Plasma radiometabolite correction in dynamic PET studies: Insights on the available modeling approaches

Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging

INTRODUCTION

We propose a novel approach for the non-invasive quantification of dynamic PET imaging data, focusing on the arterial input function (AIF) without the need for invasive arterial cannulation.

METHODS

Our method utilizes a combination of three-dimensional depth-wise separable convolutional layers and a physically informed deep neural network to incorporatea priori knowledge about the AIF's functional form and shape, enabling precise predictions of the concentrations of [11C]PBR28 in whole blood and the free tracer in metabolite-corrected plasma.

RESULTS

We found a robust linear correlation between our model's predicted AIF curves and those obtained through traditional, invasive measurements. We achieved an average cross-validated Pearson correlation of 0.86 for whole blood and 0.89 for parent plasma curves. Moreover, our method's ability to estimate the volumes of distribution across several key brain regions - without significant differences between the use of predicted versus actual AIFs in a two-tissue compartmental model - successfully captures the intrinsic variability related to sex, the binding affinity of the translocator protein (18 kDa), and age.

CONCLUSIONS

These results not only validate our method's accuracy and reliability but also establish a foundation for a streamlined, non-invasive approach to dynamic PET data quantification. By offering a precise and less invasive alternative to traditional quantification methods, our technique holds significant promise for expanding the applicability of PET imaging across a wider range of tracers, thereby enhancing its utility in both clinical research and diagnostic settings.

Developing Low Molecular Weight PET and SPECT Imaging Agents

Imaging agents for positron emission tomography (PET) and single-photon emission computerized tomography (SPECT) have shown their utility in many situations, answering clinical questions related to drug development and medical considerations. The discovery and development of imaging agents follow a well-understood process, with variations related to available starting points and to the envisaged imaging application. This article describes the general development path leading from the expression of an imaging need and project initiation to a clinically usable imaging agent. The definition of the project rationale, the design and optimization of early leads, and the assessment of the imaging potential of an imaging agent candidate are followed by preclinical and clinical development activities that differ from those required for therapeutic agents. These include radiolabeling with a positron emitter and first-in-human clinical studies, to rapidly evaluate the ability of a new imaging agent to address the questions it was designed to answer.

Exact parameter identification in PET pharmacokinetic modeling using the irreversible two tissue compartment model. Phys Med Biol 2024;69:165008. [PMID: 38830366 PMCID: PMC11288174 DOI: 10.1088/1361-6560/ad539e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Objective.In quantitative dynamic positron emission tomography (PET), time series of images, reflecting the tissue response to the arterial tracer supply, are reconstructed. This response is described by kinetic parameters, which are commonly determined on basis of the tracer concentration in tissue and the arterial input function. In clinical routine the latter is estimated by arterial blood sampling and analysis, which is a challenging process and thus, attempted to be derived directly from reconstructed PET images. However, a mathematical analysis about the necessity of measurements of the common arterial whole blood activity concentration, and the concentration of free non-metabolized tracer in the arterial plasma, for a successful kinetic parameter identification does not exist. Here we aim to address this problem mathematically.Approach.We consider the identification problem in simultaneous pharmacokinetic modeling of multiple regions of interests of dynamic PET data using the irreversible two-tissue compartment model analytically. In addition to this consideration, the situation of noisy measurements is addressed using Tikhonov regularization. Furthermore, numerical simulations with a regularization approach are carried out to illustrate the analytical results in a synthetic application example.Main results.We provide mathematical proofs showing that, under reasonable assumptions, all metabolic tissue parameters can be uniquely identified without requiring additional blood samples to measure the arterial input function. A connection to noisy measurement data is made via a consistency result, showing that exact reconstruction of the ground-truth tissue parameters is stably maintained in the vanishing noise limit. Furthermore, our numerical experiments suggest that an approximate reconstruction of kinetic parameters according to our analytic results is also possible in practice for moderate noise levels.Significance.The analytical result, which holds in the idealized, noiseless scenario, suggests that for irreversible tracers, fully quantitative dynamic PET imaging is in principle possible without costly arterial blood sampling and metabolite analysis.

A blood-free modeling approach for the quantification of the blood-to-brain tracer exchange in TSPO PET imaging

Introduction

Recent evidence suggests the blood-to-brain influx rate (K1 ) in TSPO PET imaging as a promising biomarker of blood-brain barrier (BBB) permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for K1 estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function (1T1K-IDIF).

Methods

The method is tested on a multi-site dataset containing 177 PET studies from two TSPO tracers ([11C]PBR28 and [18F]DPA714). Firstly, 1T1K-IDIF K1 estimates were compared in terms of both bias and correlation with standard kinetic methodology. Then, the method was tested on an independent sample of [11C]PBR28 scans before and after inflammatory interferon-α challenge, and on test-retest dataset of [18F]DPA714 scans.

Results

Comparison with standard kinetic methodology showed good-to-excellent intra-subject correlation for regional 1T1K-IDIF-K1 (ρintra  = 0.93 ± 0.08), although the bias was variable depending on IDIF ability to approximate blood input functions (0.03-0.39 mL/cm3/min). 1T1K-IDIF-K1 unveiled a significant reduction of BBB permeability after inflammatory interferon-α challenge, replicating results from standard quantification. High intra-subject correlation (ρ = 0.97 ± 0.01) was reported between K1 estimates of test and retest scans.

Discussion

This evidence supports 1T1K-IDIF as blood-free alternative to assess TSPO tracers' unidirectional blood brain clearance. K1 investigation could complement more traditional measures in TSPO studies, and even allow further mechanistic insight in the interpretation of TSPO signal.

Kinetic analysis of cardiac dynamic 18F-Florbetapir PET in healthy volunteers and amyloidosis patients: A pilot study

Objectives

This study aimed to explore the potential of full dynamic PET kinetic analysis in assessing amyloid binding and perfusion in the cardiac region using 18F-Florbetapir PET, establishing a quantitative approach in the clinical assessment of cardiac amyloidosis disease.

Materials & methods

The distribution volume ratios (DVRs) and the relative transport rate constant (R1), were estimated by a pseudo-simplified reference tissue model (pSRTM2) and pseudo-Logan plot (pLogan plot) with kidney reference for the region of interest-based and voxel-wise-based analyses. The parametric images generated using the pSRTM2 and linear regression with spatially constrained (LRSC) algorithm were then evaluated. Semi-quantitative analyses include standardized uptake value ratios at the early phase (SUVREP, 0.5-5 min) and late phase (SUVRLP, 50-60 min) were also calculated.

Results

Ten participants [7 healthy controls (HC) and 3 cardiac amyloidosis (CA) subjects] underwent a 60-min dynamic 18F-Florbetapir PET scan. The DVRs estimated from pSRTM2 and Logan plot were significantly increased (HC vs CA; DVRpSRTM2: 0.95 ± 0.11 vs 2.77 ± 0.42, t'(2.13) = 7.39, P = 0.015; DVRLogan: 0.80 ± 0.12 vs 2.90 ± 0.55, t'(2.08) = 6.56, P = 0.020), and R1 were remarkably decreased in CA groups, as compared to HCs (HC vs CA; 1.08 ± 0.37 vs 0.56 ± 0.10, t'(7.63) = 3.38, P = 0.010). The SUVREP and SUVRLP were highly correlated to R1 (r = 0.97, P < 0.001) and DVR(r = 0.99, P < 0.001), respectively. The DVRs in the total myocardium region increased slightly as the size of FWHM increased and became stable at a Gaussian filter ≥6 mm. The secular equilibrium of SUVR was reached at around 50-min p.i. time.

Conclusion

The DVR and R1 estimated from cardiac dynamic 18F-Florbetapir PET using pSRTM with kidney pseudo-reference tissue are suggested to quantify cardiac amyloid deposition and relative perfusion, respectively, in amyloidosis patients and healthy controls. We recommend a dual-phase scan: 0.5-5 min and 50-60 min p.i. as the appropriate time window for clinically assessing cardiac amyloidosis and perfusion measurements using 18F-Florbetapir PET.

Quantitation of dynamic total-body PET imaging: recent developments and future perspectives

BACKGROUND

Positron emission tomography (PET) scanning is an important diagnostic imaging technique used in disease diagnosis, therapy planning, treatment monitoring, and medical research. The standardized uptake value (SUV) obtained at a single time frame has been widely employed in clinical practice. Well beyond this simple static measure, more detailed metabolic information can be recovered from dynamic PET scans, followed by the recovery of arterial input function and application of appropriate tracer kinetic models. Many efforts have been devoted to the development of quantitative techniques over the last couple of decades.

CHALLENGES

The advent of new-generation total-body PET scanners characterized by ultra-high sensitivity and long axial field of view, i.e., uEXPLORER (United Imaging Healthcare), PennPET Explorer (University of Pennsylvania), and Biograph Vision Quadra (Siemens Healthineers), further stimulates valuable inspiration to derive kinetics for multiple organs simultaneously. But some emerging issues also need to be addressed, e.g., the large-scale data size and organ-specific physiology. The direct implementation of classical methods for total-body PET imaging without proper validation may lead to less accurate results.

CONCLUSIONS

In this contribution, the published dynamic total-body PET datasets are outlined, and several challenges/opportunities for quantitation of such types of studies are presented. An overview of the basic equation, calculation of input function (based on blood sampling, image, population or mathematical model), and kinetic analysis encompassing parametric (compartmental model, graphical plot and spectral analysis) and non-parametric (B-spline and piece-wise basis elements) approaches is provided. The discussion mainly focuses on the feasibilities, recent developments, and future perspectives of these methodologies for a diverse-tissue environment.

Temporal information guided dynamic dual-tracer PET signal separation network

PURPOSE

The difficulty of dynamic dual-tracer positron emission tomography (PET) technology is to separate the complete single-tracer information from mixed dual-tracer. Traditional methods cannot separate single injection single-scan dynamic dual-tracer PET images. In this paper, we propose a deep learning framework based on gated recurrent unit (GRU) network and evaluate its performance with simulation experiments and realistic monkey data.

METHODS

The proposed single-scan dynamic dual-tracer PET image separation network consists of three parts, including encoder, separation and decoder module. Encoder part is to map the mixed time activity curves (TACs) from the low-dimensional space to the high-dimensional space to get mixed weight vector matrix. Separation part is to capture the temporal information of mixed weight vector matrix using bi-directional GRU (bi-GRU) layer to obtain the single-tracer masks, and the decoding part remaps the high-dimensional single-tracer weight vector matrix to the low-dimensional space to obtain two separated single tracers.

RESULTS

In the simulation experiments under different tracers, phantoms, noise levels, arterial input function (AIF) and k-parameter with Gaussian random, compared to the stacked auto encoder (SAE) network and traditional background subtraction method, GRU-based network has better performance with low bias and mean squared error (MSE). In the realistic study, the image results of GRU network have higher mean structural similarity (MSSIM), and peak signal to noise ratio (PSNR).

CONCLUSIONS

This study demonstrates the feasibility of temporal information guided neural network in single-injection single-scan dynamic dual-tracer PET images separation. The GRU-based network uses TAC temporal information without AIFs to make the separation results more robust and accurate, which significantly outperforms state-of-the-art method qualitatively and quantitatively. This article is protected by copyright. All rights reserved.

Supervised clustering for TSPO PET imaging

PURPOSE

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

BACKGROUND

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

METHODS

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

CONCLUSIONS

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

Positron emission tomography in multiple sclerosis - straight to the target

Following the impressive progress in the treatment of relapsing-remitting multiple sclerosis (MS), the major challenge ahead is the development of treatments to prevent or delay the irreversible accumulation of clinical disability in progressive forms of the disease. The substrate of clinical progression is neuro-axonal degeneration, and a deep understanding of the mechanisms that underlie this process is a precondition for the development of therapies for progressive MS. PET imaging involves the use of radiolabelled compounds that bind to specific cellular and metabolic targets, thereby enabling direct in vivo measurement of several pathological processes. This approach can provide key insights into the clinical relevance of these processes and their chronological sequence during the disease course. In this Review, we focus on the contribution that PET is making to our understanding of extraneuronal and intraneuronal mechanisms that are involved in the pathogenesis of irreversible neuro-axonal damage in MS. We consider the major challenges with the use of PET in MS and the steps necessary to realize clinical benefits of the technique. In addition, we discuss the potential of emerging PET tracers and future applications of existing compounds to facilitate the identification of effective neuroprotective treatments for patients with MS.

Reproducibility of findings in modern PET neuroimaging: insight from the NRM2018 grand challenge

The reproducibility of findings is a compelling methodological problem that the neuroimaging community is facing these days. The lack of standardized pipelines for image processing, quantification and statistics plays a major role in the variability and interpretation of results, even when the same data are analysed. This problem is well-known in MRI studies, where the indisputable value of the method has been complicated by a number of studies that produce discrepant results. However, any research domain with complex data and flexible analytical procedures can experience a similar lack of reproducibility. In this paper we investigate this issue for brain PET imaging. During the 2018 NeuroReceptor Mapping conference, the brain PET community was challenged with a computational contest involving a simulated neurotransmitter release experiment. Fourteen international teams analysed the same imaging dataset, for which the ground-truth was known. Despite a plurality of methods, the solutions were consistent across participants, although not identical. These results should create awareness that the increased sharing of PET data alone will only be one component of enhancing confidence in neuroimaging results and that it will be important to complement this with full details of the analysis pipelines and procedures that have been used to quantify data.

Functional characterization of human brown adipose tissue metabolism

Brown adipose tissue (BAT) has long been described according to its histological features as a multilocular, lipid-containing tissue, light brown in color, that is also responsive to the cold and found especially in hibernating mammals and human infants. Its presence in both hibernators and human infants, combined with its function as a heat-generating organ, raised many questions about its role in humans. Early characterizations of the tissue in humans focused on its progressive atrophy with age and its apparent importance for cold-exposed workers. However, the use of positron emission tomography (PET) with the glucose tracer [18F]fluorodeoxyglucose ([18F]FDG) made it possible to begin characterizing the possible function of BAT in adult humans, and whether it could play a role in the prevention or treatment of obesity and type 2 diabetes (T2D). This review focuses on the in vivo functional characterization of human BAT, the methodological approaches applied to examine these features and addresses critical gaps that remain in moving the field forward. Specifically, we describe the anatomical and biomolecular features of human BAT, the modalities and applications of non-invasive tools such as PET and magnetic resonance imaging coupled with spectroscopy (MRI/MRS) to study BAT morphology and function in vivo, and finally describe the functional characteristics of human BAT that have only been possible through the development and application of such tools.

Development of a non-radiometric method for measuring the arterial input function of a 11C-labeled PET radiotracer

Positron emission tomography (PET) uses radiotracers to quantify important biochemical parameters in human subjects. A radiotracer arterial input function (AIF) is often essential for converting brain PET data into robust output measures. For radiotracers labeled with carbon-11 (t_1/2 = 20.4 min), AIF is routinely determined with radio-HPLC of blood sampled frequently during the PET experiment. There has been no alternative to this logistically demanding method, neither for regular use nor validation. A ¹¹C-labeled tracer is always accompanied by a large excess of non-radioactive tracer known as carrier. In principle, AIF might be obtained by measuring the molar activity (A_m; ratio of radioactivity to total mass; Bq/mol) of a radiotracer dose and the time-course of carrier concentration in plasma after radiotracer injection. Here, we implement this principle in a new method for determining AIF, as shown by using [¹¹C]PBR28 as a representative tracer. The method uses liquid chromatography-tandem mass spectrometry for measuring radiotracer A_m and then the carrier in plasma sampled regularly over the course of a PET experiment. A_m and AIF were determined radiometrically for comparison. The new non-radiometric method is not constrained by the short half-life of carbon-11 and is an attractive alternative to conventional AIF measurement.

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.

Kinfitr - an open-source tool for reproducible PET modelling: validation and evaluation of test-retest reliability

BACKGROUND

In positron emission tomography (PET) imaging, binding is typically estimated by fitting pharmacokinetic models to the series of measurements of radioactivity in the target tissue following intravenous injection of a radioligand. However, there are multiple different models to choose from and numerous analytical decisions that must be made when modelling PET data. Therefore, it is important that analysis tools be adapted to the specific circumstances, and that analyses be documented in a transparent manner. Kinfitr, written in the open-source programming language R, is a tool developed for flexible and reproducible kinetic modelling of PET data, i.e. performing all steps using code which can be publicly shared in analysis notebooks. In this study, we compared outcomes obtained using kinfitr with those obtained using PMOD: a widely used commercial tool.

RESULTS

Using previously collected test-retest data obtained with four different radioligands, a total of six different kinetic models were fitted to time-activity curves derived from different brain regions. We observed good correspondence between the two kinetic modelling tools both for binding estimates and for microparameters. Likewise, no substantial differences were observed in the test-retest reliability estimates between the two tools.

CONCLUSIONS

In summary, we showed excellent agreement between the open-source R package kinfitr, and the widely used commercial application PMOD. We, therefore, conclude that kinfitr is a valid and reliable tool for kinetic modelling of PET data.

First-in-human evaluation of [11C]PS13, a novel PET radioligand, to quantify cyclooxygenase-1 in the brain

PURPOSE

This study assessed whether the newly developed PET radioligand [¹¹C]PS13, which has shown excellent in vivo selectivity in previous animal studies, could be used to quantify constitutive levels of cyclooxygenase-1 (COX-1) in healthy human brain.

METHODS

Brain test-retest scans with concurrent arterial blood samples were obtained in 10 healthy individuals. The one- and unconstrained two-tissue compartment models, as well as the Logan graphical analysis were compared, and test-retest reliability and time-stability of total distribution volume (V_T) were assessed. Correlation analyses were conducted between brain regional V_T and COX-1 transcript levels provided in the Allen Human Brain Atlas.

RESULTS

In the brain, [¹¹C]PS13 showed highest uptake in the hippocampus and occipital cortex. The pericentral cortex also showed relatively higher uptake compared with adjacent neocortices. The two-tissue compartment model showed the best fit in all the brain regions, and the results from the Logan graphical analysis were consistent with those from the two-tissue compartment model. V_T values showed excellent test-retest variability (range 6.0-8.5%) and good reliability (intraclass correlation coefficient range 0.74-0.87). V_T values also showed excellent time-stability in all brain regions, confirming that there was no radiometabolite accumulation and that shorter scans were still able to reliably measure V_T. Significant correlation was observed between V_T and COX-1 transcript levels (r = 0.82, P = 0.007), indicating that [¹¹C]PS13 binding reflects actual COX-1 density in the human brain.

CONCLUSIONS

These results from the first-in-human evaluation of the ability of [¹¹C]PS13 to image COX-1 in the brain justifies extending the study to disease populations with neuroinflammation.

CLINICAL TRIAL REGISTRATION

NCT03324646 at https://clinicaltrials.gov/ . Registered October 30, 2017. Retrospectively registered.

[18F]Fluciclatide PET as a biomarker of response to combination therapy of pazopanib and paclitaxel in platinum-resistant/refractory ovarian cancer

BACKGROUND

Angiogenesis is a driver of platinum resistance in ovarian cancer. We assessed the effect of combination pazopanib and paclitaxel followed by maintenance pazopanib in patients with platinum-resistant/refractory ovarian cancer. Integrins αvβ3 and αvβ5 are both upregulated in tumor-associated vasculature. [18F]Fluciclatide is a novel PET tracer that has high affinity for integrins αvβ3/5, and was used to assess the anti-angiogenic effect of pazopanib.

PATIENTS AND METHODS

We conducted an open-label, phase Ib study in patients with platinum-resistant/refractory ovarian cancer. Patients received 1 week of single-agent pazopanib (800 mg daily) followed by combination therapy with weekly paclitaxel (80 mg/m2). Following completion of 18 weeks of combination therapy, patients continued with single-agent pazopanib until disease progression. Dynamic [18F]fluciclatide-PET imaging was conducted at baseline and after 1 week of pazopanib. Response (RECIST 1.1), toxicities, and survival outcomes were recorded. Circulating markers of angiogenesis were assessed with therapy.

RESULTS

Fourteen patients were included in the intention-to-treat analysis. Complete and partial responses were seen in seven patients (54%). Median progression-free survival (PFS) was 10.63 months, and overall survival (OS) was 18.5 months. Baseline [18F]fluciclatide uptake was predictive of long PFS. Elevated baseline circulating angiopoietin and fibroblast growth factor (FGF) were predictive of greater reduction in SUV60,mean following pazopanib. Kinetic modeling of PET data indicated a reduction in K1 and Ki following pazopanib indicating reduced radioligand delivery and retention.

CONCLUSIONS

Combination therapy followed by maintenance pazopanib is effective and tolerable in platinum-resistant/refractory ovarian cancer. [18F]Fluciclatide-PET uptake parameters predict clinical outcome with pazopanib therapy indicating an anti-angiogenic response.

Repurposing radiotracers for myelin imaging: a study comparing 18F-florbetaben, 18F-florbetapir, 18F-flutemetamol,11C-MeDAS, and 11C-PiB

PURPOSE

Drugs promoting myelin repair represent a promising therapeutic approach in multiple sclerosis and several candidate molecules are currently being evaluated, fostering the need of a quantitative method to specifically measure myelin content in vivo. PET using the benzothiazole derivative ¹¹C-PiB has been successfully used to quantify myelin content changes in humans. Stilbene derivatives, such as ¹¹C-MeDAS, have also been shown to bind to myelin in animals and are considered a promising radiopharmaceutical class for myelin imaging. Fluorinated compounds from both classes are now commercially available and thus should constitute clinically useful myelin radiotracers. The aim of this study is to provide a head-to-head comparison of ¹⁸F-florbetaben, ¹⁸F-florbetapir, ¹⁸F-flutemetamol, ¹¹C-MeDAS, and ¹¹C-PiB with regard to brain kinetics and binding in white matter (WM).

METHODS

Four baboons underwent a 90-min dynamic PET scan for each radioligand. Arterial blood samples were collected during the exam for each radiotracer, except for ¹⁸F-florbetapir, to obtain a radiometabolite-corrected input function. Standardized uptake value ratio between 75 at 90 min (SUVR_75-90), binding potential (BP) estimated with Logan method with input function, and distribution volume ratio (DVR) estimated with Logan reference method (using cerebellar gray matter as reference region) were calculated in WM and compared between tracers using mixed effect models.

RESULTS

In WM, ¹⁸F-florbetapir had the highest SUVR_75-90 (1.38 ± 0.03), followed by ¹⁸F-flutemetamol (1.34 ± 0.02), ¹⁸F-florbetaben (1.32 ± 0.07), ¹¹C-MeDAS (1.27 ± 0.04), and ¹¹C-PiB (1.25 ± 0.07). With regard to BP, ¹⁸F-florbetaben had the highest value (0.32 ± 0.06) compared with ¹⁸F-flutemetamol (0.20 ± 0.03), ¹¹C-MeDAS (0.17 ± 0.03), and ¹¹C-PiB (0.16 ± 0.03). No difference in DVR was detected between ¹⁸F-florbetaben (1.26 ± 0.06) and ¹⁸F-florbetapir (1.27 ± 0.03), but both were significantly higher in DVR than ¹⁸F-flutemetamol (1.17 ± 0.02), ¹¹C-MeDAS (1.16 ± 0.03), and ¹¹C-PiB (1.14 ± 0.02).

CONCLUSIONS

Given their higher binding and longer half-life, our study indicates that ¹⁸F-florbetapir and ¹⁸F-florbetaben are promising tracers for myelin imaging which are readily available for clinical application in demyelinating diseases.

The association of psychosocial risk factors for mental health with a brain marker altered by inflammation: A translocator protein (TSPO) PET imaging study

Psychiatric disorders associated with psychosocial risk factors, including depression and psychosis, have been shown to demonstrate increased microglia activity. Whilst preclinical studies indicate that psychosocial stress leads to increased levels of microglia in the frontal cortex, no study has yet been performed in humans. This study aimed at investigating whether psychosocial risk factors for depression and/or psychosis would be associated with alterations in a brain marker expressed by microglia, the translocator specific protein (TSPO) in humans. We used [¹¹C]-PBR28 Positron Emission Tomography on healthy subjects exposed to childhood and adulthood psychosocial risk factors (high-risk group, N = 12) and age- and sex-matched healthy controls not exposed to childhood and adulthood psychosocial risk factors (low-risk group, N = 12). The [¹¹C]-PBR28 volume of distribution (V_T) and Distribution Volume Ratio (DVR) were measured in the total gray matter, and frontal, parietal, temporal, occipital lobes. Levels of childhood trauma, anxiety and depression were measured using respectively the Childhood Trauma Questionnaire, State-anxiety questionnaire and Beck Depression Inventory. Compared to the low-risk group, the high-risk group did not exhibit significant differences in the mean [¹¹C]-PBR28 V_T (F(1,20) = 1.619, p = 0.218) or DVR (F(1,22) = 0.952, p = 0.340) on any region. There were no significant correlations between the [¹¹C]-PBR28 V_T and DVRs in total gray matter and frontal lobe and measures of childhood trauma, anxiety and depression. Psychosocial risk factors for depression and/or psychosis are unlikely to be associated with alterations in [¹¹C]-PBR28 binding, indicating that alterations in TSPO expression reported in these disorders is unlikely to be caused by psychosocial risk factors alone.

Automatic Extraction of a Reference Region for the Noninvasive Quantification of Translocator Protein in Brain Using 11C-PBR28

Brain inflammation is associated with various types of neurodegenerative diseases, including Alzheimer disease (AD). Quantifying inflammation with PET is a challenging and invasive procedure, especially in frail patients, because it requires blood sampling from an arterial catheter. A widely used alternative to arterial sampling is a supervised clustering algorithm (SVCA), which identifies the voxels with minimal specific binding in the PET images, thus extracting a reference region for noninvasive kinetic modeling. Methods: We tested this algorithm on a large population of subjects injected with the translocator protein radioligand ¹¹C-PBR28 and compared the kinetic modeling results obtained with the gold standard of arterial input function (V _T/f _p) with those obtained by SVCA (distribution volume ratio [DVR] with Logan plot). The study comprised 57 participants (21 healthy controls, 11 mild cognitive impairment patients, and 25 AD patients). Results: We found that V _T/f _p was greater in AD patients than in controls in the inferior parietal, combined middle and inferior temporal, and entorhinal cortices. SVCA-DVR identified increased binding in the same regions and in an additional one, the parahippocampal region. We noticed however that the average amplitude of the reference curve obtained from subjects with genetic high-affinity binding for ¹¹C-PBR28 was significantly larger than that from subjects with moderate affinity. This suggests that the reference curve extracted by SVCA was contaminated by specific binding. Conclusion: SVCA allows the noninvasive quantification of inflammatory biomarker translocator protein measured with ¹¹C-PBR28 but without the need of arterial sampling. Although the reference curves were contaminated with specific binding, the decreased variance of the outcome measure, SVCA DVR, allowed for an apparent greater sensitivity to detect regional abnormalities in brains of patients with AD.

Advances in PET Methodology

Recent advances in disease understanding, instrumentation technology, and computationally demanding image analysis approaches are opening new frontiers in the investigation of movement disorders and brain disease in general. A key aspect is the recognition of the need to determine molecular correlates to early functional and metabolic connectivity alterations, which are increasingly recognized as useful signatures of specific clinical disease phenotypes. Such multi-modal approaches are highly likely to provide new information on pathogenic mechanisms and to help the identification of novel therapeutic targets. This chapter describes recent methodological developments in PET starting with a very brief overview of radiotracers relevant to movement disorders while emphasizing the development of instrumentation, algorithms and imaging analysis methods relevant to multi-modal investigation of movement disorders.

Non-invasive kinetic modelling of PET tracers with radiometabolites using a constrained simultaneous estimation method: evaluation with 11C-SB201745

Background

Kinetic analysis of dynamic PET data requires an accurate knowledge of available PET tracer concentration within blood plasma over time, known as the arterial input function (AIF). The gold standard method used to measure the AIF requires serial arterial blood sampling over the course of the PET scan, which is an invasive procedure and makes this method less practical in clinical settings. Traditional image-derived methods are limited to specific tracers and are not accurate if metabolites are present in the plasma.

Results

In this work, we utilise an image-derived whole blood curve measurement to reduce the computational complexity of the simultaneous estimation method (SIME), which is capable of estimating the AIF directly from tissue time activity curves (TACs). This method was applied to data obtained from a serotonin receptor study (¹¹C-SB207145) and estimated parameter results are compared to results obtained using the original SIME and gold standard AIFs derived from arterial samples. Reproducibility of the method was assessed using test-retest data. It was shown that the incorporation of image-derived information increased the accuracy of total volume of distribution (V _T) estimates, averaged across all regions, by 40% and non-displaceable binding potential (BP _ND) estimates by 16% compared to the original SIME. Particular improvements were observed in K₁ parameter estimates. BP _ND estimates, based on the proposed method and the gold standard arterial sample-derived AIF, were not significantly different (P=0.7).

Conclusions

The results of this work indicate that the proposed method with prior AIF information obtained from a partial volume corrected image-derived whole blood curve, and modelled parent fraction, has the potential to be used as an alternative non-invasive method to perform kinetic analysis of tracers with metabolite products.

Brain TSPO imaging and gray matter volume in schizophrenia patients and in people at ultra high risk of psychosis: An [11C]PBR28 study

Patients with schizophrenia show whole brain and cortical gray matter (GM) volume reductions which are progressive early in their illness. Microglia, the resident immune cells in the CNS, phagocytose neurons and synapses. Some post mortem and in vivo studies in schizophrenia show evidence for elevated microglial activation compared to matched controls. However, it is currently unclear how these results relate to changes in cortical structure.

METHODS

Fourteen patients with schizophrenia and 14 ultra high risk for psychosis (UHR) subjects alongside two groups of age and genotype matched healthy controls received [11C]PBR28 PET scans to index TSPO expression, a marker of microglial activation and a 3T MRI scan. We investigated the relationship between the volume changes of cortical regions and microglial activation in cortical GM (as indexed by [11C]PBR28 distribution volume ratio (DVR).

RESULTS

The total cortical GM volume was significantly lower in SCZ than the controls [mean (SD)/cm3: SCZ=448.83 (39.2) and controls=499.6 (59.2) (p=0.02) but not in UHR (mean (SD)=503.06 (57.9) and controls=524.46 (45.3) p=0.3). Regression model fitted the total cortical GM DVR values with the cortical regional volumes in SCZ (r=0.81; p<0.001) and in UHR (r=0.63; p=0.02). We found a significant negative correlation between the TSPO signal and total cortical GM volume in SCZ with the highest absolute correlation coefficient in the right superior-parietal cortex (r=-0.72; p=0.006).

CONCLUSIONS

These findings suggest that microglial activity is related to the altered cortical volume seen in schizophrenia. Longitudinal investigations are required to determine whether microglial activation leads to cortical gray matter loss.

The importance of small polar radiometabolites in molecular neuroimaging: A PET study with [11C]Cimbi-36 labeled in two positions

[11C]Cimbi-36, a 5-HT2A receptor agonist PET radioligand, contains three methoxy groups amenable to [11C]-labeling. In pigs, [11C]Cimbi-36 yields a polar (M1) and a less polar (M2) radiometabolite fraction, while changing the labeling to [11C]Cimbi-36_5 yields only the M1 fraction. We investigate whether changing the labeling position of [11C]Cimbi-36 eliminates M2 in humans, and if this changes the signal-to-background ratio. Six healthy volunteers each underwent two dynamic PET scans; after injection of [11C]Cimbi-36, both the M1 and M2 fraction appeared in plasma, whereas only the M1 appeared after [11C]Cimbi-36_5 injection. [11C]Cimbi-36_5 generated higher uptake than [11C]Cimbi-36 in both neocortex and cerebellum. With the simplified reference tissue model mean neocortical non-displaceable binding potential for [11C]Cimbi-36 was 1.38 ± 0.07, whereas for [11C]Cimbi-36_5, it was 1.18 ± 0.14. This significant difference can be explained by higher non-displaceable binding caused by demethylation products in the M1 fraction such as [11C]formaldehyde and/or [11C]carbon dioxide/bicarbonate. Although often considered without any impact on binding measures, we show that small polar radiometabolites can substantially decrease the signal-to-background ratio of PET radioligands for neuroimaging. Further, we find that [11C]Cimbi-36 has a better signal-to-background ratio than [11C]Cimbi-36_5, and thus will be more sensitive to changes in 5-HT2A receptor levels in the brain.

Molecular imaging of postprandial metabolism

Disordered postprandial metabolism of energy substrates is one of the main defining features of prediabetes and contributes to the development of several chronic diseases associated with obesity, such as type 2 diabetes and cardiovascular diseases. Postprandial energy metabolism has been studied using classical isotopic tracer approaches that are limited by poor access to splanchnic metabolism and highly dynamic and complex exchanges of energy substrates involving multiple organs and systems. Advances in noninvasive molecular imaging modalities, such as PET and MRI/magnetic resonance spectroscopy (MRS), have recently allowed important advances in our understanding of postprandial energy metabolism in humans. The present review describes some of these recent advances, with particular focus on glucose and fatty acid metabolism in the postprandial state, and discusses current gaps in knowledge and new perspectives of application of PET and MRI/MRS for the investigation and treatment of human metabolic diseases.