were analysed in their Native Space and Standard Space; non-rigid spatial transformation methods based on maximum a posteriori approaches and tissue probability maps (TPM) for regularisation were explored. Furthermore, grey matter tissue segmentations were defined before and after spatial normalisation, and also using a population-based template. Five quantification metrics were analysed: two intensity-based, two volumetric-based, and one multi-parametric feature. Intensity-related metrics were not substantially affected by spatial normalisation and did not significantly depend on the grey matter segmentation method, with an impact similar to that expected from test-retest studies (≤10%). Yet, volumetric and multi-parametric features were sensitive to the image processing methodology, with an overall variability up to 45%. Therefore, the analysis should be carried out in Native Space avoiding non-rigid spatial transformations. For analyses in Standard Space, spatial normalisation regularised by TPM is preferred. Volumetric-based measurements should be done in Native Space, while intensity-based metrics are more robust against differences in image processing pipelines.

Increased pulmonary serotonin transporter in patients with chronic obstructive pulmonary disease who developed pulmonary hypertension

Purpose

Pulmonary hypertension (PH) is characterized by a progressive remodelling of the pulmonary vasculature resulting in right heart failure and eventually death. The serotonin transporter (SERT) may be involved in the pathogenesis of PH in patients with chronic-obstructive pulmonary disease (COPD). This study investigated for the first time the SERT in vivo availability in the lungs of patients with COPD and PH (COPD+PH).

Methods

SERT availability was assessed using SERT-selective [¹¹C]DASB and positron emission tomography/computed tomography (PET/CT) with dynamic acquisition over 30 min in 4 groups of 5 participants each: COPD, COPD+PH, pulmonary arterial hypertension, and a healthy control (HC). Time activity curves were generated based on a volume of interest within the middle lobe. Tissue-to-blood concentration ratios after 25 to 30 min (TTBR_25–30) served as receptor parameter for group comparison and were corrected for lung tissue attenuation. Participants underwent comprehensive pulmonary workup. Statistical analysis included group comparisons and correlation analysis.

Results

[¹¹C]DASB uptake peak values did not differ among the cohorts after adjusting for lung tissue attenuation, suggesting equal radiotracer delivery. Both the COPD and COPD+PH cohort showed significantly lower TTBR_25–30 values after correction for lung attenuation than HC. Attenuation corrected TTBR_25–30 values were significantly higher in the COPD+PH cohort than those in the COPD cohort and higher in non-smokers than in smokers. They positively correlated with invasively measured severity of PH and inversely with airflow limitation and emphysema. Considering all COPD patients ± PH, they positively correlated with right heart strain (NT-proBNP).

Conclusion

By applying [¹¹C]DASB and PET/CT, semiquantitative measures of SERT availability are demonstrated in the lung vasculature of patients with COPD and/or PH. COPD patients who developed PH show increased pulmonary [¹¹C]DASB uptake compared to COPD patients without PH indicating an implication of pulmonary SERT in the development of PH in COPD patients.

Electronic supplementary material

The online version of this article (10.1007/s00259-020-05056-7) contains supplementary material, which is available to authorized users.

Different preprocessing strategies lead to different conclusions: A [11C]DASB-PET reproducibility study

Positron emission tomography (PET) neuroimaging provides unique possibilities to study biological processes in vivo under basal and interventional conditions. For quantification of PET data, researchers commonly apply different arrays of sequential data analytic methods ("preprocessing pipeline"), but it is often unknown how the choice of preprocessing affects the final outcome. Here, we use an available data set from a double-blind, randomized, placebo-controlled [¹¹C]DASB-PET study as a case to evaluate how the choice of preprocessing affects the outcome of the study. We tested the impact of 384 commonly used preprocessing strategies on a previously reported positive association between the change from baseline in neocortical serotonin transporter binding determined with [¹¹C]DASB-PET, and change in depressive symptoms, following a pharmacological sex hormone manipulation intervention in 30 women. The two preprocessing steps that were most critical for the outcome were motion correction and kinetic modeling of the dynamic PET data. We found that 36% of the applied preprocessing strategies replicated the originally reported finding (p < 0.05). For preprocessing strategies with motion correction, the replication percentage was 72%, whereas it was 0% for strategies without motion correction. In conclusion, the choice of preprocessing strategy can have a major impact on a study outcome.

Guidelines for the content and format of PET brain data in publications and archives: A consensus paper

It is a growing concern that outcomes of neuroimaging studies often cannot be replicated. To counteract this, the magnetic resonance (MR) neuroimaging community has promoted acquisition standards and created data sharing platforms, based on a consensus on how to organize and share MR neuroimaging data. Here, we take a similar approach to positron emission tomography (PET) data. To facilitate comparison of findings across studies, we first recommend publication standards for tracer characteristics, image acquisition, image preprocessing, and outcome estimation for PET neuroimaging data. The co-authors of this paper, representing more than 25 PET centers worldwide, voted to classify information as mandatory, recommended, or optional. Second, we describe a framework to facilitate data archiving and data sharing within and across centers. Because of the high cost of PET neuroimaging studies, sample sizes tend to be small and relatively few sites worldwide have the required multidisciplinary expertise to properly conduct and analyze PET studies. Data sharing will make it easier to combine datasets from different centers to achieve larger sample sizes and stronger statistical power to test hypotheses. The combining of datasets from different centers may be enhanced by adoption of a common set of best practices in data acquisition and analysis.

Kinfitr - an open-source tool for reproducible PET modelling: validation and evaluation of test-retest reliability

Background

In positron emission tomography (PET) imaging, binding is typically estimated by fitting pharmacokinetic models to the series of measurements of radioactivity in the target tissue following intravenous injection of a radioligand. However, there are multiple different models to choose from and numerous analytical decisions that must be made when modelling PET data. Therefore, it is important that analysis tools be adapted to the specific circumstances, and that analyses be documented in a transparent manner. Kinfitr, written in the open-source programming language R, is a tool developed for flexible and reproducible kinetic modelling of PET data, i.e. performing all steps using code which can be publicly shared in analysis notebooks. In this study, we compared outcomes obtained using kinfitr with those obtained using PMOD: a widely used commercial tool.

Results

Using previously collected test-retest data obtained with four different radioligands, a total of six different kinetic models were fitted to time-activity curves derived from different brain regions. We observed good correspondence between the two kinetic modelling tools both for binding estimates and for microparameters. Likewise, no substantial differences were observed in the test-retest reliability estimates between the two tools.

Conclusions

In summary, we showed excellent agreement between the open-source R package kinfitr, and the widely used commercial application PMOD. We, therefore, conclude that kinfitr is a valid and reliable tool for kinetic modelling of PET data.

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.

A new perspective for advanced positron emission tomography-based molecular imaging in neurodegenerative proteinopathies

Recent studies in neurodegenerative conditions have increasingly highlighted that the same neuropathology can trigger different clinical phenotypes or, vice-versa, that similar phenotypes can be triggered by different neuropathologies. This evidence has called for the adoption of a pathology spectrum-based approach to study neurodegenerative proteinopathies. These conditions share brain deposition of abnormal protein aggregates, leading to aberrant biochemical, metabolic, functional, and structural changes. Positron emission tomography (PET) is a well-recognized and unique tool for the in vivo assessment of brain neuropathology, and novel PET techniques are emerging for the study of specific protein species. Today, key applications of PET range from early research and clinical diagnostic tools to their use in clinical trials for both participants screening and outcome evaluation. This position article critically reviews the role of distinct PET molecular tracers for different neurodegenerative proteinopathies, highlighting their strengths, weaknesses, and opportunities, with special emphasis on methodological challenges and future applications.

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.