Quantitative imaging of protein targets in the human brain with PET

Quantifying VMAT2 target occupancy at effective valbenazine doses and comparing to a novel VMAT2 inhibitor: a translational PET study

Positron emission tomography (PET) is frequently used to obtain target occupancy (%TO) of central nervous system (CNS) drug candidates during clinical development. Obtaining %TO with PET can be particularly powerful when the %TO associated with efficacy is known for a protein target. Using the radiotracer [18F]AV-133, the relationship between plasma concentration (PK) and %TO of NBI-750142, an experimental inhibitor of the vesicular monoamine transporter type 2 (VMAT2) was obtained in both nonhuman primate (NHP) and human. This work established [18F]AV-133 PET as capable of providing a VMAT2 inhibitor PK-%TO relationship that translated from NHP to human. To establish the VMAT2%TO benchmark, PET was performed in NHP with NBI-98782, the main active metabolite of valbenazine, and this PK-%TO relationship was used to estimate VMAT2%TO at NBI-98782 exposures associated with valbenazine therapeutic effects in the treatment of tardive dyskinesia (TD). This work defined 85-90% as the VMAT2%TO achieved by exposures associated with daily dosing with 80 mg valbenazine, a dosing regimen known to exhibit a large effect size in the treatment of TD and in the treatment of chorea associated with Huntington's Disease. NBI-750142 was estimated to achieve 36-78% VMAT2 target occupancy at acceptable doses, indicating potential inferiority in conferring clinical benefit compared to valbenazine. It is recommended that the %TO benchmark of valbenazine derived from [18F]AV-133 PET serve as a gold standard biomarker to evaluate novel VMAT2 inhibitors undergoing clinical development.

RED: Residual estimation diffusion for low-dose PET sinogram reconstruction

Recent advances in diffusion models have demonstrated exceptional performance in generative tasks across various fields. In positron emission tomography (PET), the reduction in tracer dose leads to information loss in sinograms. Using diffusion models to reconstruct missing information can improve imaging quality. Traditional diffusion models effectively use Gaussian noise for image reconstructions. However, in low-dose PET reconstruction, Gaussian noise can worsen the already sparse data by introducing artifacts and inconsistencies. To address this issue, we propose a diffusion model named residual estimation diffusion (RED). From the perspective of diffusion mechanism, RED uses the residual between sinograms to replace Gaussian noise in diffusion process, respectively sets the low-dose and full-dose sinograms as the starting point and endpoint of reconstruction. This mechanism helps preserve the original information in the low-dose sinogram, thereby enhancing reconstruction reliability. From the perspective of data consistency, RED introduces a drift correction strategy to reduce accumulated prediction errors during the reverse process. Calibrating the intermediate results of reverse iterations helps maintain the data consistency and enhances the stability of reconstruction process. In the experiments, RED achieved the best performance across all metrics. Specifically, the PSNR metric showed improvements of 2.75, 5.45, and 8.08 dB in DRF4, 20, and 100 respectively, compared to traditional methods. The code is available at: https://github.com/yqx7150/RED.

Bexotegrast Shows Dose-Dependent Integrin αvβ6 Receptor Occupancy in Lungs of Participants with Idiopathic Pulmonary Fibrosis: A Phase 2, Open-Label Clinical Trial

Rationale: Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive disease characterized by dyspnea and loss of lung function. Transforming growth factor-β (TGF-β) activation mediated by αv integrins is central to the pathogenesis of IPF. Bexotegrast (PLN-74809) is an oral, once-daily, dual-selective inhibitor of αvβ6 and αvβ1 integrins under investigation for the treatment of IPF. Positron emission tomography (PET) using an αvβ6-specific PET tracer could confirm target engagement of bexotegrast in the lungs of participants with IPF. Objectives: This Phase 2 study evaluated αvβ6 receptor occupancy in the lung as assessed by changes from baseline in αvβ6 PET tracer uptake, after single-dose administration of bexotegrast to participants with IPF. Methods: In this open-label, single-center study, adults with IPF received up to two single doses of bexotegrast, ranging from 60 to 320 mg with or without background IPF therapy (pirfenidone or nintedanib). At baseline and approximately 4 hours after each orally administered bexotegrast dose, a 60-minute dynamic PET-computed tomography scan was conducted after administration of an αvβ6-specific PET probe ([18F]FP-R01-MG-F2). αvβ6 receptor occupancy by bexotegrast was estimated from the changes in PET tracer uptake after bexotegrast administration. Pharmacokinetics, safety, and tolerability of bexotegrast were also assessed. Results: Eight participants completed the study. Total and unbound plasma bexotegrast concentrations increased in a dose-dependent manner, and regional PET volume of distribution values decreased in a dose- and concentration-dependent manner. The data for volume of distribution fit a simple saturation model, producing an unbound bexotegrast half maximal effective concentration estimate of 3.32 ng/ml. Estimated maximum receptor occupancy was 35%, 53%, 71%, 88%, and 92% after single 60-, 80-, 120-, 240-, and 320-mg doses of bexotegrast, respectively. No treatment-emergent adverse events related to bexotegrast were reported. Conclusions: Dose and concentration-dependent αvβ6 receptor occupancy by bexotegrast was observed by PET imaging, supporting once-daily 160- to 320-mg dosing to evaluate efficacy in clinical trials of IPF. Clinical trial registered with www.clinicaltrials.gov (NCT04072315).

External delay and dispersion correction of automatically sampled arterial blood with dual flow rates

Objective. Arterial sampling for PET imaging often involves continuously measuring the radiotracer activity concentration in blood using an automatic blood sampling system (ABSS). We proposed and validated an external delay and dispersion correction procedure needed when a change in flow rate occurs during data acquisition. We also measured the external dispersion constant of [11C]CURB, [18F]FDG, [18F]FEPPA, and [18F]SynVesT-1.Approach. External delay and dispersion constants were measured for the flow rates of 350, 300, 180, and 150 ml h-1, using 1-minute-long rectangular inputs (n= 10;18F-fluoride in saline). Resulting constants were used to validate the external delay and dispersion corrections (n= 6;18F-fluoride in saline; flow rate change: 350 to 150 ml h-1and 300 to 180 ml h-1); constants were modelled to transition linearly between flow rates. Corrected curves were assessed using the percent area-under-the-curve (AUC) ratio and a modified model selection criterion (MSC). External delay and dispersion constants were measured for various radiotracers using a blood analog (i.e., similar viscoelastic properties).Main results. ABSS outputs were successfully corrected for external delay and dispersion using our proposed method accounting for a change in flow rate. AUC ratio reduced from ∼10% for the uncorrected 350-150 ml h-1output (∼6% for the 300-180 ml h-1) to < 1% after correction when compared to true input (511 keV energy window); approx. 5-fold increase in MSC. Assuming an internal dispersion constant of 5 s, the dispersion constant (internal + external) for [11C]CURB, [18F]FDG, [18F]FEPPA, and [18F]SynVesT-1 was 13, 9, 16, and 10 s, respectively.Significance. This study presented an external delay and dispersion correction procedure needed when a change in flow rate occurs during ABSS data acquisition. Additionally, this is the first study to measure the external delay and dispersion constants using a blood analog solution, a suitable alternative to blood when estimating external dispersion.

PET image reconstruction using weighted nuclear norm maximization and deep learning prior

The ill-posed Positron emission tomography (PET) reconstruction problem usually results in limited resolution and significant noise. Recently, deep neural networks have been incorporated into PET iterative reconstruction framework to improve the image quality. In this paper, we propose a new neural network-based iterative reconstruction method by using weighted nuclear norm (WNN) maximization, which aims to recover the image details in the reconstruction process. The novelty of our method is the application of WNN maximization rather than WNN minimization in PET image reconstruction. Meanwhile, a neural network is used to control the noise originated from WNN maximization. Our method is evaluated on simulated and clinical datasets. The simulation results show that the proposed approach outperforms state-of-the-art neural network-based iterative methods by achieving the best contrast/noise tradeoff with a remarkable contrast improvement on the lesion contrast recovery. The study on clinical datasets also demonstrates that our method can recover lesions of different sizes while suppressing noise in various low-dose PET image reconstruction tasks. Our code is available athttps://github.com/Kuangxd/PETReconstruction.

SPLIT: Statistical Positronium Lifetime Image Reconstruction via Time-Thresholding

Positron emission tomography (PET) is a widely utilized medical imaging modality that uses positron-emitting radiotracers to visualize biochemical processes in a living body. The spatiotemporal distribution of a radiotracer is estimated by detecting the coincidence photon pairs generated through positron annihilations. In human tissue, about 40% of the positrons form positroniums prior to the annihilation. The lifetime of these positroniums is influenced by the microenvironment in the tissue and could provide valuable information for better understanding of disease progression and treatment response. Currently, there are few methods available for reconstructing high-resolution lifetime images in practical applications. This paper presents an efficient statistical image reconstruction method for positronium lifetime imaging (PLI). We also analyze the random triple-coincidence events in PLI and propose a correction method for random events, which is essential for real applications. Both simulation and experimental studies demonstrate that the proposed method can produce lifetime images with high numerical accuracy, low variance, and resolution comparable to that of the activity images generated by a PET scanner with currently available time-of-flight resolution.

Quantitative Brain Amyloid PET

Since the development of amyloid tracers for PET imaging, there has been interest in quantifying amyloid burden in the brains of patients with Alzheimer disease. Quantitative amyloid PET imaging is poised to become a valuable approach in disease staging, theranostics, monitoring, and as an outcome measure for interventional studies. Yet, there are significant challenges and hurdles to overcome before it can be implemented into widespread clinical practice. On November 17, 2022, the U.S. Food and Drug Administration, Society of Nuclear Medicine and Molecular Imaging, and Medical Imaging and Technology Alliance cosponsored a public workshop comprising experts from academia, industry, and government agencies to discuss the role of quantitative brain amyloid PET imaging in staging, prognosis, and longitudinal assessment of Alzheimer disease. The workshop discussed a range of topics, including available radiopharmaceuticals for amyloid imaging; the methodology, metrics, and analytic validity of quantitative amyloid PET imaging; its use in disease staging, prognosis, and monitoring of progression; and challenges facing the field. This report provides a high-level summary of the presentations and the discussion.

Deep learned triple-tracer multiplexed PET myocardial image separation

Introduction

In multiplexed positron emission tomography (mPET) imaging, physiological and pathological information from different radiotracers can be observed simultaneously in a single dynamic PET scan. The separation of mPET signals within a single PET scan is challenging due to the fact that the PET scanner measures the sum of the PET signals of all the tracers. The conventional multi-tracer compartment modeling (MTCM) method requires staggered injections and assumes that the arterial input functions (AIFs) of each tracer are known.

Methods

In this work, we propose a deep learning-based method to separate triple-tracer PET images without explicitly knowing the AIFs. A dynamic triple-tracer noisy MLEM reconstruction was used as the network input, and dynamic single-tracer noisy MLEM reconstructions were used as training labels.

Results

A simulation study was performed to evaluate the performance of the proposed framework on triple-tracer ([ F 18 ]FDG+ Rb 82 +[ Tc 99m ]sestamibi) PET myocardial imaging. The results show that the proposed methodology substantially reduced the noise level compared to the results obtained from single-tracer imaging. Additionally, it achieved lower bias and standard deviation in the separated single-tracer images compared to the MTCM-based method at both the voxel and region of interest (ROI) levels.

Discussion

As compared to MTCM separation, the proposed method uses spatiotemporal information for separation, which improves the separation performance at both the voxel and ROI levels. The simulation study also demonstrates the feasibility and potential of the proposed DL-based method for the application to pre-clinical and clinical studies.

Advances and challenges in immunoPET methodology

Immuno-positron emission tomography (immunoPET) enables imaging of specific targets that play a role in targeted therapy and immunotherapy, such as antigens on cell membranes, targets in the disease microenvironment, or immune cells. The most common immunoPET applications use a monoclonal antibody labeled with a relatively long-lived positron emitter such as 89Zr (T 1/2 = 78.4 h), but smaller antibody-based constructs labeled with various other positron emitting radionuclides are also being investigated. This molecular imaging technique can thus guide the development of new drugs and may have a pivotal role in selecting patients for a particular therapy. In early phase immunoPET trials, multiple imaging time points are used to examine the time-dependent biodistribution and to determine the optimal imaging time point, which may be several days after tracer injection due to the slow kinetics of larger molecules. Once this has been established, usually only one static scan is performed and semi-quantitative values are reported. However, total PET uptake of a tracer is the sum of specific and nonspecific uptake. In addition, uptake may be affected by other factors such as perfusion, pre-/co-administration of the unlabeled molecule, and the treatment schedule. This article reviews imaging methodologies used in immunoPET studies and is divided into two parts. The first part summarizes the vast majority of clinical immunoPET studies applying semi-quantitative methodologies. The second part focuses on a handful of studies applying pharmacokinetic models and includes preclinical and simulation studies. Finally, the potential and challenges of immunoPET quantification methodologies are discussed within the context of the recent technological advancements provided by long axial field of view PET/CT scanners.

A short 18F-FDG imaging window triple injection neuroimaging protocol for parametric mapping in PET

BACKGROUND

In parametric PET, kinetic parameters are extracted from dynamic PET images. It is not commonly used in clinical practice because of long scan times and the requirement for an arterial input function (AIF). To address these limitations, we designed an 18F-fluorodeoxyglucose (18F-FDG) triple injection dynamic PET protocol for brain imaging with a standard field of view PET scanner using a 24-min imaging window and an input function modeled using measurements from a region of interest placed over the left ventricle.

METHODS

To test the protocol in 6 healthy participants, we examined the quality of voxel-based maps of kinetic parameters in the brain generated using the two-tissue compartment model and compared estimated parameter values with previously published values. We also utilized data from a 36-min validation imaging window to compare (1) the modeled AIF against the input function measured in the validation window; and (2) the net influx rate ([Formula: see text]) computed using parameter estimates from the short imaging window against the net influx rate obtained using Patlak analysis in the validation window.

RESULTS

Compared to the AIF measured in the validation window, the input function estimated from the short imaging window achieved a mean area under the curve error of 9%. The voxel-wise Pearson's correlation between [Formula: see text] estimates from the short imaging window and the validation imaging window exceeded 0.95.

CONCLUSION

The proposed 24-min triple injection protocol enables parametric 18F-FDG neuroimaging with noninvasive estimation of the AIF from cardiac images using a standard field of view PET scanner.

Super-resolution in brain positron emission tomography using a real-time motion capture system

Super-resolution (SR) is a methodology that seeks to improve image resolution by exploiting the increased spatial sampling information obtained from multiple acquisitions of the same target with accurately known sub-resolution shifts. This work aims to develop and evaluate an SR estimation framework for brain positron emission tomography (PET), taking advantage of a high-resolution infra-red tracking camera to measure shifts precisely and continuously. Moving phantoms and non-human primate (NHP) experiments were performed on a GE Discovery MI PET/CT scanner (GE Healthcare) using an NDI Polaris Vega (Northern Digital Inc), an external optical motion tracking device. To enable SR, a robust temporal and spatial calibration of the two devices was developed as well as a list-mode Ordered Subset Expectation Maximization PET reconstruction algorithm, incorporating the high-resolution tracking data from the Polaris Vega to correct motion for measured line of responses on an event-by-event basis. For both phantoms and NHP studies, the SR reconstruction method yielded PET images with visibly increased spatial resolution compared to standard static acquisitions, allowing improved visualization of small structures. Quantitative analysis in terms of SSIM, CNR and line profiles were conducted and validated our observations. The results demonstrate that SR can be achieved in brain PET by measuring target motion in real-time using a high-resolution infrared tracking camera.

Radiolabelling small and biomolecules for tracking and monitoring

Radiolabelling small molecules with beta-emitters has been intensively explored in the last decades and novel concepts for the introduction of radionuclides continue to be reported regularly. New catalysts that induce carbon/hydrogen activation are able to incorporate isotopes such as deuterium or tritium into small molecules. However, these established labelling approaches have limited applicability for nucleic acid-based drugs, therapeutic antibodies, or peptides, which are typical of the molecules now being investigated as novel therapeutic modalities. These target molecules are usually larger (significantly >1 kDa), mostly multiply charged, and often poorly soluble in organic solvents. However, in preclinical research they often require radiolabelling in order to track and monitor drug candidates in metabolism, biotransformation, or pharmacokinetic studies. Currently, the most established approach to introduce a tritium atom into an oligonucleotide is based on a multistep synthesis, which leads to a low specific activity with a high level of waste and high costs. The most common way of tritiating peptides is using appropriate precursors. The conjugation of a radiolabelled prosthetic compound to a functional group within a protein sequence is a commonly applied way to introduce a radionuclide or a fluorescent tag into large molecules. This review highlights the state-of-the-art in different radiolabelling approaches for oligonucleotides, peptides, and proteins, as well as a critical assessment of the impact of the label on the properties of the modified molecules. Furthermore, applications of radiolabelled antibodies in biodistribution studies of immune complexes and imaging of brain targets are reported.

Positronium Lifetime Image Reconstruction for TOF PET

Positron emission tomography is widely used in clinical and preclinical applications. Positronium lifetime carries information about the tissue microenvironment where positrons are emitted, but such information has not been captured because of two technical challenges. One challenge is the low sensitivity in detecting triple coincidence events. This problem has been mitigated by the recent developments of PET scanners with long (1-2 m) axial field of view. The other challenge is the low spatial resolution of the positronium lifetime images formed by existing methods that is determined by the time-of-flight (TOF) resolution (200-500 ps) of existing PET scanners. This paper solves the second challenge by developing a new image reconstruction method to generate high-resolution positronium lifetime images using existing TOF PET. Simulation studies demonstrate that the proposed method can reconstruct positronium lifetime images at much better spatial resolution than the limit set by the TOF resolution of the PET scanner. The proposed method opens up the possibility of performing positronium lifetime imaging using existing TOF PET scanners. The lifetime information can be used to understand the tissue microenvironment in vivo which could facilitate the study of disease mechanism and selection of proper treatments.

Pretargeted Imaging beyond the Blood-Brain Barrier-Utopia or Feasible?

Pretargeting is a promising nuclear imaging technique that allows for the usage of antibodies (Abs) with enhanced imaging contrast and reduced patient radiation burden. It is based on bioorthogonal chemistry with the tetrazine ligation-a reaction between trans-cyclooctenes (TCOs) and tetrazines (Tzs)-currently being the most popular reaction due to its high selectivity and reactivity. As Abs can be designed to bind specifically to currently 'undruggable' targets such as protein isoforms or oligomers, which play a crucial role in neurodegenerative diseases, pretargeted imaging beyond the BBB is highly sought after, but has not been achieved yet. A challenge in this respect is that large molecules such as Abs show poor brain uptake. Uptake can be increased by receptor mediated transcytosis; however, it is largely unknown if the achieved brain concentrations are sufficient for pretargeted imaging. In this study, we investigated whether the required concentrations are feasible to reach. As a model Ab, we used the bispecific anti-amyloid beta (Aβ) anti-transferrin receptor (TfR) Ab 3D6scFv8D3 and conjugated it to a different amount of TCOs per Ab and tested different concentrations in vitro. With this model in hand, we estimated the minimum required TCO concentration to achieve a suitable contrast between the high and low binding regions. The estimation was carried out using pretargeted autoradiography on brain sections of an Alzheimer's disease mouse model. Biodistribution studies in wild-type (WT) mice were used to correlate how different TCO/Ab ratios alter the brain uptake. Pretargeted autoradiography showed that increasing the number of TCOs as well as increasing the TCO-Ab concentration increased the imaging contrast. A minimum brain concentration of TCOs for pretargeting purposes was determined to be 10.7 pmol/g in vitro. Biodistribution studies in WT mice showed a brain uptake of 1.1% ID/g using TCO-3D6scFv8D3 with 6.8 TCO/Ab. According to our estimations using the optimal parameters, pretargeted imaging beyond the BBB is not a utopia. Necessary brain TCO concentrations can be reached and are in the same order of magnitude as required to achieve sufficient contrast. This work gives a first estimate that pretargeted imaging is indeed possible with antibodies. This could allow the imaging of currently 'undruggable' targets and therefore be crucial to monitor (e.g., therapies for intractable neurodegenerative diseases).

Neurospecific Molecules Measured in Periphery in Humans: How Do They Correlate with the Brain Levels? A Systematic Review

Human brain state is usually estimated by brain-specific substances in peripheral tissues, but, for most analytes, a concordance between their content in the brain and periphery is unclear. In this systematic review, we summarized the investigated correlations in humans. PubMed was searched up to June 2022. We included studies measuring the same endogenous neurospecific analytes in the central nervous system and periphery in the same subjects. Not eligible were studies of cerebrospinal fluid, with significant blood–brain barrier disruption, of molecules with well-established blood-periphery concordance or measured in brain tumors. Seventeen studies were eligible. Four studies did not report on correlation and four revealed no significant correlation. Four molecules were examined twice. For BDNF, there was no correlation in both studies. For phenylalanine, glutamine, and glutamate, results were contradictory. Strong correlations were found for free tryptophan (r = 0.97) and translocator protein (r = 0.90). Thus, only for three molecules was there some certainty. BDNF in plasma or serum does not reflect brain content, whereas free tryptophan (in plasma) and translocator protein (in blood cells) can serve as peripheral biomarkers. We expect a breakthrough in the field with advanced in vivo metabolomic analyses, neuroimaging techniques, and blood assays for exosomes of brain origin.

Historical efforts to develop 99mTc-based amyloid plaque targeting radiotracers

Imaging biomarkers have changed the way we study Alzheimer's disease and related dementias, develop new therapeutics to treat the disease, and stratify patient populations in clinical trials. With respect to protein aggregates comprised of amyloid-β plaques and tau neurofibrillary tangles, Positron Emission Tomography (PET) has become the gold standard imaging modality for quantitative visualization. Due to high infrastructural costs, the availability of PET remains limited to large urban areas within high income nations. This limits access to leading edge medical imaging, and potentially access to new treatments, by millions of rural and remote residents in those regions as well as billions of people in middle- and low-income countries. Single Photon Emission Computed Tomography (SPECT) is a more widely available imaging alternative with lower infrastructural costs and decades of familiarity amongst nuclear medicine professionals. Recent technological advances have closed the gap in spatial resolution and quantitation between SPECT and PET. If effective SPECT radiotracers were available to visualize amyloid-β plaques, geographic barriers to imaging could be circumvented. In this review, we will discuss past efforts to develop SPECT radiotracers targeting amyloid-β plaques which incorporate the most used radionuclide in nuclear medicine: technetium-99m (99mTc; t 1/2 = 6.01 h; γ = 140 keV). While reviewing the various chemical scaffolds and chelates employed, the focus will be upon the impact to the pharmacological properties of putative 99mTc-based amyloid-targeting radiotracers.

PET Imaging of Leg Arteries for Determining the Input Function in PET/MRI Brain Studies Using a Compact, MRI-Compatible PET System

In this study, we used a compact, high-resolution, and MRI-compatible PET camera (VersaPET) to assess the feasibility of measuring the image-derived input function (IDIF) from arteries in the leg with the ultimate goal of enabling fully quantitative PET brain imaging without blood sampling. We used this approach in five ¹⁸F-FDG PET/MRI brain studies in which the input function was also acquired using the gold standard of serial arterial blood sampling. After accounting for partial volume, dispersion, and calibration effects, we compared the metabolic rates of glucose (MRglu) quantified from VersaPET IDIFs in 80 brain regions to those using the gold standard and achieved a bias and variability of <5% which is within the range of reported test-retest values for this type of study. We also achieved a strong linear relationship (R² >0.97) against the gold standard across regions. The results of this preliminary study are promising and support further studies to optimize methods, validate in a larger cohort, and extend to the modeling of other radiotracers.

Evaluation of the spline reconstruction technique for preclinical PET imaging

BACKGROUND AND OBJECTIVE

The Spline Reconstruction Technique (SRT) is a fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The purpose of this study is to provide a comparison between SRT, Filtered Back-Projection (FBP), Ordered Subset Expectation Maximization 2D (2D-OSEM), and the Tera-Tomo 3D algorithm, using phantom data at various acquisition durations as well as small-animal data obtained from the Mediso nanoScan® PET/CT scanner.

METHODS

For this purpose, the "NEMA NU 4-2008 standards" protocol was employed at five different realizations and acquisition durations. In addition to the image quality metrics described by the NEMA protocol, Cold Region Contrast was also considered as a figure-of-merit. Furthermore, Cold Region Contrast was measured in the myocardial infarction region of six male Wistar rats. The volumetric defect quantification was assessed with dedicated computer software. Lastly, plots of Recovery Coefficient and Spill-Over Ratio as a function of the Percentage Standard Deviation were generated, after smoothing the phantom reconstructions with four different Gaussian filters. Statistical significance was determined by employing the Kruskal-Wallis test or One-way Analysis of Variance depending on the normality of the variable's distribution.

RESULTS

The present study revealed that, at the expense of slightly increased noise in the reconstructed images, SRT resulted in higher Recovery Coefficient values for small hot regions of interest, when compared with FBP and 2D-OSEM at all acquisition durations. Furthermore, SRT reconstructed images exhibit higher Recovery Coefficient values, for all hot regions of interest, when compared to the other 2D algorithms at short acquisition durations. In both phantom and animal studies, SRT achieved a significant improvement over 2D-OSEM for the Spill-Over Ratio and the Cold Region Contrast. These advantages were maintained even after comparing the algorithms at equal noise levels. The Tera-Tomo 3D algorithm (4 subsets, iterations≥ 13) performed significantly better compared to the other algorithms for all figures-of-merit. No statistically significant differences regarding the myocardial defect size were observed between the algorithms investigated.

CONCLUSIONS

Overall, SRT appears that could be useful for the quantification of small hot regions of interest, cold regions of interest, as well as in low-count imaging applications.

PET Imaging of Synaptic Density: Challenges and Opportunities of Synaptic Vesicle Glycoprotein 2A PET in Small Animal Imaging

The development of novel PET imaging agents for synaptic vesicle glycoprotein 2A (SV2A) allowed for the in vivo detection of synaptic density changes, which are correlated with the progression and severity of a variety of neuropsychiatric diseases. While multiple ongoing clinical investigations using SV2A PET are expanding its applications rapidly, preclinical SV2A PET imaging in animal models is an integral component of the translation research and provides supporting and complementary information. Herein, we overview preclinical SV2A PET studies in animal models of neurodegenerative disorders and discuss the opportunities and practical challenges in small animal SV2A PET imaging. At the Yale PET Center, we have conducted SV2A PET imaging studies in animal models of multiple diseases and longitudinal SV2A PET allowed us to evaluate synaptic density dynamics in the brains of disease animal models and to assess pharmacological effects of novel interventions. In this article, we discuss key considerations when designing preclinical SV2A PET imaging studies and strategies for data analysis. Specifically, we compare the brain imaging characteristics of available SV2A tracers, i.e., [11C]UCB-J, [18F]SynVesT-1, [18F]SynVesT-2, and [18F]SDM-16, in rodent brains. We also discuss the limited spatial resolution of PET scanners for small brains and challenges of kinetic modeling. We then compare different injection routes and estimate the maximum throughput (i.e., number of animals) per radiotracer synthesis by taking into account the injectable volume for each injection method, injected mass, and radioactivity half-lives. In summary, this article provides a perspective for designing and analyzing SV2A PET imaging studies in small animals.

Relationship Between Replay-Associated Ripples and Hippocampal N-Methyl-D-Aspartate Receptors: Preliminary Evidence From a PET-MEG Study in Schizophrenia

Background and Hypotheses

Hippocampal replay and associated high-frequency ripple oscillations are among the best-characterized phenomena in resting brain activity. Replay/ripples support memory consolidation and relational inference, and are regulated by N-methyl-D-aspartate receptors (NMDARs). Schizophrenia has been associated with both replay/ripple abnormalities and NMDAR hypofunction in both clinical samples and genetic mouse models, although the relationship between these 2 facets of hippocampal function has not been tested in humans.

Study Design

Here, we avail of a unique multimodal human neuroimaging data set to investigate the relationship between the availability of (intrachannel) NMDAR binding sites in hippocampus, and replay-associated ripple power, in 16 participants (7 nonclinical participants and 9 people with a diagnosis of schizophrenia, PScz). Each participant had both a [18F]GE-179 positron emission tomography (PET) scan (to measure NMDAR availability, V T ) and a magnetoencephalography (MEG) scan (to measure offline neural replay and associated high-frequency ripple oscillations, using Temporally Delayed Linear Modeling).

Study Results

We show a positive relationship between hippocampal NMDAR availability and replay-associated ripple power. This linkage was evident across control participants (r(5) = .94, P = .002) and PScz (r(7) = .70, P = .04), with no group difference.

Conclusions

Our findings provide preliminary evidence for a relationship between hippocampal NMDAR availability and replay-associated ripple power in humans, and haverelevance for NMDAR hypofunction theories of schizophrenia.

Preclinical Evaluation of [11C]YC-72-AB85 for In Vivo Visualization of Heat Shock Protein 90 in Brain and Cancer with Positron Emission Tomography

Aberrant Hsp90 has been implied in cancer and neurodegenerative disorders. The development of a suitable Hsp90 Positron emission tomography (PET) probe can provide in vivo quantification of the expression levels of Hsp90 as a biomarker for diagnosis and follow-up of cancer and central nervous system (CNS) disease progression. In this respect, [¹¹C]YC-72-AB85 was evaluated as an Hsp90 PET probe in B16.F10 melanoma bearing mice and its brain uptake was determined in rats and nonhuman primate. In vitro binding of [¹¹C]YC-72-AB85 to tissue slices of mouse B16.F10 melanoma, PC3 prostate carcinoma, and rodent brain was evaluated using autoradiography. Biodistribution of [¹¹C]YC-72-AB85 was evaluated in healthy and B16.F10 melanoma mice. In vivo brain uptake was assessed by μPET studies in rats and a rhesus monkey. In vitro binding was deemed Hsp90-specific by blocking studies with heterologous Hsp90 inhibitors onalespib and SNX-0723. Saturable Hsp90 binding was observed in brain, tumor, blood, and blood-rich organs in mice. In combined pretreatment and displacement studies, reversible and Hsp90-specific binding of [¹¹C]YC-72-AB85 was observed in rat brain. Dynamic μPET brain scans in baseline and blocking conditions in a rhesus monkey indicated Hsp90-specific binding. [¹¹C]YC-72-AB85 is a promising PET tracer for in vivo visualization of Hsp90 in tumor and brain. Clear differences of Hsp90 binding to blood and blood-rich organs were observed in tumor vs control mice. Further, we clearly demonstrate, for the first time, binding to a saturable Hsp90 pool in brain of rats and a rhesus monkey.

Improved low-dose positron emission tomography image reconstruction using deep learned prior

Positron emission tomography (PET) is a promising medical imaging technology that provides non-invasive and quantitative measurement of biochemical process in the human bodies. PET image reconstruction is challenging due to the ill-poseness of the inverse problem. With lower statistics caused by the limited detected photons, low-dose PET imaging leads to noisy reconstructed images with much quality degradation. Recently, deep neural networks (DNN) have been widely used in computer vision tasks and attracted growing interests in medical imaging. In this paper, we proposed a maximuma posteriori(MAP) reconstruction algorithm incorporating a convolutional neural network (CNN) representation in the formation of the prior. Rather than using the CNN in post-processing, we embedded the neural network in the reconstruction framework for image representation. Using the simulated data, we first quantitatively evaluated our proposed method in terms of the noise-bias tradeoff, and compared with the filtered maximum likelihood (ML), the conventional MAP, and the CNN post-processing methods. In addition to the simulation experiments, the proposed method was further quantitatively validated on the acquired patient brain and body data with the tradeoff between noise and contrast. The results demonstrated that the proposed CNN-MAP method improved noise-bias tradeoff compared with the filtered ML, the conventional MAP, and the CNN post-processing methods in the simulation study. For the patient study, the CNN-MAP method achieved better noise-contrast tradeoff over the other three methods. The quantitative enhancements indicate the potential value of the proposed CNN-MAP method in low-dose PET imaging.

PET-ABC: fully Bayesian likelihood-free inference for kinetic models

Aims.We describe an intuitive, easy to use method called PET-ABC that enables full Bayesian statistical inference from single subject dynamic PET data. The performance of PET-ABC was compared with weighted non-linear least squares (WNLS) in terms of reliability of kinetic parameter estimation and statistical power for model selection.Methods.Dynamic PET data based on 1-tissue and 2-tissue compartmental models were simulated with 2 noise models and 3 noise levels. PET-ABC was used to evaluate the reliability of parameter estimates under each condition. It was also used to perform model selection for a simulated noisy dataset composed of a mixture of 1- and 2-tissue compartment kinetics. Finally, PET-ABC was used to analyze a non-steady state dynamic [¹¹C] raclopride study performed on a fully conscious rat administered either 2 mg.kg^-1amphetamine or saline 20 min after tracer injection.Results.PET-ABC yielded posterior point estimates for model parameters with smaller variance than WNLS, as well as probability density functions indicating confidence intervals for those estimates. It successfully identified the superiority of a 2-tissue compartment model to fit the simulated mixed model data. For the drug challenge study, the post observation probability of striatal displacement of the PET signal was 0.9 for amphetamine and approximately 0 for saline, indicating a high probability of amphetamine-induced endogenous dopamine release in the striatum. PET-ABC also demonstrated superior statistical power to WNLS (0.87 versus 0.09) for selecting the correct model in a simulated ligand displacement study.Conclusions.PET-ABC is a simple and intuitive method that provides complete Bayesian statistical analysis of single subject dynamic PET data, including the extent to which model parameter estimates and model choice are supported by the data. Software for PET-ABC is freely available as part of thePETabcpackagehttps://github.com/cgrazian/PETabc.

The Use, Standardization, and Interpretation of Brain Imaging Data in Clinical Trials of Neurodegenerative Disorders

Imaging biomarkers play a wide-ranging role in clinical trials for neurological disorders. This includes selecting the appropriate trial participants, establishing target engagement and mechanism-related pharmacodynamic effect, monitoring safety, and providing evidence of disease modification. In the early stages of clinical drug development, evidence of target engagement and/or downstream pharmacodynamic effect-especially with a clear relationship to dose-can provide confidence that the therapeutic candidate should be advanced to larger and more expensive trials, and can inform the selection of the dose(s) to be further tested, i.e., to "de-risk" the drug development program. In these later-phase trials, evidence that the therapeutic candidate is altering disease-related biomarkers can provide important evidence that the clinical benefit of the compound (if observed) is grounded in meaningful biological changes. The interpretation of disease-related imaging markers, and comparability across different trials and imaging tools, is greatly improved when standardized outcome measures are defined. This standardization should not impinge on scientific advances in the imaging tools per se but provides a common language in which the results generated by these tools are expressed. PET markers of pathological protein aggregates and structural imaging of brain atrophy are common disease-related elements across many neurological disorders. However, PET tracers for pathologies beyond amyloid β and tau are needed, and the interpretability of structural imaging can be enhanced by some simple considerations to guard against the possible confound of pseudo-atrophy. Learnings from much-studied conditions such as Alzheimer's disease and multiple sclerosis will be beneficial as the field embraces rarer diseases.

Quantitative PET in the 2020s: a roadmap

Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative 'hot spot' imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice.

Parameter-Transferred Wasserstein Generative Adversarial Network (PT-WGAN) for Low-Dose PET Image Denoising

Due to the widespread use of positron emission tomography (PET) in clinical practice, the potential risk of PET-associated radiation dose to patients needs to be minimized. However, with the reduction in the radiation dose, the resultant images may suffer from noise and artifacts that compromise diagnostic performance. In this paper, we propose a parameter-transferred Wasserstein generative adversarial network (PT-WGAN) for low-dose PET image denoising. The contributions of this paper are twofold: i) a PT-WGAN framework is designed to denoise low-dose PET images without compromising structural details, and ii) a task-specific initialization based on transfer learning is developed to train PT-WGAN using trainable parameters transferred from a pretrained model, which significantly improves the training efficiency of PT-WGAN. The experimental results on clinical data show that the proposed network can suppress image noise more effectively while preserving better image fidelity than recently published state-of-the-art methods. We make our code available at https://github.com/90n9-yu/PT-WGAN.

LCPR-Net: low-count PET image reconstruction using the domain transform and cycle-consistent generative adversarial networks

BACKGROUND

Reducing the radiation tracer dose and scanning time during positron emission tomography (PET) imaging can reduce the cost of the tracer, reduce motion artifacts, and increase the efficiency of the scanner. However, the reconstructed images to be noisy. It is very important to reconstruct high-quality images with low-count (LC) data. Therefore, we propose a deep learning method called LCPR-Net, which is used for directly reconstructing full-count (FC) PET images from corresponding LC sinogram data.

METHODS

Based on the framework of a generative adversarial network (GAN), we enforce a cyclic consistency constraint on the least-squares loss to establish a nonlinear end-to-end mapping process from LC sinograms to FC images. In this process, we merge a convolutional neural network (CNN) and a residual network for feature extraction and image reconstruction. In addition, the domain transform (DT) operation sends a priori information to the cycle-consistent GAN (CycleGAN) network, avoiding the need for a large amount of computational resources to learn this transformation.

RESULTS

The main advantages of this method are as follows. First, the network can use LC sinogram data as input to directly reconstruct an FC PET image. The reconstruction speed is faster than that provided by model-based iterative reconstruction. Second, reconstruction based on the CycleGAN framework improves the quality of the reconstructed image.

CONCLUSIONS

Compared with other state-of-the-art methods, the quantitative and qualitative evaluation results show that the proposed method is accurate and effective for FC PET image reconstruction.

Bias evaluation and reduction in 3D OP-OSEM reconstruction in dynamic equilibrium PET studies with 11C-labeled for binding potential analysis

Iterative image reconstruction is widely used in positron emission tomography. However, it is known to contribute to quantitation bias and is particularly pronounced during dynamic studies with ¹¹C-labeled radiotracers where count rates become low towards the end of the acquisition. As the strength of the quantitation bias depends on the counts in the reconstructed frame, it can differ from frame to frame of the acquisition. This is especially relevant in the case of neuro-receptor studies with simultaneous PET/MR when a bolus-infusion protocol is applied to allow the comparison of pre- and post-task effects. Here, count dependent changes in quantitation bias may interfere with task changes. We evaluated the impact of different framing schemes on quantitation bias and its propagation into binding potential (BP) using a phantom decay study with ¹¹C and 3D OP-OSEM. Further, we propose a framing scheme that keeps the true counts per frame constant over the acquisition time as constant framing schemes and conventional increasing framing schemes are unlikely to achieve stable bias values during the acquisition time range. For a constant framing scheme with 5 minutes frames, the BP bias was 7.13±2.01% (10.8% to 3.8%) compared to 5.63±2.85% (7.8% to 4.0%) for conventional increasing framing schemes. Using the proposed constant true counts framing scheme, a stabilization of the BP bias was achieved at 2.56±3.92% (3.5% to 1.7%). The change in BP bias was further studied by evaluating the linear slope during the acquisition time interval. The lowest slope values were observed in the constant true counts framing scheme. The constant true counts framing scheme was effective for BP bias stabilization at relevant activity and time ranges. The mean BP bias under these conditions was 2.56±3.92%, which represents the lower limit for the detection of changes in BP during equilibrium and is especially important in the case of cognitive tasks where the expected changes are low.

Test-retest repeatability of [18F]Flortaucipir PET in Alzheimer's disease and cognitively normal individuals

The aim of this study was to investigate the test-retest (TRT) repeatability of various parametric quantification methods for [18F]Flortaucipir positron emission tomography (PET). We included eight subjects with dementia or mild cognitive impairment due to Alzheimer's disease and six cognitively normal subjects. All underwent two 130-min dynamic [18F]Flortaucipir PET scans within 3 ± 1 weeks. Data were analyzed using reference region models receptor parametric mapping (RPM), simplified reference tissue method 2 (SRTM2) and reference logan (RLogan), as well as standardized uptake value ratios (SUVr, time intervals 40-60, 80-100 and 110-130 min post-injection) with cerebellar gray matter as reference region. We obtained distribution volume ratio or SUVr, first for all brain regions and then in three tau-specific regions-of-interest (ROIs). TRT repeatability (%) was defined as |retest-test|/(average (test + retest)) × 100. For all methods and across ROIs, TRT repeatability ranged from (median (IQR)) 0.84% (0.68-2.15) to 6.84% (2.99-11.50). TRT repeatability was good for all reference methods used, although semi-quantitative models (i.e. SUVr) performed marginally worse than quantitative models, for instance TRT repeatability of RPM: 1.98% (0.78-3.58) vs. SUVr80-100: 3.05% (1.28-5.52), p < 0.001. Furthermore, for SUVr80-100 and SUVr110-130, with higher average SUVr, more variation was observed. In conclusion, while TRT repeatability was good for all models used, quantitative methods performed slightly better than semi-quantitative methods.

PET Parametric Imaging: Past, Present, and Future

Positron emission tomography (PET) is actively used in a diverse range of applications in oncology, cardiology, and neurology. The use of PET in the clinical setting focuses on static (single time frame) imaging at a specific time-point post radiotracer injection and is typically considered as semi-quantitative; e.g. standardized uptake value (SUV) measures. In contrast, dynamic PET imaging requires increased acquisition times but has the advantage that it measures the full spatiotemporal distribution of a radiotracer and, in combination with tracer kinetic modeling, enables the generation of multiparametric images that more directly quantify underlying biological parameters of interest, such as blood flow, glucose metabolism, and receptor binding. Parametric images have the potential for improved detection and for more accurate and earlier therapeutic response assessment. Parametric imaging with dynamic PET has witnessed extensive research in the past four decades. In this paper, we provide an overview of past and present activities and discuss emerging opportunities in the field of parametric imaging for the future.

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.

Human Positron Emission Tomography Neuroimaging

Neuroimaging with positron emission tomography (PET) is the most powerful tool for understanding pharmacology, neurochemistry, and pathology in the living human brain. This technology combines high-resolution scanners to measure radioactivity throughout the human body with specific, targeted radioactive molecules, which allow measurements of a myriad of biological processes in vivo. While PET brain imaging has been active for almost 40 years, the pace of development for neuroimaging tools, known as radiotracers, and for quantitative analytical techniques has increased dramatically over the past decade. Accordingly, the fundamental questions that can be addressed with PET have expanded in basic neurobiology, psychiatry, neurology, and related therapeutic development. In this review, we introduce the field of human PET neuroimaging, some of its conceptual underpinnings, and motivating questions. We highlight some of the more recent advances in radiotracer development, quantitative modeling, and applications of PET to the study of the human brain.

Positron emission tomography imaging of novel AAV capsids maps rapid brain accumulation

Adeno-associated viruses (AAVs) are typically single-stranded deoxyribonucleic acid (ssDNA) encapsulated within 25-nm protein capsids. Recently, tissue-specific AAV capsids (e.g. PHP.eB) have been shown to enhance brain delivery in rodents via the LY6A receptor on brain endothelial cells. Here, we create a non-invasive positron emission tomography (PET) methodology to track viruses. To provide the sensitivity required to track AAVs injected at picomolar levels, a unique multichelator construct labeled with a positron emitter (Cu-64, t_1/2 = 12.7 h) is coupled to the viral capsid. We find that brain accumulation of the PHP.eB capsid 1) exceeds that reported in any previous PET study of brain uptake of targeted therapies and 2) is correlated with optical reporter gene transduction of the brain. The PHP.eB capsid brain endothelial receptor affinity is nearly 20-fold greater than that of AAV9. The results suggest that novel PET imaging techniques can be applied to inform and optimize capsid design.

Adeno-associated viruses (AAVs) can be targeted in a tissue-specific manner, but their tissue accumulation cannot be assessed in a non-invasive manner. Here the authors conjugate a multivalent chelator labelled with Cu-64 to the surface of AAVs and image the brain accumulation of the PHB.eB capsid by PET.

PET image reconstruction using physical and mathematical modelling for time of flight PET-MR scanners in the STIR library

This work demonstrates how computational and physical modelling of the positron emission tomography (PET) image acquisition process for a state-of-the-art integrated PET and magnetic resonance imaging (PET-MR) system can produce images comparable to the manufacturer. The GE SIGNA PET/MR scanner is manufactured by General Electric and has time-of-flight (TOF) capabilities of about 390 ps. All software development took place in the Software for Tomographic Image Reconstruction (STIR: http://stir.sf.net) library, which is a widely used open source software to reconstruct data as exported from emission tomography scanners. The new software developments will be integrated into STIR, providing the opportunity for researchers worldwide to establish and expand their image reconstruction methods. Furthermore, this work is of particular significance as it provides the first validation of TOF PET image reconstruction for real scanner datasets using the STIR library. This paper presents the methodology, analysis, and critical issues encountered in implementing an independent reconstruction software package. Acquired PET data were processed via several appropriate algorithms which are necessary to produce an accurate and precise quantitative image. This included mathematical, physical and anatomical modelling of the patient and simulation of various aspects of the acquisition. These included modelling of random coincidences using 'singles' rates per crystals, detector efficiencies and geometric effects. Attenuation effects were calculated by using the STIR's attenuation correction model. Modelling all these effects within the system matrix allowed the reconstruction of PET images which demonstrates the metabolic uptake of the administered radiopharmaceutical. These implementations were validated using measured phantom and clinical datasets. The developments are tested using the ordered subset expectation maximisation (OSEM) and the more recently proposed kernelised expectation maximisation (KEM) algorithm which incorporates anatomical information from MR images into PET reconstruction.

A Gas Phase Route to [18F]fluoroform with Limited Molar Activity Dilution

Positron emission tomography (PET) is an important imaging modality for biomedical research and drug development. PET requires biochemically selective radiotracers to realize full potential. Fluorine-18 (t1/2 = 109.8 min) is a major radionuclide for labeling such radiotracers but is only readily available in high activities from cyclotrons as [18F]fluoride ion. [18F]fluoroform has emerged for labeling tracers in trifluoromethyl groups. Prior methods of [18F]fluoroform synthesis used difluoro precursors in solution and led to high dilution with carrier and low molar activity (Am). We explored a new approach for the synthesis of [18F]fluoroform based on the radiosynthesis of [18F]fluoromethane from [18F]fluoride ion and then cobaltIII fluoride mediated gas phase fluorination. We estimate that carrier dilution in this process is limited to about 3-fold and find that moderate to high Am values can be achieved. We show that [18F]fluoroform so produced is highly versatile for rapidly and efficiently labeling various chemotypes that carry trifluoromethyl groups, thereby expanding prospects for developing new PET radiotracers.

PET imaging of tau protein targets: a methodology perspective

The two neuropathological hallmarks of Alzheimer's disease (AD) are amyloid-[Formula: see text] plaques and neurofibrillary tangles of tau protein. Fifteen years ago, Positron Emission Tomography (PET) with Pittsburgh Compound B (11C-PiB) enabled selective in-vivo visualization of amyloid-[Formula: see text] plaque deposits and has since provided valuable information about the role of amyloid-[Formula: see text] deposition in AD. The progression of tau deposition has been shown to be highly associated with neuronal loss, neurodegeneration, and cognitive decline. Until recently it was not possible to visualize tau deposition in-vivo, but several tau PET tracers are now available in different stages of clinical development. To date, no tau tracer has been approved by the Food and Drug Administration for use in the evaluation of AD or other tauopathies, despite very active research efforts. In this paper we review the recent developments in tau PET imaging with a focus on in-vivo findings in AD and discuss the challenges associated with tau tracer development, the status of development and validation of different tau tracers, and the clinical information these provide.

What proportion of striatal D2 receptors are occupied by endogenous dopamine at baseline? A meta-analysis with implications for understanding antipsychotic occupancy

Using molecular imaging techniques - positron emission tomography (PET) and single-photon emission computed tomography (SPECT) - in conjunction with an acute dopamine depletion challenge (alpha-methyl-para-tyrosine) it is possible to estimate endogenous dopamine levels occupying striatal dopamine D₂ receptors (D₂R) in humans in vivo. However, it is unclear what proportion of striatal D₂R are occupied by endogenous dopamine under normal conditions. This is important since it has been suggested that in schizophrenia there may be a substantial proportion of striatal D₂R which are occupied by endogenous dopamine and not accessible by therapeutic doses of antipsychotics. In order to clarify these issues, we conducted a meta-analysis of dopamine depletion studies using substituted benzamide radiotracers in healthy persons. This meta-analysis suggests that anywhere from 8 to 21% (weighted average 11%) of striatal D₂R may be occupied by endogenous dopamine at baseline. Using these estimates, we propose an updated occupancy model and tentatively suggest that antipsychotics inhibit a smaller proportion of the total pool of striatal D₂R in vivo than previously acknowledged. This article is part of the issue entitled 'Special Issue on Antipsychotics'.

Iterative PET Image Reconstruction Using Convolutional Neural Network Representation

PET image reconstruction is challenging due to the ill-poseness of the inverse problem and limited number of detected photons. Recently, the deep neural networks have been widely and successfully used in computer vision tasks and attracted growing interests in medical imaging. In this paper, we trained a deep residual convolutional neural network to improve PET image quality by using the existing inter-patient information. An innovative feature of the proposed method is that we embed the neural network in the iterative reconstruction framework for image representation, rather than using it as a post-processing tool. We formulate the objective function as a constrained optimization problem and solve it using the alternating direction method of multipliers algorithm. Both simulation data and hybrid real data are used to evaluate the proposed method. Quantification results show that our proposed iterative neural network method can outperform the neural network denoising and conventional penalized maximum likelihood methods.

Improved Simultaneous Algebraic Reconstruction Technique Algorithm for Positron-Emission Tomography Image Reconstruction via Minimizing the Fast Total Variation

CONTEXT

There has been considerable progress in the instrumentation for data measurement and computer methods for generating images of measured PET data. These computer methods have been developed to solve the inverse problem, also known as the "image reconstruction from projections" problem.

AIM

In this paper, we propose a modified Simultaneous Algebraic Reconstruction Technique (SART) algorithm to improve the quality of image reconstruction by incorporating total variation (TV) minimization into the iterative SART algorithm.

METHODOLOGY

The SART updates the estimated image by forward projecting the initial image onto the sinogram space. Then, the difference between the estimated sinogram and the given sinogram is back-projected onto the image domain. This difference is then subtracted from the initial image to obtain a corrected image. Fast total variation (FTV) minimization is applied to the image obtained in the SART step. The second step is the result obtained from the previous FTV update. The SART and the FTV minimization steps run iteratively in an alternating manner. Fifty iterations were applied to the SART algorithm used in each of the regularization-based methods. In addition to the conventional SART algorithm, spatial smoothing was used to enhance the quality of the image. All images were sized at 128 × 128 pixels.

RESULTS

The proposed algorithm successfully accomplished edge preservation. A detailed scrutiny revealed that the reconstruction algorithms differed; for example, the SART and the proposed FTV-SART algorithm effectively preserved the hot lesion edges, whereas artifacts and deviations were more likely to occur in the ART algorithm than in the other algorithms.

CONCLUSIONS

Compared to the standard SART, the proposed algorithm is more robust in removing background noise while preserving edges to suppress the existent image artifacts. The quality measurements and visual inspections show a significant improvement in image quality compared to the conventional SART and Algebraic Reconstruction Technique (ART) algorithms.

Tactics for preclinical validation of receptor-binding radiotracers

INTRODUCTION

Aspects of radiopharmaceutical development are illustrated through preclinical studies of [125I]-(E)-1-(2-(2,3-dihydrobenzofuran-5-yl)ethyl)-4-(iodoallyl)piperazine ([125I]-E-IA-BF-PE-PIPZE), a radioligand for sigma-1 (σ1) receptors, coupled with examples from the recent literature. Findings are compared to those previously observed for [125I]-(E)-1-(2-(2,3-dimethoxy-5-yl)ethyl)-4-(iodoallyl)piperazine ([125I]-E-IA-DM-PE-PIPZE).

METHODS

Syntheses of E-IA-BF-PE-PIPZE and [125I]-E-IA-BF-PE-PIPZE were accomplished by standard methods. In vitro receptor binding studies and autoradiography were performed, and binding potential was predicted. Measurements of lipophilicity and protein binding were obtained. In vivo studies were conducted in mice to evaluate radioligand stability, as well as specific binding to σ1 sites in brain, brain regions and peripheral organs in the presence and absence of potential blockers.

RESULTS

E-IA-BF-PE-PIPZE exhibited high affinity and selectivity for σ1 receptors (Ki = 0.43 ± 0.03 nM, σ2/σ1 = 173). [125I]-E-IA-BF-PE-PIPZE was prepared in good yield and purity, with high specific activity. Radioligand binding provided dissociation (koff) and association (kon) rate constants, along with a measured Kd of 0.24 ± 0.01 nM and Bmax of 472 ± 13 fmol/mg protein. The radioligand proved suitable for quantitative autoradiography in vitro using brain sections. Moderate lipophilicity, Log D7.4 2.69 ± 0.28, was determined, and protein binding was 71 ± 0.3%. In vivo, high initial whole brain uptake, >6% injected dose/g, cleared slowly over 24 h. Specific binding represented 75% to 93% of total binding from 15 min to 24 h. Findings were confirmed and extended by regional brain biodistribution. Radiometabolites were not observed in brain (1%).

CONCLUSIONS

Substitution of dihydrobenzofuranylethyl for dimethoxyphenethyl increased radioligand affinity for σ1 receptors by 16-fold. While high specific binding to σ1 receptors was observed for both radioligands in vivo, [125I]-E-IA-BF-PE-PIPZE displayed much slower clearance kinetics than [125I]-E-IA-DM-PE-PIPZE. Thus, minor structural modifications of σ1 receptor radioligands lead to major differences in binding properties in vitro and in vivo.

Microglia and Brain Plasticity in Acute Psychosis and Schizophrenia Illness Course: A Meta-Review

OBJECTIVE

Schizophrenia poses a tremendous health, social, and economic burden upon patients and society, indicating current treatment options remain inadequate. Recent findings from several lines of evidence have pointed to the importance of immune system involvement in not only premorbid neurodevelopmental but also subsequent symptom generation and aging processes of brain change in schizophrenia. In this meta-review, we use the summarized evidence from recent quantitative systematic reviews (SRs) and meta-analyses of several subspecialties to critically evaluate the hypothesis that immune-related processes shape the symptomatic presentation and illness course of schizophrenia, both directly and indirectly through altered neuroplasticity.

METHODS

We performed a data search in PubMed for English language SRs and meta-analyses from 2010 to 2017. The methodological quality of the SRs was assessed with the AMSTAR instrument. In addition, we review in this paper 11 original publications on translocator protein (TSPO) positron emission tomography (PET) imaging in schizophrenia.

RESULTS

We reviewed 26 SRs and meta-analyses. Evidence from clinical observational studies of inflammatory or immunological markers and randomized controlled drug trials of immunomodulatory compounds as add-on in the treatment of schizophrenia suggests psychotic exacerbations are accompanied by immunological changes different from those seen in non-acute states, and that the symptoms of schizophrenia can be modified by compounds such as non-steroidal anti-inflammatory drug and minocycline. Information derived from post-mortem brain tissue analysis and PET neuroimaging studies to evaluate microglial activation have added new perspectives to the available evidence, yet these results are very heterogeneous. Each research domain comes with unique opportunities as well as inherent limitations. A better understanding of the (patho-)physiology of microglial cells and their role in neuroplasticity is key to interpreting the immune-related findings in the context of schizophrenia illness exacerbations and progression.

CONCLUSION

Evidence from clinical studies analyzing patients' blood and cerebrospinal fluid samples, neuroimaging and post-mortem brain tissue suggests that aberrant immune responses may define schizophrenia illness' course through altered neuroplasticity representing abnormal aging processes. Most findings are however prone to bias and confounding, and often non-specific to schizophrenia, and a multidisciplinary translational approach is needed to consolidate these findings and link them to other schizophrenia hypotheses.

Generalized paired-agent kinetic model for in vivo quantification of cancer cell-surface receptors under receptor saturation conditions

New precision medicine drugs oftentimes act through binding to specific cell-surface cancer receptors, and thus their efficacy is highly dependent on the availability of those receptors and the receptor concentration per cell. Paired-agent molecular imaging can provide quantitative information on receptor status in vivo, especially in tumor tissue; however, to date, published approaches to paired-agent quantitative imaging require that only 'trace' levels of imaging agent exist compared to receptor concentration. This strict requirement may limit applicability, particularly in drug binding studies, which seek to report on a biological effect in response to saturating receptors with a drug moiety. To extend the regime over which paired-agent imaging may be used, this work presents a generalized simplified reference tissue model (GSRTM) for paired-agent imaging developed to approximate receptor concentration in both non-receptor-saturated and receptor-saturated conditions. Extensive simulation studies show that tumor receptor concentration estimates recovered using the GSRTM are more accurate in receptor-saturation conditions than the standard simple reference tissue model (SRTM) (% error (mean  ±  sd): GSRTM 0  ±  1 and SRTM 50  ±  1) and match the SRTM accuracy in non-saturated conditions (% error (mean  ±  sd): GSRTM 5  ±  5 and SRTM 0  ±  5). To further test the approach, GSRTM-estimated receptor concentration was compared to SRTM-estimated values extracted from tumor xenograft in vivo mouse model data. The GSRTM estimates were observed to deviate from the SRTM in tumors with low receptor saturation (which are likely in a saturated regime). Finally, a general 'rule-of-thumb' algorithm is presented to estimate the expected level of receptor saturation that would be achieved in a given tissue provided dose and pharmacokinetic information about the drug or imaging agent being used, and physiological information about the tissue. These studies suggest that the GSRTM is necessary when receptor saturation exceeds 20% and highlight the potential for GSRTM to accurately measure receptor concentrations under saturation conditions, such as might be required during high dose drug studies, or for imaging applications where high concentrations of imaging agent are required to optimize signal-to-noise conditions. This model can also be applied to PET and SPECT imaging studies that tend to suffer from noisier data, but require one less parameter to fit if images are converted to imaging agent concentration (quantitative PET/SPECT).

Imaging in Central Nervous System Drug Discovery

The discovery and development of central nervous system (CNS) drugs is an extremely challenging process requiring large resources, timelines, and associated costs. The high risk of failure leads to high levels of risk. Over the past couple of decades PET imaging has become a central component of the CNS drug-development process, enabling decision-making in phase I studies, where early discharge of risk provides increased confidence to progress a candidate to more costly later phase testing at the right dose level or alternatively to kill a compound through failure to meet key criteria. The so called "3 pillars" of drug survival, namely; tissue exposure, target engagement, and pharmacologic activity, are particularly well suited for evaluation by PET imaging. This review introduces the process of CNS drug development before considering how PET imaging of the "3 pillars" has advanced to provide valuable tools for decision-making on the critical path of CNS drug development. Finally, we review the advances in PET science of biomarker development and analysis that enable sophisticated drug-development studies in man.

Recent Developments in Molecular Brain Imaging of Neuropsychiatric Disorders

Molecular imaging with PET or SPECT has been an important research tool in psychiatry for as long as these modalities have been available. Here, we discuss two areas of neuroimaging relevant to current psychiatry research. The first is the use of imaging to study neurotransmission. We discuss the use of pharmacologic probes to induce changes in levels of neurotransmitters that can be inferred through their effects on outcome measures of imaging experiments, from their historical origins focusing on dopamine transmission through recent developments involving serotonin, GABA, and glutamate. Next, we examine imaging of neuroinflammation in the context of psychiatry. Imaging markers of neuroinflammation have been studied extensively in other areas of brain research, but they have more recently attracted interest in psychiatry research, based on accumulating evidence that there may be an inflammatory component to some psychiatric conditions. Furthermore, new probes are under development that would allow unprecedented insights into cellular processes. In summary, molecular imaging would continue to offer great potential as a unique tool to further our understanding of brain function in health and disease.

Estimating the effect of endogenous dopamine on baseline [(11) C]-(+)-PHNO binding in the human brain

Endogenous dopamine (DA) levels at dopamine D2/3 receptors (D2/3 R) have been quantified in the living human brain using the agonist radiotracer [(11) C]-(+)-PHNO. As an agonist radiotracer, [(11) C]-(+)-PHNO is more sensitive to endogenous DA levels than antagonist radiotracers. We sought to determine the proportion of the variance in baseline [(11) C]-(+)-PHNO binding to D2/3 Rs which can be accounted for by variation in endogenous DA levels. This was done by computing the Pearson's coefficient for the correlation between baseline binding potential (BPND ) and the change in BPND after acute DA depletion, using previously published data. All correlations were inverse, and the proportion of the variance in baseline [(11) C]-(+)-PHNO BPND that can be accounted for by variation in endogenous DA levels across the striatal subregions ranged from 42-59%. These results indicate that lower baseline values of [(11) C]-(+)-PHNO BPND reflect greater stimulation by endogenous DA. To further validate this interpretation, we sought to examine whether these data could be used to estimate the dissociation constant (Kd) of DA at D2/3 R. In line with previous in vitro work, we estimated the in vivo Kd of DA to be around 20 nM. In summary, the agonist radiotracer [(11) C]-(+)-PHNO can detect the impact of endogenous DA levels at D2/3 R in the living human brain from a single baseline scan, and may be more sensitive to this impact than other commonly employed radiotracers.

Designing a compact high performance brain PET scanner-simulation study

The desire to understand normal and disordered human brain function of upright, moving persons in natural environments motivates the development of the ambulatory micro-dose brain PET imager (AMPET). An ideal system would be light weight but with high sensitivity and spatial resolution, although these requirements are often in conflict with each other. One potential approach to meet the design goals is a compact brain-only imaging device with a head-sized aperture. However, a compact geometry increases parallax error in peripheral lines of response, which increases bias and variance in region of interest (ROI) quantification. Therefore, we performed simulation studies to search for the optimal system configuration and to evaluate the potential improvement in quantification performance over existing scanners. We used the Cramér-Rao variance bound to compare the performance for ROI quantification using different scanner geometries. The results show that while a smaller ring diameter can increase photon detection sensitivity and hence reduce the variance at the center of the field of view, it can also result in higher variance in peripheral regions when the length of detector crystal is 15 mm or more. This variance can be substantially reduced by adding depth-of-interaction (DOI) measurement capability to the detector modules. Our simulation study also shows that the relative performance depends on the size of the ROI, and a large ROI favors a compact geometry even without DOI information. Based on these results, we propose a compact 'helmet' design using detectors with DOI capability. Monte Carlo simulations show the helmet design can achieve four-fold higher sensitivity and resolve smaller features than existing cylindrical brain PET scanners. The simulations also suggest that improving TOF timing resolution from 400 ps to 200 ps also results in noticeable improvement in image quality, indicating better timing resolution is desirable for brain imaging.