Test-retest reliability and convergent validity of (R)-[11C]PK11195 outcome measures without arterial input function

[18F]LW223 has low non-displaceable binding in murine brain, enabling high sensitivity TSPO PET imaging

Neuroinflammation is associated with a number of brain diseases, making it a common feature of cerebral pathology. Among the best-known biomarkers for neuroinflammation in Positron Emission Tomography (PET) research is the 18 kDa translocator protein (TSPO). This study aims to investigate the binding kinetics of a novel TSPO PET radiotracer, [18F]LW223, in mice and specifically assess its volume of non-displaceable binding (VND) in brain as well as investigate the use of simplified analysis approaches for quantification of [18F]LW223 PET data. Adult male mice were injected with [18F]LW223 and varying concentrations of LW223 (0.003-0.55 mg/kg) to estimate VND of [18F]LW223. Dynamic PET imaging with arterial input function studies and radiometabolite studies were conducted. Simplified quantification methods, standard uptake values (SUV) and apparent volume of distribution (VTapp), were investigated. [18F]LW223 had low VND in the brain (<10% of total binding) and low radiometabolism (∼15-20%). The 2-tissue compartment model provided the best fit for [18F]LW223 PET data, although its correlation with SUV90-120min or VTapp allowed for [18F]LW223 brain PET data quantification in healthy animals while using simpler experimental and analytical approaches. [18F]LW223 has the required properties to become a successful TSPO PET radiotracer.

Inflammation and viral infection as disease modifiers in schizophrenia

Numerous studies have now implicated a role for inflammation in schizophrenia. However, many aspects surrounding this aspect of the disease are still controversial. This controversy has been driven by conflicting evidence on the role of both pro-and anti-inflammatory factors and by often contentious findings concerning cytokine and immune cell profiles in the central nervous system and periphery. Current evidence supports the point that interleukin-6 is elevated in CSF, but does not support activation of microglia, resident macrophage-like cells in the brain. Furthermore, the mechanisms involving transit of the peripheral immune system factors across the blood brain barrier to central parenchyma have still not been completely elucidated. This process appears to involve perivascular macrophages and accompanying dendritic cells retained in the parenchyma by the chemokine and cytokine composition of the surrounding milieu. In addition, a number of studies have shown that this can be modulated by infection with viruses such as herpes simplex virus type I which may disrupt antigen presentation in the perivascular space, with long-lasting consequences. In this review article, we discuss the role of inflammation and viral infection as potential disease modifiers in schizophrenia. The primary viral hit may occur in the fetus in utero, transforming the immune response regulatory T-cells or the virus may secondarily remain latent in immune cells or neurons and modify further immune responses in the developing individual. It is hoped that unraveling this pathway further and solidifying our understanding of the pathophysiological mechanisms involved will pave the way for future studies aimed at identification and implementation of new biomarkers and drug targets. This may facilitate the development of more effective personalized therapies for individuals suffering with schizophrenia.

Textural properties of microglial activation in Alzheimer's disease as measured by (R)-[11C]PK11195 PET

Alzheimer's disease is the most common form of dementia worldwide, accounting for 60-70% of diagnosed cases. According to the current understanding of molecular pathogenesis, the main hallmarks of this disease are the abnormal accumulation of amyloid plaques and neurofibrillary tangles. Therefore, biomarkers reflecting these underlying biological mechanisms are recognized as valid tools for an early diagnosis of Alzheimer's disease. Inflammatory mechanisms, such as microglial activation, are known to be involved in Alzheimer's disease onset and progression. This activated state of the microglia is associated with increased expression of the translocator protein 18 kDa. On that account, PET tracers capable of measuring this signature, such as (R)-[¹¹C]PK11195, might be instrumental in assessing the state and evolution of Alzheimer's disease. This study aims to investigate the potential of Gray Level Co-occurrence Matrix-based textural parameters as an alternative to conventional quantification using kinetic models in (R)-[¹¹C]PK11195 PET images. To achieve this goal, kinetic and textural parameters were computed on (R)-[¹¹C]PK11195 PET images of 19 patients with an early diagnosis of Alzheimer's disease and 21 healthy controls and submitted separately to classification using a linear support vector machine. The classifier built using the textural parameters showed no inferior performance compared to the classical kinetic approach, yielding a slightly larger classification accuracy (accuracy of 0.7000, sensitivity of 0.6957, specificity of 0.7059 and balanced accuracy of 0.6967). In conclusion, our results support the notion that textural parameters may be an alternative to conventional quantification using kinetic models in (R)-[¹¹C]PK11195 PET images. The proposed quantification method makes it possible to use simpler scanning procedures, which increase patient comfort and convenience. We further speculate that textural parameters may also provide an alternative to kinetic analysis in (R)-[¹¹C]PK11195 PET neuroimaging studies involving other neurodegenerative disorders. Finally, we recognize that the potential role of this tracer is not in diagnosis but rather in the assessment and progression of the diffuse and dynamic distribution of inflammatory cell density in this disorder as a promising therapeutic target.

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.

Image Quantification for TSPO PET with a Novel Image-Derived Input Function Method

There is a growing interest in using 18F-DPA-714 PET to study neuroinflammation and microglial activation through imaging the 18-kDa translocator protein (TSPO). Although quantification of 18F-DPA-714 binding can be achieved through kinetic modeling analysis with an arterial input function (AIF) measured with blood sampling procedures, the invasiveness of such procedures has been an obstacle for wide application. To address these challenges, we developed an image-derived input function (IDIF) that noninvasively estimates the arterial input function from the images acquired for 18F-DPA-714 quantification. Methods: The method entails three fully automatic steps to extract the IDIF, including a segmentation of voxels with highest likelihood of being the arterial blood over the carotid artery, a model-based matrix factorization to extract the arterial blood signal, and a scaling optimization procedure to scale the extracted arterial blood signal into the activity concentration unit. Two cohorts of human subjects were used to evaluate the extracted IDIF. In the first cohort of five subjects, arterial blood sampling was performed, and the calculated IDIF was validated against the measured AIF through the comparison of distribution volumes from AIF (VT,AIF) and IDIF (VT,IDIF). In the second cohort, PET studies from twenty-eight healthy controls without arterial blood sampling were used to compare VT,IDIF with VT,REF measured using a reference region-based analysis to evaluate whether it can distinguish high-affinity (HAB) and mixed-affinity (MAB) binders. Results: In the arterial blood-sampling cohort, VT derived from IDIF was found to be an accurate surrogate of the VT from AIF. The bias of VT, IDIF was −5.8 ± 7.8% when compared to VT,AIF, and the linear mixed effect model showed a high correlation between VT,AIF and VT, IDIF (p < 0.001). In the nonblood-sampling cohort, VT, IDIF showed a significance difference between the HAB and MAB healthy controls. VT, IDIF and standard uptake values (SUV) showed superior results in distinguishing HAB from MAB subjects than VT,REF. Conclusions: A novel IDIF method for 18F-DPA-714 PET quantification was developed and evaluated in this study. This IDIF provides a noninvasive alternative measurement of VT to quantify the TSPO binding of 18F-DPA-714 in the human brain through dynamic PET scans.

Kinetic modeling and parameter estimation of TSPO PET imaging in the human brain

PURPOSE

Translocator protein 18-kDa (TSPO) imaging with positron emission tomography (PET) is widely used in research studies of brain diseases that have a neuro-immune component. Quantification of TSPO PET images, however, is associated with several challenges, such as the lack of a reference region, a genetic polymorphism affecting the affinity of the ligand for TSPO, and a strong TSPO signal in the endothelium of the brain vessels. These challenges have created an ongoing debate in the field about which type of quantification is most useful and whether there is an appropriate simplified model.

METHODS

This review focuses on the quantification of TSPO radioligands in the human brain. The various methods of quantification are summarized, including the gold standard of compartmental modeling with metabolite-corrected input function as well as various alternative models and non-invasive approaches. Their advantages and drawbacks are critically assessed.

RESULTS AND CONCLUSIONS

Researchers employing quantification methods for TSPO should understand the advantages and limitations associated with each method. Suggestions are given to help researchers choose between these viable alternative methods.

Supervised clustering for TSPO PET imaging

PURPOSE

This technical note seeks to act as a practical guide for implementing a supervised clustering algorithm (SVCA) reference region approach and to explain the main strengths and limitations of the technique in the context of 18-kilodalton translocator protein (TSPO) positron emission tomography (PET) studies in experimental medicine.

BACKGROUND

TSPO PET is the most widely used imaging technique for studying neuroinflammation in vivo in humans. Quantifying neuroinflammation with PET can be a challenging and invasive procedure, especially in frail patients, because it often requires blood sampling from an arterial catheter. A widely used alternative to arterial sampling is SVCA, which identifies the voxels with minimal specific binding in the PET images, thus extracting a pseudo-reference region for non-invasive quantification. Unlike other reference region approaches, SVCA does not require specification of an anatomical reference region a priori, which alleviates the limitation of TSPO contamination in anatomically-defined reference regions in individuals with underlying inflammatory processes. Furthermore, SVCA can be applied to any TSPO PET tracer across different neurological and neuropsychiatric conditions, providing noninvasivequantification of TSPO expression.

METHODS

We provide an overview of the development of SVCA as well as step-by-step instructions for implementing SVCA with suggestions for specific settings. We review the literature on SVCAapplications using first- and second- generation TSPO PET tracers and discuss potential clinically relevant limitations and applications.

CONCLUSIONS

The correct implementation of SVCA can provide robust and reproducible estimates of brain TSPO expression. This review encourages the standardisation of SVCA methodology in TSPO PET analysis, ultimately aiming to improve replicability and comparability across study sites.

Minimally invasive quantification of cerebral P2X7R occupancy using dynamic [18F]JNJ-64413739 PET and MRA-driven image derived input function

[¹⁸F]JNJ-64413739 has been evaluated as PET-ligand for in vivo quantification of purinergic receptor subtype 7 receptor (P2X7R) using Logan graphical analysis with a metabolite-corrected arterial plasma input function. In the context of a P2X7R PET dose occupancy study, we evaluated a minimally invasive approach by limiting arterial sampling to baseline conditions. Meanwhile, post dose distribution volumes (V_T) under blocking conditions were estimated by combining baseline blood to plasma ratios and metabolite fractions with an MR angiography driven image derived input function (IDIF). Regional postdose V_T,IDIF values were compared with corresponding V_T,AIF estimates using a arterial input function (AIF), in terms of absolute values, test–retest reliability and receptor occupancy. Compared to an invasive AIF approach, postdose V_T,IDIF values and corresponding receptor occupancies showed only limited bias (Bland–Altman analysis: 0.06 ± 0.27 and 3.1% ± 6.4%) while demonstrating a high correlation (Spearman ρ = 0.78 and ρ = 0.98 respectively). In terms of test–retest reliability, regional intraclass correlation coefficients were 0.98 ± 0.02 for V_T,IDIF compared to 0.97 ± 0.01 for V_T,AIF. These results confirmed that a postdose IDIF, guided by MR angiography and using baseline blood and metabolite data, can be considered for accurate [¹⁸F]JNJ-64413739 PET quantification in a repeated PET study design, thus avoiding multiple invasive arterial sampling and increasing dosing flexibility.

Population-based input function for TSPO quantification and kinetic modeling with [11C]-DPA-713

INTRODUCTION

Quantitative positron emission tomography (PET) studies of neurodegenerative diseases typically require the measurement of arterial input functions (AIF), an invasive and risky procedure. This study aims to assess the reproducibility of [11C]DPA-713 PET kinetic analysis using population-based input function (PBIF). The final goal is to possibly eliminate the need for AIF.

MATERIALS AND METHODS

Eighteen subjects including six healthy volunteers (HV) and twelve Parkinson disease (PD) subjects from two [11C]-DPA-713 PET studies were included. Each subject underwent 90 min of dynamic PET imaging. Five healthy volunteers underwent a test-retest scan within the same day to assess the repeatability of the kinetic parameters. Kinetic modeling was carried out using the Logan total volume of distribution (VT) model. For each data set, kinetic analysis was performed using a patient-specific AIF (PSAIF, ground-truth standard) and then repeated using the PBIF. PBIF was generated using the leave-one-out method for each subject from the remaining 17 subjects and after normalizing the PSAIFs by 3 techniques: (a) Weightsubject×DoseInjected, (b) area under AIF curve (AUC), and (c) Weightsubject×AUC. The variability in the VT measured with PSAIF, in the test-retest study, was determined for selected brain regions (white matter, cerebellum, thalamus, caudate, putamen, pallidum, brainstem, hippocampus, and amygdala) using the Bland-Altman analysis and for each of the 3 normalization techniques. Similarly, for all subjects, the variabilities due to the use of PBIF were assessed.

RESULTS

Bland-Altman analysis showed systematic bias between test and retest studies. The corresponding mean bias and 95% limits of agreement (LOA) for the studied brain regions were 30% and ± 70%. Comparing PBIF- and PSAIF-based VT estimate for all subjects and all brain regions, a significant difference between the results generated by the three normalization techniques existed for all brain structures except for the brainstem (P-value = 0.095). The mean % difference and 95% LOA is -10% and ±45% for Weightsubject×DoseInjected; +8% and ±50% for AUC; and +2% and ± 38% for Weightsubject×AUC. In all cases, normalizing by Weightsubject×AUC yielded the smallest % bias and variability (% bias = ±2%; LOA = ±38% for all brain regions). Estimating the reproducibility of PBIF-kinetics to PSAIF based on disease groups (HV/PD) and genotype (MAB/HAB), the average VT values for all regions obtained from PBIF is insignificantly higher than PSAIF (%difference = 4.53%, P-value = 0.73 for HAB; and %difference = 0.73%, P-value = 0.96 for MAB). PBIF also tends to overestimate the difference between PD and HV for HAB (% difference = 32.33% versus 13.28%) and underestimate it in MAB (%difference = 6.84% versus 20.92%).

CONCLUSIONS

PSAIF kinetic results are reproducible with PBIF, with variability in VT within that obtained for the test-retest studies. Therefore, VT assessed using PBIF-based kinetic modeling is clinically feasible and can be an alternative to PSAIF.

Dopamine and Neuroinflammation in Schizophrenia - Interpreting the Findings from Translocator Protein (18kDa) PET Imaging

Schizophrenia is a complex disease whose pathophysiology is not yet fully understood. In addition to the long prevailing dopaminergic hypothesis, the evidence suggests that neuroinflammation plays a role in the pathophysiology of the disease. Recent studies using positron emission tomography (PET) that target a 18kDa translocator protein (TSPO) in activated microglial cells in an attempt to measure neuroinflammation in patients have shown a decrease or a lack of an increase in TSPO binding. Many biological and methodological considerations have been formulated to explain these findings. Although dopamine has been described as an immunomodulatory molecule, its potential role in neuroinflammation has not been explored in the aforementioned studies. In this review, we discuss the interactions between dopamine and neuroinflammation in psychotic states. Dopamine may inhibit neuroinflammation in activated microglia. Proinflammatory molecules released from microglia may decrease dopaminergic transmission. This could potentially explain why the levels of neuroinflammation in the brain of patients with schizophrenia seem to be unchanged or decreased compared to those in healthy subjects. However, most data are indirect and are derived from animal studies or from studies performed outside the field of schizophrenia. Further studies are needed to combine TSPO and dopamine imaging to study the association between microglial activation and dopamine system function.

Positron Emission Tomography After Ischemic Brain Injury: Current Challenges and Future Developments

Positron emission tomography (PET) is widely used in clinical and animal studies, along with the development of diverse tracers. The biochemical characteristics of PET tracers may help uncover the pathophysiological consequences of cardiac arrest (CA) and ischemic stroke, which include cerebral ischemia and reperfusion, depletion of oxygen and glucose, and neuroinflammation. PubMed was searched for studies of the application of PET for "cardiac arrest," "ischemic stroke," and "targeted temperature management." Available studies were included and classified according to the biochemical properties involved and metabolic processes of PET tracers, and were summarized. The mechanisms of ischemic brain injuries were investigated by PET with various tracers to elucidate the pathological process from the initial decrease of cerebral blood flow (CBF) to the subsequent abnormalities in energy and oxygen metabolism, to the monitoring of inflammation. In general, the trends of cerebral blood flow and oxygen metabolism after ischemic attack are not unidirectional but closely related to the time point of injury and recovery. Glucose metabolism after injury showed significant differences in different brain regions whereas global cerebral metabolic rate of glucose (CMRglc) declined. PET monitoring of neuroinflammation shows comparable efficacy to immunostaining. The technology of PET targeting in brain metabolism and the development of tracers provide new tools to track and evaluate the brain's pathological changes after ischemic brain injury. Despite no existing evidence for an available PET-based prediction method, discoveries of new tracers are expected to provide more possibilities for the whole field.

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.

Molecular imaging of multiple sclerosis: from the clinical demand to novel radiotracers

Background

Brain PET imaging with different tracers is mainly clinically used in the field of neurodegenerative diseases and brain tumors. In recent years, the potential usefulness of PET has also gained attention in the field of MS. In fact, MS is a complex disease and several processes can be selected as a target for PET imaging. The use of PET with several different tracers has been mainly evaluated in the research setting to investigate disease pathophysiology (i.e. phenotypes, monitoring of progression) or to explore its use a surrogate end-point in clinical trials.

Results

We have reviewed PET imaging studies in MS in humans and animal models. Tracers have been grouped according to their pathophysiological targets (ie. tracers for myelin kinetic, neuroinflammation, and neurodegeneration). The emerging clinical indication for brain PET imaging in the differential diagnosis of suspected tumefactive demyelinated plaques as well as the clinical potential provided by PET images in view of the recent introduction of PET/MR technology are also addressed.

Conclusion

While several preclinical and fewer clinical studies have shown results, full-scale clinical development programs are needed to translate molecular imaging technologies into a clinical reality that could ideally fit into current precision medicine perspectives.

Accuracy and reliability of [11C]PBR28 specific binding estimated without the use of a reference region

[¹¹C]PBR28 is a positron emission tomography radioligand used to examine the expression of the 18 kDa translocator protein (TSPO). TSPO is located in glial cells and can function as a marker for immune activation. Since TSPO is expressed throughout the brain, no true reference region exists. For this reason, an arterial input function is required for accurate quantification of [¹¹C]PBR28 binding and the most common outcome measure is the total distribution volume (V_T). Notably, V_T reflects both specific binding and non-displaceable binding. Therefore, estimates of specific binding, such as binding potential (e.g. BP_ND) and specific distribution volume (V_S) should theoretically be more sensitive to underlying differences in TSPO expression. It is unknown, however, if unbiased and accurate estimates of these outcome measures are obtainable for [¹¹C]PBR28. The Simultaneous Estimation (SIME) method uses time-activity-curves from multiple brain regions with the aim to obtain a brain-wide estimate of the non-displaceable distribution volume (V_ND), which can subsequently be used to improve the estimation of BP_ND and V_S. In this study we evaluated the accuracy of SIME-derived V_ND, and the reliability of resulting estimates of specific binding for [¹¹C]PBR28, using a combination of simulation experiments and in vivo studies in healthy humans. The simulation experiments, based on data from 54 unique [¹¹C]PBR28 examinations, showed that V_ND values estimated using SIME were both precise and accurate. Data from a pharmacological competition challenge (n = 5) showed that SIME provided V_ND values that were on average 19% lower than those obtained using the Lassen plot, but similar to values obtained using the Likelihood-Estimation of Occupancy technique. Test-retest data (n = 11) showed that SIME-derived V_S values exhibited good reliability and precision, while larger variability was observed in SIME-derived BP_ND values. The results support the use of SIME for quantifying specific binding of [¹¹C]PBR28, and suggest that V_S can be used in complement to the conventional outcome measure V_T. Additional studies in patient cohorts are warranted.