Simulation-based optimisation of the PET data processing for partial saturation approach protocols

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.

In vivo absolute quantification of striatal and extrastriatal D2/3 receptors with [123I]epidepride SPECT

Background

[¹²³I]epidepride is a high-affinity radiotracer used in single-photon emission computed tomography (SPECT) imaging of the D_2/3 receptors. It binds with high affinity to striatal and extrastriatal receptors. Nevertheless, its slow kinetics in the striatum impedes quantification in this region. Thus, an approach that would allow a simultaneous quantification of both striatal and extrastriatal D_2/3 receptors would be of interest for preclinical and clinical SPECT neuroimaging. We describe a partial saturation protocol that allows us to produce an in vivo Scatchard plot and thus estimate B_avail and appK_d separately in both striatal and extrastriatal regions, through a single dynamic SPECT session. To validate this approach, a multi-injection protocol is used for the full kinetic modeling of [¹²³I]epidepride using a two-tissue compartment, 5-parameter model (2T-5k).

Methods

Eighteen male rats were used. Binding parameters were estimated using the multi-injection protocol. Various simulations were performed to estimate the optimal conditions for the partial saturation protocol, which was applied at the region and voxel level. The results of the partial saturation study were compared to those obtained with the 2T-5k model. To illustrate the interest of the partial saturation approach, we performed a preliminary study of the effect of a chronic, subcutaneous administration of haloperidol (1 mg/kg/day), a D₂ receptor antagonist, on the B_avail of [¹²³I]epidepride in the rat striatum.

Results

A series of simulations demonstrated that a mass of 3 ug/kg of unlabeled epidepride allows the formation of an in vivo Scatchard plot. The partial saturation study led to robust estimations of B_avail in all brain regions that highly correlated (r = 0.99) with the corresponding values from the multi-injection study. A chronic haloperidol treatment resulted in a 17.9% increase in the B_avail values in the left Caudate Putamen nucleus (CP) (p = 0.07) and a 13.8% increase in the right CP (p = 0.12).

Conclusion

A partial saturation method allowed the robust quantification of D_2/3 receptors in striatal and extrastriatal D_2/3 receptors with a single-scan approach. This approach may be applied in the mapping of the D_2/3 receptor in translational biological studies and potentially, in clinical SPECT imaging.

Longitudinal mouse-PET imaging: a reliable method for estimating binding parameters without a reference region or blood sampling

Abstract

Longitudinal mouse PET imaging is becoming increasingly popular due to the large number of transgenic and disease models available but faces challenges. These challenges are related to the small size of the mouse brain and the limited spatial resolution of microPET scanners, along with the small blood volume making arterial blood sampling challenging and impossible for longitudinal studies. The ability to extract an input function directly from the image would be useful for quantification in longitudinal small animal studies where there is no true reference region available such as TSPO imaging.

Methods

Using dynamic, whole-body ¹⁸F-DPA-714 PET scans (60 min) in a mouse model of hippocampal sclerosis, we applied a factor analysis (FA) approach to extract an image-derived input function (IDIF). This mouse-specific IDIF was then used for 4D-resolution recovery and denoising (4D-RRD) that outputs a dynamic image with better spatial resolution and noise properties, and a map of the total volume of distribution (V_T) was obtained using a basis function approach in a total of 9 mice with 4 longitudinal PET scans each. We also calculated percent injected dose (%ID) with and without 4D-RRD. The V_T and %ID parameters were compared to quantified ex vivo autoradiography using regional correlations of the specific binding from autoradiography against V_T and %ID parameters.

Results

The peaks of the IDIFs were strongly correlated with the injected dose (Pearson R = 0.79). The regional correlations between the %ID estimates and autoradiography were R = 0.53 without 4D-RRD and 0.72 with 4D-RRD over all mice and scans. The regional correlations between the V_T estimates and autoradiography were R = 0.66 without 4D-RRD and 0.79 with application of 4D-RRD over all mice and scans.

Conclusion

We present a FA approach for IDIF extraction which is robust, reproducible and can be used in quantification methods for resolution recovery, denoising and parameter estimation. We demonstrated that the proposed quantification method yields parameter estimates closer to ex vivo measurements than semi-quantitative methods such as %ID and is immune to tracer binding in tissue unlike reference tissue methods. This approach allows for accurate quantification in longitudinal PET studies in mice while avoiding repeated blood sampling.

Electronic supplementary material

The online version of this article (10.1007/s00259-020-04755-5) contains supplementary material, which is available to authorized users.

Dynamic image denoising for voxel-wise quantification with Statistical Parametric Mapping in molecular neuroimaging

Purpose

PET and SPECT voxel kinetics are highly noised. To our knowledge, no study has determined the effect of denoising on the ability to detect differences in binding at the voxel level using Statistical Parametric Mapping (SPM).

Methods

In the present study, groups of subject-images with a 10%- and 20%- difference in binding of [¹²³I]iomazenil (IMZ) were simulated. They were denoised with Factor Analysis (FA). Parametric images of binding potential (BP_ND) were produced with the simplified reference tissue model (SRTM) and the Logan non-invasive graphical analysis (LNIGA) and analyzed using SPM to detect group differences. FA was also applied to [¹²³I]IMZ and [¹¹C]flumazenil (FMZ) clinical images (n = 4) and the variance of BP_ND was evaluated.

Results

Estimations from FA-denoised simulated images provided a more favorable bias-precision profile in SRTM and LNIGA quantification. Simulated differences were detected in a higher number of voxels when denoised simulated images were used for voxel-wise estimations, compared to quantification on raw simulated images. Variability of voxel-wise binding estimations on denoised clinical SPECT and PET images was also significantly diminished.

Conclusion

In conclusion, noise removal from dynamic brain SPECT and PET images may optimize voxel-wise BP_ND estimations and detection of biological differences using SPM.

Cortico-Amygdala-Striatal Activation by Modafinil/Flecainide Combination

Background

Modafinil, a nonamphetaminic wake-promoting compound, is prescribed as first line therapy in narcolepsy, an invalidating disorder characterized by excessive daytime sleepiness and cataplexy. Although its mode of action remains incompletely known, recent studies indicated that modafinil modulates astroglial connexin-based gap junctional communication as administration of a low dose of flecainide, an astroglial connexin inhibitor, enhanced the wake-promoting and procognitive activity of modafinil in rodents and healthy volunteers. The aim of this study is to investigate changes in glucose cerebral metabolism in rodents, induced by the combination of modafinil+flecainide low dose (called THN102).

Methods

The impact of THN102 on brain glucose metabolism was noninvasively investigated using 18F-2-fluoro-2-deoxy-D-glucose Positron Emission Tomography imaging in Sprague-Dawley male rats. Animals were injected with vehicle, flecainide, modafinil, or THN102 and further injected with 18F-2-fluoro-2-deoxy-D-glucose followed by 60-minute Positron Emission Tomography acquisition. 18F-2-fluoro-2-deoxy-D-glucose Positron Emission Tomography images were coregistered to a rat brain template and normalized from the total brain Positron Emission Tomography signal. Voxel-to-voxel analysis was performed using SPM8 software. Comparison of brain glucose metabolism between groups was then performed.

Results

THN102 significantly increased regional brain glucose metabolism as it resulted in large clusters of 18F-2-fluoro-2-deoxy-D-glucose uptake localized in the cortex, striatum, and amygdala compared with control or drugs administered alone. These regions, highly involved in the regulation of sleep-wake cycle, emotions, and cognitive functions were hence quantitatively modulated by THN102.

Conclusion

Data presented here provide the first evidence of a regional brain activation induced by THN102, currently being tested in a phase II clinical trial in narcoleptic patients.

OSSI-PET: Open-Access Database of Simulated [(11)C]Raclopride Scans for the Inveon Preclinical PET Scanner: Application to the Optimization of Reconstruction Methods for Dynamic Studies

A wide range of medical imaging applications benefits from the availability of realistic ground truth data. In the case of positron emission tomography (PET), ground truth data is crucial to validate processing algorithms and assessing their performances. The design of such ground truth data often relies on Monte-Carlo simulation techniques. Since the creation of a large dataset is not trivial both in terms of computing time and realism, we propose the OSSI-PET database containing 350 simulated [(11)C]Raclopride dynamic scans for rats, created specifically for the Inveon pre-clinical PET scanner. The originality of this database lies on the availability of several groups of scans with controlled biological variations in the striata. Besides, each group consists of a large number of realizations (i.e., noise replicates). We present the construction methodology of this database using rat pharmacokinetic and anatomical models. A first application using the OSSI-PET database is presented. Several commonly used reconstruction techniques were compared in terms of image quality, accuracy and variability of the activity estimates and of the computed kinetic parameters. The results showed that OP-OSEM3D iterative reconstruction method outperformed the other tested methods. Analytical methods such as FBP2D and 3DRP also produced satisfactory results. However, FORE followed by OSEM2D reconstructions should be avoided. Beyond the illustration of the potential of the database, this application will help scientists to understand the different sources of noise and bias that can occur at the different steps in the processing and will be very useful for choosing appropriate reconstruction methods and parameters.

4D PET iterative deconvolution with spatiotemporal regularization for quantitative dynamic PET imaging

Quantitative measurements in dynamic PET imaging are usually limited by the poor counting statistics particularly in short dynamic frames and by the low spatial resolution of the detection system, resulting in partial volume effects (PVEs). In this work, we present a fast and easy to implement method for the restoration of dynamic PET images that have suffered from both PVE and noise degradation. It is based on a weighted least squares iterative deconvolution approach of the dynamic PET image with spatial and temporal regularization. Using simulated dynamic [(11)C] Raclopride PET data with controlled biological variations in the striata between scans, we showed that the restoration method provides images which exhibit less noise and better contrast between emitting structures than the original images. In addition, the method is able to recover the true time activity curve in the striata region with an error below 3% while it was underestimated by more than 20% without correction. As a result, the method improves the accuracy and reduces the variability of the kinetic parameter estimates calculated from the corrected images. More importantly it increases the accuracy (from less than 66% to more than 95%) of measured biological variations as well as their statistical detectivity.