Clinical brain PET research must embrace multi-centre collaboration and data sharing or risk its demise

Application of positron emission tomography in psychiatry-methodological developments and future directions

Mental disorders represent an increasing source of disability and high costs for societies globally. Molecular imaging techniques such as positron emission tomography (PET) represent powerful tools with the potential to advance knowledge regarding disease mechanisms, allowing the development of new treatment approaches. Thus far, most PET research on pathophysiology in psychiatric disorders has focused on the monoaminergic neurotransmission systems, and although a series of discoveries have been made, the results have not led to any material changes in clinical practice. We outline areas of methodological development that can address some of the important obstacles to fruitful progress. First, we point towards new radioligands and targets that can lead to the identification of processes upstream, or parallel to disturbances in monoaminergic systems. Second, we describe the development of new methods of PET data quantification and PET systems that may facilitate research in psychiatric populations. Third, we review the application of multimodal imaging that can link molecular imaging data to other aspects of brain function, thus deepening our understanding of disease processes. Fourth, we highlight the need to develop imaging study protocols to include longitudinal and interventional paradigms, as well as frameworks to assess dimensional symptoms such that the field can move beyond cross-sectional studies within current diagnostic boundaries. Particular effort should be paid to include also the most severely ill patients. Finally, we discuss the importance of harmonizing data collection and promoting data sharing to reach the desired sample sizes needed to fully capture the phenotype of psychiatric conditions.

No association between cortical dopamine D2 receptor availability and cognition in antipsychotic-naive first-episode psychosis

Cognitive impairment is an important predictor of disability in schizophrenia. Dopamine neurotransmission in cortical brain regions has been suggested to be of importance for higher-order cognitive processes. The aim of this study was to examine the relationship between extrastriatal dopamine D2-R availability and cognitive function, using positron emission tomography and the high-affinity D2-R radioligand [¹¹C]FLB 457, in an antipsychotic-naive sample of 18 first-episode psychosis patients and 16 control subjects. We observed no significant associations between D2-R binding in the dorsolateral prefrontal cortex or hippocampus (β = 0.013–0.074, partial r = −0.037–0.273, p = 0.131–0.841). Instead, using Bayesian statistics, we found moderate support for the null hypothesis of no relationship (BF_H0:H1 = 3.3–8.2). Theoretically, our findings may suggest a lack of detrimental effects of D2-R antagonist drugs on cognition in schizophrenia patients, in line with clinical observations.

Harmonisation of PET/CT contrast recovery performance for brain studies

PURPOSE

In order to achieve comparability of image quality, harmonisation of PET system performance is imperative. In this study, prototype harmonisation criteria for PET brain studies were developed.

METHODS

Twelve clinical PET/CT systems (4 GE, 4 Philips, 4 Siemens, including SiPM-based "digital" systems) were used to acquire 30-min PET scans of a Hoffman 3D Brain phantom filled with ~ 33 kBq·mL^-1 [¹⁸F]FDG. Scan data were reconstructed using various reconstruction settings. The images were rigidly coregistered to a template (voxel size 1.17 × 1.17 × 2.00 mm³) onto which several volumes of interest (VOIs) were defined. Recovery coefficients (RC) and grey matter to white matter ratios (GMWMr) were derived for eroded (denoted in the text by subscript e) and non-eroded grey (GM) and white (WM) matter VOIs as well as a mid-phantom cold spot (VOI_cold) and VOIs from the Hammers atlas. In addition, left-right hemisphere differences and voxel-by-voxel differences compared to a reference image were assessed.

RESULTS

Systematic differences were observed for reconstructions with and without point-spread-function modelling (PSF_ON and PSF_OFF, respectively). Normalising to image-derived activity, upper and lower limits ensuring image comparability were as follows: for PSF_ON, RC_GMe = [0.97-1.01] and GMWMr_e = [3.51-3.91] for eroded VOI and RC_GM = [0.78-0.83] and GMWMr = [1.77-2.06] for non-eroded VOI, and for PSF_OFF, RC_GMe = [0.92-0.99] and GMWMr_e = [3.14-3.68] for eroded VOI and RC_GM = [0.75-0.81] and GMWMr = [1.72-1.95] for non-eroded VOI.

CONCLUSIONS

To achieve inter-scanner comparability, we propose selecting reconstruction settings based on RC_GMe and GMWMr_e as specified in "Results". These proposed standards should be tested prospectively to validate and/or refine the harmonisation criteria.

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.