Open-field PET: Simultaneous brain functional imaging and behavioural response measurements in freely moving small animals

Modeling PET Data Acquired During Nonsteady Conditions: What If Brain Conditions Change During the Scan?

Researchers use dynamic PET imaging with target-selective tracer molecules to probe molecular processes. Kinetic models have been developed to describe these processes. The models are typically fitted to the measured PET data with the assumption that the brain is in a steady-state condition for the duration of the scan. The end results are quantitative parameters that characterize the molecular processes. The most common kinetic modeling endpoints are estimates of volume of distribution or the binding potential of a tracer. If the steady state is violated during the scanning period, the standard kinetic models may not apply. To address this issue, time-variant kinetic models have been developed for the characterization of dynamic PET data acquired while significant changes (e.g., short-lived neurotransmitter changes) are occurring in brain processes. These models are intended to extract a transient signal from data. This work in the PET field dates back at least to the 1990s. As interest has grown in imaging nonsteady events, development and refinement of time-variant models has accelerated. These new models, which we classify as belonging to the first, second, or third generation according to their innovation, have used the latest progress in mathematics, image processing, artificial intelligence, and statistics to improve the sensitivity and performance of the earliest practical time-variant models to detect and describe nonsteady phenomena. This review provides a detailed overview of the history of time-variant models in PET. It puts key advancements in the field into historical and scientific context. The sum total of the methods is an ongoing attempt to better understand the nature and implications of neurotransmitter fluctuations and other brief neurochemical phenomena.

Impact of shortening time on diagnosis of 18F-florbetaben PET

BACKGROUND

18F-Florbetaben amyloid positron emission tomography (PET) scan is crucial for diagnosing Alzheimer's disease, typically involving a 20 min acquisition. However, maintaining such prolonged scans can be challenging in some cases. This study explores the diagnostic impact and feasibility of reducing scan durations by comparing quantitative measures between shortened and standard scans. Additionally, we identified the optimal Centiloid threshold to distinguish between positive and negative amyloid results.

RESULTS

We analyzed 307 PET scans from our memory clinic, each followed up for a minimum of two years. The scans, conducted 90 to 110 min after approximately 300 MBq of 18F-Florbetaben injection, were categorized into four sets of 5 min durations: 5, 10, 15, and 20 min. Nuclear medicine physicians validated and rated each scan as either amyloid-positive or negative. For quantitative assessments, we employed the standardized uptake value ratio (SUVR) and Centiloid scales, comparing total SUVR and Centiloid values across five subregions (global, frontal, posterior cingulate-precuneus, lateral temporal, and parietal) using Bland-Altman analysis. Receiver operator characteristic (ROC) curves were utilized to develop optimal Centiloid thresholds. Comparing the images at 5, 10, 15, and 20 min images, SUVR and Centiloid values gradually increased with prolonged scan times. The mean SUVR difference between 5 and 20 min was 0.03 for the amyloid-positive and 0.01 for the amyloid-negative groups; Centiloid differences were 4.60 and 2.38, respectively. Additionally, no significant variation was observed in total SUVR and Centiloid values among the durations across all subregions in positive and negative groups (all p > 0.1). ROC analysis indicated that a Centiloid threshold of 21.86 at 5 min provided optimal agreement with visual assessments (AUC = 0.985, sensitivity = 0.950, specificity = 0.972), especially using the global area.

CONCLUSIONS

This study demonstrated that 5 min image scans with an optimal threshold of CL = 21.86 exhibited minimal bias in SUVR and Centiloid values compared to longer scans (10, 15, and 20 min). Our findings suggest that shorter scan times are a viable and effective option for brain amyloid PET imaging in clinical settings.

Dynamic neuroreceptor positron emission tomography in non-anesthetized rats using point source based motion correction: A feasibility study with [11C]ABP688

To prevent motion artifacts in small animal positron emission tomography (PET), animals are routinely scanned under anesthesia or physical restraint. Both may potentially alter metabolism and neurochemistry. This study investigates the feasibility of fully awake acquisition and subsequent absolute quantification of dynamic brain PET data via pharmacokinetic modelling in moving rats using the glutamate 5 receptor radioligand [11C]ABP688 and point source based motion correction. Five male rats underwent three dynamic [11C]ABP688 PET scans: two test-retest awake PET scans and one scan under anesthesia for comparison. Specific radioligand binding was determined via the simplified reference tissue model (reference: cerebellum) and outcome parameters BPND and R1 were evaluated in terms of stability and reproducibility. Test-retest measurements in awake animals gave reliable results with high correlations of BPND (y = 1.08 × -0.2, r = 0.99, p < 0.01) and an acceptable variability (mean over all investigated regions 15.7 ± 2.4%). Regional [11C]ABP688 BPNDs under awake and anesthetized conditions were comparable although in awake scans, absolute radioactive peak uptakes were lower and relative blood flow in terms of R1 was higher. Awake small animal PET with absolute quantification of neuroreceptor availability is technically feasible and reproducible thereby providing a suitable alternative whenever effects of anesthesia are undesirable, e.g. in sleep research.

Time-varying SUVr reflects the dynamics of dopamine increases during methylphenidate challenges in humans

Dopamine facilitates cognition and is implicated in reward processing. Methylphenidate, a dopamine transporter blocker widely used to treat attention-deficit/hyperactivity disorder, can have rewarding and addictive effects if injected. Since methylphenidate's brain uptake is much faster after intravenous than oral intake, we hypothesize that the speed of dopamine increases in the striatum in addition to its amplitude underly drug reward. To test this we use simulations and PET data of [¹¹C]raclopride's binding displacement with oral and intravenous methylphenidate challenges in 20 healthy controls. Simulations suggest that the time-varying difference in standardized uptake value ratios for [¹¹C]raclopride between placebo and methylphenidate conditions is a proxy for the time-varying dopamine increases induced by methylphenidate. Here we show that the dopamine increase induced by intravenous methylphenidate (0.25 mg/kg) in the striatum is significantly faster than that by oral methylphenidate (60 mg), and its time-to-peak is strongly associated with the intensity of the self-report of "high". We show for the first time that the "high" is associated with the fast dopamine increases induced by methylphenidate.

Luminescence Thermometry for Brain Activity Monitoring: A Perspective

Minimally invasive monitoring of brain activity is essential not only to gain understanding on the working principles of the brain, but also for the development of new diagnostic tools. In this perspective we describe how brain thermometry could be an alternative to conventional methods (e.g., magnetic resonance or nuclear medicine) for the acquisition of thermal images of the brain with enough spatial and temperature resolution to track brain activity in minimally perturbed animals. We focus on the latest advances in transcranial luminescence thermometry introducing a critical discussion on its advantages and shortcomings. We also anticipate the main challenges that the application of luminescent nanoparticles for brain thermometry will face in next years. With this work we aim to promote the development of near infrared luminescence for brain activity monitoring, which could also benefit other research areas dealing with the brain and its illnesses.

Spatiotemporal Kernel Reconstruction for Linear Parametric Neurotransmitter PET Kinetic Modeling in Motion Correction Brain PET of Awake Rats

The linear parametric neurotransmitter positron emission tomography (lp-ntPET) kinetic model can be used to detect transient changes (activation) in endogenous neurotransmitter levels. Preclinical PET scans in awake animals can be performed to investigate neurotransmitter transient changes. Here we use the spatiotemporal kernel reconstruction (Kernel) for noise reduction in dynamic PET, and lp-ntPET kinetic modeling. Kernel is adapted for motion correction reconstruction, applied in awake rat PET scans. We performed 2D rat brain phantom simulation using the ntPET model at 3 different noise levels. Data was reconstructed with independent frame reconstruction (IFR), IFR with HYPR denoising, and Kernel, and lp-ntPET kinetic parameters (k 2a : efflux rate, γ: activation magnitude, t d : activation onset time, and t p : activation peak time) were calculated. Additionally, significant activation magnitude (γ) difference with respect to a region with no activation (rest) was calculated. Finally, [11C]raclopride experiments were performed in anesthetized and awake rats, injecting cold raclopride at 20 min after scan start to simulate endogenous neurotransmitter release. For simulated data at the regional level, IFR coefficient of variation (COV) of k 2a , γ, t d and t p was reduced with HYPR denoising, but Kernel showed the lowest COV (2 fold reduction compared with IFR). At the pixel level the same trend is observed for k 2a , γ, t d and t p COV, but reduction is larger with Kernel compared with IFR (10-14 fold). Bias in γ with respect with noise-free values was additionally reduced using Kernel (difference of 292, 72.4, and -6.92% for IFR, IFR+KYPR, and Kernel, respectively). Significant difference in activation between the rest and active region could be detected at a simulated activation of 160% for IFR and IFR+HYPR, and of 120% for Kernel. In rat experiments, lp-ntPET parameters have better confidence intervals using Kernel. In the γ, and t d parametric maps, the striatum structure can be identified with Kernel but not with IFR. Striatum voxel-wise γ, t d and t p values have lower variability using Kernel compared with IFR and IFR+HYPR. The spatiotemporal kernel reconstruction adapted for motion correction reconstruction allows to improve lp-ntPET kinetic modeling noise in awake rat studies, as well as detection of subtle neurotransmitter activations.

Whole-brain studies of spontaneous behavior in head-fixed rats enabled by zero echo time MB-SWIFT fMRI

Understanding the link between the brain activity and behavior is a key challenge in modern neuroscience. Behavioral neuroscience, however, lacks tools to record whole-brain activity in complex behavioral settings. Here we demonstrate that a novel Multi-Band SWeep Imaging with Fourier Transformation (MB-SWIFT) functional magnetic resonance imaging (fMRI) approach enables whole-brain studies in spontaneously behaving head-fixed rats. First, we show anatomically relevant functional parcellation. Second, we show sensory, motor, exploration, and stress-related brain activity in relevant networks during corresponding spontaneous behavior. Third, we show odor-induced activation of olfactory system with high correlation between the fMRI and behavioral responses. We conclude that the applied methodology enables novel behavioral study designs in rodents focusing on tasks, cognition, emotions, physical exercise, and social interaction. Importantly, novel zero echo time and large bandwidth approaches, such as MB-SWIFT, can be applied for human behavioral studies, allowing more freedom as body movement is dramatically less restricting factor.

Translation of Preclinical PET Imaging Findings: Challenges and Motion Correction to Overcome the Confounding Effect of Anesthetics

Preclinical brain positron emission tomography (PET) in animals is performed using anesthesia to avoid movement during the PET scan. In contrast, brain PET scans in humans are typically performed in the awake subject. Anesthesia is therefore one of the principal limitations in the translation of preclinical brain PET to the clinic. This review summarizes the available literature supporting the confounding effect of anesthesia on several PET tracers for neuroscience in preclinical small animal scans. In a second part, we present the state-of-the-art methodologies to circumvent this limitation to increase the translational significance of preclinical research, with an emphasis on motion correction methods. Several motion tracking systems compatible with preclinical scanners have been developed, each one with its advantages and limitations. These systems and the novel experimental setups they can bring to preclinical brain PET research are reviewed here. While technical advances have been made in this field, and practical implementations have been demonstrated, the technique should become more readily available to research centers to allow for a wider adoption of the motion correction technique for brain research.

Motion estimation and correction in SPECT, PET and CT

Patient motion impacts single photon emission computed tomography (SPECT), positron emission tomography (PET) and X-ray computed tomography (CT) by giving rise to projection data inconsistencies that can manifest as reconstruction artifacts, thereby degrading image quality and compromising accurate image interpretation and quantification. Methods to estimate and correct for patient motion in SPECT, PET and CT have attracted considerable research effort over several decades. The aims of this effort have been two-fold: to estimate relevant motion fields characterizing the various forms of voluntary and involuntary motion; and to apply these motion fields within a modified reconstruction framework to obtain motion-corrected images. The aims of this review are to outline the motion problem in medical imaging and to critically review published methods for estimating and correcting for the relevant motion fields in clinical and preclinical SPECT, PET and CT. Despite many similarities in how motion is handled between these modalities, utility and applications vary based on differences in temporal and spatial resolution. Technical feasibility has been demonstrated in each modality for both rigid and non-rigid motion, but clinical feasibility remains an important target. There is considerable scope for further developments in motion estimation and correction, and particularly in data-driven methods that will aid clinical utility. State-of-the-art machine learning methods may have a unique role to play in this context.

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.

Conscious rat PET imaging with soft immobilization for quantitation of brain functions: comprehensive assessment of anesthesia effects on cerebral blood flow and metabolism

BACKGROUND

Animal brain functions evaluated by in vivo imaging under anesthesia can be affected by anesthetic agents, resulting in incorrect assessment of physiological brain function. We therefore performed dynamic positron emission tomography (PET) imaging of conscious rats using recently reported soft immobilization to validate the efficacy of the immobilization for brain function assessments. We also determined the effects of six anesthetic agents-a mixed anesthetic agent (MMB), ketamine + xylazine (KX), chloral hydrate (Chloral), pentobarbital (PTB), propofol (PF), and isoflurane (IFL)-on brain function by comparison with conscious rats.

RESULTS

The immobilization enabled 45-min dynamic [¹⁸F]FDG-PET acquisition with arterial blood sampling using conscious rats without the use of special techniques or invasive surgery. The spatial resolution and quantitativity of [¹⁸F]FDG-PET were not significantly lower for conscious rats than for anesthetized rats. While MMB, Chloral, PTB, and PF showed ubiquitous reduction in the cerebral metabolic rates of glucose (CMR_glu) in brain regions, KX and IFL showed higher reductions in cerebellum and interbrain, and cerebellum, respectively. Cerebral blood flow (CBF) was reduced by MMB, KX, PTB, and PF; increased by IFL; and unaltered by Chloral. The magnitude of decrease in CMR_glu and CBF for MMB were not larger than for other five anesthetic agents, although blood glucose levels and body temperature can be easily affected by MMB.

CONCLUSION

The six anesthetic agents induced various effects on CMR_glu and CBF. The immobilization technique presented here is a promising tool for noninvasive brain functional imaging using conscious rats to avoid the effects of anesthetic agents.

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.

[18F]F13640, a 5-HT1A Receptor Radiopharmaceutical Sensitive to Brain Serotonin Fluctuations

Introduction

Serotonin is involved in a variety of physiological functions and brain disorders. In this context, efforts have been made to investigate the in vivo fluctuations of this neurotransmitter using positron emission tomography (PET) imaging paradigms. Since serotonin is a full agonist, it binds preferentially to G-protein coupled receptors. In contrast, antagonist PET ligands additionally interact with uncoupled receptors. This could explain the lack of sensitivity to serotonin fluctuations of current 5-HT_1A radiopharmaceuticals which are mainly antagonists and suggests that agonist radiotracers would be more appropriate to measure changes in neurotransmitter release. The present study evaluated the sensitivity to endogenous serotonin release of a recently developed, selective 5-HT_1A receptor PET radiopharmaceutical, the agonist [¹⁸F]F13640 (a.k.a. befiradol or NLX-112).

Materials and Methods

Four cats each underwent three PET scans with [¹⁸F]F13640, i.e., a control PET scan of 90 min, a PET scan preceded 30 min before by an intravenous injection 1 mg/kg of d-fenfluramine, a serotonin releaser (blocking challenge), and a PET scan comprising the intravenous injection of 1 mg/kg of d-fenfluramine 30 min after the radiotracer injection (displacement challenge). Data were analyzed with regions of interest and voxel-based approaches. A lp-ntPET model approach was implemented to determine the dynamic of serotonin release during the challenge study.

Results

D-fenfluramine pretreatment elicited a massive inhibition of [¹⁸F]F13640 labeling in regions known to express 5-HT_1A receptors, e.g., raphe nuclei, hippocampus, thalamus, anterior cingulate cortex, caudate putamen, occipital, frontal and parietal cortices, and gray matter of cerebellum. Administration of d-fenfluramine during PET acquisition indicates changes in occupancy from 10% (thalamus) to 31% (gray matter of cerebellum) even though the dissociation rate of [¹⁸F]F13640 over the 90 min acquisition time was modest. The lp-ntPET simulation succeeded in differentiating the control and challenge conditions.

Conclusion

The present findings demonstrate that labeling of 5-HT_1A receptors with [¹⁸F]F13640 is sensitive to serotonin concentration fluctuations in vivo. Although the data underline the need to perform longer PET scan to ensure accurate measure of displacement, they support clinical development of [¹⁸F]F13640 as a tool to explore experimental paradigms involving physiological or pathological (neurological or neuropsychiatric pathologies) fluctuations of extracellular serotonin.

Quo Vadis, Nanoparticle-Enabled In Vivo Fluorescence Imaging?

The exciting advancements that we are currently witnessing in terms of novel materials and synthesis approaches are leading to the development of colloidal nanoparticles (NPs) with increasingly greater tunable properties. We have now reached a point where it is possible to synthesize colloidal NPs with functionalities tailored to specific societal demands. The impact of this new wave of colloidal NPs has been especially important in the field of biomedicine. In that vein, luminescent NPs with improved brightness and near-infrared working capabilities have turned out to be optimal optical probes that are capable of fast and high-resolution in vivo imaging. However, luminescent NPs have thus far only reached a limited portion of their potential. Although we believe that the best is yet to come, the future might not be as bright as some of us think (and have hoped!). In particular, translation of NP-based fluorescence imaging from preclinical studies to clinics is not straightforward. In this Perspective, we provide a critical assessment and highlight promising research avenues based on the latest advances in the fields of luminescent NPs and imaging technologies. The disillusioned outlook we proffer herein might sound pessimistic at first, but we consider it necessary to avoid pursuing "pipe dreams" and redirect the efforts toward achievable-yet ambitious-goals.

Quantitative Rodent Brain Receptor Imaging

Positron emission tomography (PET) is a non-invasive imaging technology employed to describe metabolic, physiological, and biochemical processes in vivo. These include receptor availability, metabolic changes, neurotransmitter release, and alterations of gene expression in the brain. Since the introduction of dedicated small-animal PET systems along with the development of many novel PET imaging probes, the number of PET studies using rats and mice in basic biomedical research tremendously increased over the last decade. This article reviews challenges and advances of quantitative rodent brain imaging to make the readers aware of its physical limitations, as well as to inspire them for its potential applications in preclinical research. In the first section, we briefly discuss the limitations of small-animal PET systems in terms of spatial resolution and sensitivity and point to possible improvements in detector development. In addition, different acquisition and post-processing methods used in rodent PET studies are summarized. We further discuss factors influencing the test-retest variability in small-animal PET studies, e.g., different receptor quantification methodologies which have been mainly translated from human to rodent receptor studies to determine the binding potential and changes of receptor availability and radioligand affinity. We further review different kinetic modeling approaches to obtain quantitative binding data in rodents and PET studies focusing on the quantification of endogenous neurotransmitter release using pharmacological interventions. While several studies have focused on the dopamine system due to the availability of several PET tracers which are sensitive to dopamine release, other neurotransmitter systems have become more and more into focus and are described in this review, as well. We further provide an overview of latest genome engineering technologies, including the CRISPR/Cas9 and DREADD systems that may advance our understanding of brain disorders and function and how imaging has been successfully applied to animal models of human brain disorders. Finally, we review the strengths and opportunities of simultaneous PET/magnetic resonance imaging systems to study drug-receptor interactions and challenges for the translation of PET results from bench to bedside.

Denoising non-steady state dynamic PET data using a feed-forward neural network

The quality of reconstructed dynamic PET images, as well as the statistical reliability of the estimated pharmacokinetic parameters is often compromised by high levels of statistical noise, particularly at the voxel level. Many denoising strategies have been proposed, both in the temporal and spatial domain, which substantially improve the signal to noise ratio of the reconstructed dynamic images. However, although most filtering approaches are fairly successful in reducing the spatio-temporal inter-voxel variability, they may also average out or completely eradicate the critically important temporal signature of a transient neurotransmitter activation response that may be present in a non-steady state dynamic PET study. In this work, we explore an approach towards temporal denoising of non-steady state dynamic PET images using an artificial neural network, which was trained to identify the temporal profile of a time-activity curve, while preserving any potential activation response. We evaluated the performance of a feed-forward perceptron neural network to improve the signal to noise ratio of dynamic [¹¹C]raclopride activation studies and compared it with the widely used highly constrained back projection (HYPR) filter. Results on both simulated Geant4 Application for Tomographic Emission data of a realistic rat brain phantom and experimental animal data of a freely moving animal study showed that the proposed neural network can efficiently improve the noise characteristics of dynamic data in the temporal domain, while it can lead to a more reliable estimation of voxel-wise activation response in target region. In addition, improvements in signal-to-noise ratio achieved by denoising the dynamic data using the proposed neural network led to improved accuracy and precision of the estimated model parameters of the lp-ntPET model, compared to the HYPR filter. The performance of the proposed denoising approach strongly depends on the amount of noise in the dynamic PET data, with higher noise leading to substantially higher variability in the estimated parameters of the activation response. Overall, the feed-forward network led to a similar performance as the HYPR filter in terms of spatial denoising, but led to notable improvements in terms of temporal denoising, which in turn improved the estimation activation parameters.

Role of Nuclear Imaging to Understand the Neural Substrates of Brain Disorders in Laboratory Animals: Current Status and Future Prospects

Molecular imaging, which allows the real-time visualization, characterization and measurement of biological processes, is becoming increasingly used in neuroscience research. Scintigraphy techniques such as single photon emission computed tomography (SPECT) and positron emission tomography (PET) provide qualitative and quantitative measurement of brain activity in both physiological and pathological states. Laboratory animals, and rodents in particular, are essential in neuroscience research, providing plenty of models of brain disorders. The development of innovative high-resolution small animal imaging systems together with their radiotracers pave the way to the study of brain functioning and neurotransmitter release during behavioral tasks in rodents. The assessment of local changes in the release of neurotransmitters associated with the performance of a given behavioral task is a turning point for the development of new potential drugs for psychiatric and neurological disorders. This review addresses the role of SPECT and PET small animal imaging systems for a better understanding of brain functioning in health and disease states. Brain imaging in rodent models faces a series of challenges since it acts within the boundaries of current imaging in terms of sensitivity and spatial resolution. Several topics are discussed, including technical considerations regarding the strengths and weaknesses of both technologies. Moreover, the application of some of the radioligands developed for small animal nuclear imaging studies is discussed. Then, we examine the changes in metabolic and neurotransmitter activity in various brain areas during task-induced neural activation with special regard to the imaging of opioid, dopaminergic and cannabinoid receptors. Finally, we discuss the current status providing future perspectives on the most innovative imaging techniques in small laboratory animals. The challenges and solutions discussed here might be useful to better understand brain functioning allowing the translation of preclinical results into clinical applications.

Glymphatic Cerebrospinal Fluid and Solute Transport Quantified by MRI and PET Imaging

Over the past decade there has been an enormous progress in our understanding of fluid and solute transport in the central nervous system (CNS). This is due to a number of factors, including important developments in whole brain imaging technology and computational fluid dynamics analysis employed for the elucidation of glymphatic transport function in the live animal and human brain. In this paper, we review the technical aspects of dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in combination with administration of Gd-based tracers into the cerebrospinal fluid (CSF) for tracking glymphatic solute and fluid transport in the CNS as well as lymphatic drainage. Used in conjunction with advanced computational processing methods including optimal mass transport analysis, one gains new insights into the biophysical forces governing solute transport in the CNS which leads to intriguing new research directions. Considering drainage pathways, we review the novel T1 mapping technique for quantifying glymphatic transport and cervical lymph node drainage concurrently in the same subject. We provide an overview of knowledge gleaned from DCE-MRI studies of glymphatic transport and meningeal lymphatic drainage. Finally, we introduce positron emission tomography (PET) and CSF administration of radiotracers as an alternative method to explore other pharmacokinetic aspects of CSF transport into brain parenchyma as well as efflux pathways.

Motion Dependent and Spatially Variant Resolution Modeling for PET Rigid Motion Correction

Recent advances in positron emission tomography (PET) have allowed to perform brain scans of freely moving animals by using rigid motion correction. One of the current challenges in these scans is that, due to the PET scanner spatially variant point spread function (SVPSF), motion corrected images have a motion dependent blurring since animals can move throughout the entire field of view (FOV). We developed a method to calculate the image-based resolution kernels of the motion dependent and spatially variant PSF (MD-SVPSF) to correct the loss of spatial resolution in motion corrected reconstructions. The resolution kernels are calculated for each voxel by sampling and averaging the SVPSF at all positions in the scanner FOV where the moving object was measured. In resolution phantom scans, the use of the MD-SVPSF resolution model improved the spatial resolution in motion corrected reconstructions and corrected the image deformation caused by the parallax effect consistently for all motion patterns, outperforming the use of a motion independent SVPSF or Gaussian kernels. Compared to motion correction in which the SVPSF is applied independently for every pose, our method performed similarly, but with more than two orders of magnitude faster computation time. Importantly, in scans of freely moving mice, brain regional quantification in motion-free and motion corrected images was better correlated when using the MD-SVPSF in comparison with motion independent SVPSF and a Gaussian kernel. The method developed here allows to obtain consistent spatial resolution and quantification in motion corrected images, independently of the motion pattern of the subject.

Bayesian Estimation of the ntPET Model in Single-Scan Competition PET Studies

This paper proposes an innovative method, named b-ntPET, for solving a competition model in PET. The model is built upon the state-of-the-art method called lp-ntPET. It consists in identifying the parameters of the PET kinetic model relative to a reference region that rule the steady state exchanges, together with the identification of four additional parameters defining a displacement curve caused by an endogenous neurotransmitter discharge, or by a competing injected drug targeting the same receptors as the PET tracer. The resolution process of lp-ntPET is however suboptimal due to the use of discretized basis functions, and is very sensitive to noise, limiting its sensitivity and accuracy. Contrary to the original method, our proposed resolution approach first estimates the probability distribution of the unknown parameters using Markov-Chain Monte-Carlo sampling, distributions from which the estimates are then inferred. In addition, and for increased robustness, the noise level is jointly estimated with the parameters of the model. Finally, the resolution is formulated in a Bayesian framework, allowing the introduction of prior knowledge on the parameters to guide the estimation process toward realistic solutions. The performance of our method was first assessed and compared head-to-head with the reference method lp-ntPET using well-controlled realistic simulated data. The results showed that the b-ntPET method is substantially more robust to noise and much more sensitive and accurate than lp-ntPET. We then applied the model to experimental animal data acquired in pharmacological challenge studies and human data with endogenous releases induced by transcranial direct current stimulation. In the drug challenge experiment on cats using [¹⁸F]MPPF, a serotoninergic 1A antagonist radioligand, b-ntPET measured a dose response associated with the amount of the challenged injected concurrent 5-HT1A agonist, where lp-ntPET failed. In human [¹¹C]raclopride experiment, contrary to lp-ntPET, b-ntPET successfully detected significant endogenous dopamine releases induced by the stimulation. In conclusion, our results showed that the proposed method b-ntPET has similar performance to lp-ntPET for detecting displacements, but with higher resistance to noise and better robustness to various experimental contexts. These improvements lead to the possibility of detecting and characterizing dynamic drug occupancy from a single PET scan more efficiently.

Small animal PET: a review of what we have done and where we are going

Small animal research is an essential tool in studying both pharmaceutical biodistributions and disease progression over time. Furthermore, through the rapid development of in vivo imaging technology over the last few decades, small animal imaging (also referred to as preclinical imaging) has become a mainstay for all fields of biologic research and a center point for most preclinical cancer research. Preclinical imaging modalities include optical, MRI and MRS, microCT, small animal PET, ultrasound, and photoacoustic, each with their individual strengths. The strong points of small animal PET are its translatability to the clinic; its quantitative imaging capabilities; its whole-body imaging ability to dynamically trace functional/biochemical processes; its ability to provide useful images with only nano- to pico‑ molar concentrations of administered compounds; and its ability to study animals serially over time. This review paper gives an overview of the development and evolution of small animal PET imaging. It provides an overview of detector designs; system configurations; multimodality PET imaging systems; image reconstruction and analysis tools; and an overview of research and commercially available small animal PET systems. It concludes with a look toward developing technologies/methodologies that will further enhance the impact of small animal PET imaging on medical research in the future.