Model selection criteria for dynamic brain PET studies

Kinetic Modeling Methods in Preclinical Positron Emission Tomography Imaging

There is an expanding number of applications for preclinical positron emission tomography (PET) imaging. Kinetic modeling of PET data provides rich multiparameter information on radiotracer uptake and binding in tissue from a single experiment. In this chapter, we provide a practical step-by-step protocol to assist with collection of PET data for kinetic modeling studies in rats and mice.

Evaluation of [18F]PF-06455943 as a Potential LRRK2 PET Imaging Agent in the Brain of Nonhuman Primates

Mutations in the leucine-rich repeat kinase 2 (LRRK2) gene are the common causes of inherited Parkinson's disease (PD) and emerged as a causative PD gene. Particularly, LRRK2-Gly2019Ser mutation was reported to alter the early phase of neuronal differentiation, increasing cell death. Selective inhibitors of LRRK2 kinase activity were considered as a promising therapeutic target for PD treatment. However, the development of effective brain-penetrant LRRK2 inhibitors remains challenging. Recently, we have developed a novel positron emission tomography (PET) radioligand for LRRK2 imaging and demonstrated preferable tracer properties in rodents. Herein, we evaluate [18F]PF-06455943 quantification methods in the nonhuman primate (NHP) brain using full kinetic modeling with radiometabolite-corrected arterial blood samples, and homologous blocking with two doses (0.1 and 0.3 mg/kg). Kinetic analysis results demonstrated that a two-tissue compartmental model and a Logan graphical analysis are appropriate for [18F]PF-06455943 PET quantification. In addition, we observed that total distribution volume (VT) values can be reliably estimated with as short as a 30 min scan duration. Homologous blocking studies confirmed the specific binding of [18F]PF-06455943 and revealed that the nonradioactive mass of PF-06455943 achieved 45-55% of VT displacement in the whole brain. This work supports the translation of [18F]PF-06455943 PET imaging for the human brain and target occupancy studies.

Regional Characterization of the Gottingen Minipig Brain by [18 F]FDG Dynamic Pet Modeling

Purpose

To determine the best kinetic model to be applied on dynamic brain [18 F]FDG PET images by characterizing the regional brain glucose metabolism of normal Göttingen minipigs.

Methods

Nine Göttingen minipigs were scanned with a clinical PET/CT tomograph, starting from the injection of an intravenous bolus of [18 F]FDG, for about 25 min. Dynamic images were reconstructed and nine brain regions of interest (ROI), plus a vascular region, were defined and time-activity curves (TAC) were determined.

Three kinetic models were considered for fitting with experimental TACs: one-tissue compartment model 1TC, two-tissue irreversible compartment model 2TCi and two-tissue reversible model 2TC. Akaike Information Criterion was considered to evaluate the goodness of each model fitting. Regional and global kinetic parameter values were evaluated, in addition to the partition coefficient, net influx rate and retention index (RI).

Results

Both 2TCi and 2TC models turned out to be good choices for the next analysis. Parameter values were very similar between the different brain regions, with similar values to when the brain as a whole is considered (kinetic parameters mean values, from 2TCi model: K1 = 1.0 ml/g/min, k2 = 0.49 min− 1, k3 = 0.034 min− 1, K1/k2 = 2.14ml/g, Ki =0.069 ml/g/min; from 2TC model: K1 = 1.10 ml/g/min, k2 = 0.54 min− 1, k3 = 0.058 min− 1, k4 = 0.039 min− 1, K1/k2 = 2.18 ml/g, Ki = 0.10 ml/g/min; RI mean ± sd: 0.147 ± 0.037 min− 1), with the exception of the cerebellum (mean values from the 2TCi model: K1 = 0.52 ml/g/min, k2 = 0.56 min− 1, k3 = 0.025 min− 1, K1/k2 = 0.98ml/g, Ki=0.022 ml/g/min; from 2TC model: K1 = 0.54 ml/g/min, k2 = 0.61 min− 1, k3 = 0.044 min− 1, k4 = 0.038 min− 1, K1/k2 = 0.95ml/g, Ki=0.032 ml/g/min; RI mean ± sd: 0.071 ± 0.018 min− 1).

Conclusion

The two-tissue model is able to describe the regional brain metabolism in Göttingen minipigs. Compared to the 2TCi model, in the 2TC model the k4 micro-parameter was also evaluated. This led to adjustments of the other microparameters, especially k3 and consequently the net influx rate Ki. For healthy minipigs, the glucose metabolism was similar in all of the brain regions analyzed, with the exception of the cerebellum, where the FDG uptake was lower.

Non-invasive quantification of acute macrophagic lung inflammation with [11C](R)-PK11195 using a three-tissue compartment kinetic model in experimental acute respiratory distress syndrome

PURPOSE

Imaging of acute lung inflammation is pivotal to evaluate innovative ventilation strategies. We aimed to develop and validate a three-tissue compartment kinetic model (3TCM) of [¹¹C](R)-PK11195 lung uptake in experimental acute respiratory distress syndrome (ARDS) to help quantify macrophagic inflammation, while accounting for the impact of its non-specific and irreversible uptake in lung tissues.

MATERIAL AND METHODS

We analyzed the data of 38 positron emission tomography (PET) studies performed in 21 swine with or without experimental ARDS, receiving general anesthesia and mechanical ventilation. Model input function was a plasma, metabolite-corrected, image-derived input function measured in the main pulmonary artery. Regional lung analysis consisted in applying both the 3TCM and the two-tissue compartment model (2TCM); in each region, the best model was selected using a selection algorithm with a goodness-of-fit criterion. Regional best model binding potentials (BP_ND) were compared to lung macrophage presence, semi-quantified in pathology.

RESULTS

The 3TCM was preferred in 142 lung regions (62%, 95% confidence interval: 56 to 69%). BP_ND determined by the 2TCM was significantly higher than the value computed with the 3TCM (overall median with interquartile range: 0.81 [0.44-1.33] vs. 0.60 [0.34-0.94], p < 0.02). Regional macrophage score was significantly associated with the best model BP_ND (p = 0.03). Regional BP_ND was significantly increased in the hyperinflated lung compartment, compared to the normally aerated one (median with interquartile range: 0.8 [0.6-1.7] vs. 0.6 [0.3-0.8], p = 0.03).

CONCLUSION

To assess the intensity and spatial distribution of acute macrophagic lung inflammation in the context of experimental ARDS with mechanical ventilation, PET quantification of [¹¹C](R)-PK11195 lung uptake was significantly improved in most lung regions using the 3TCM. This new methodology offers the opportunity to non-invasively evaluate innovative ventilatory strategies aiming at controlling acute lung inflammation.

[11C]deschloroclozapine is an improved PET radioligand for quantifying a human muscarinic DREADD expressed in monkey brain

Previous work found that [¹¹C]deschloroclozapine ([¹¹C]DCZ) is superior to [¹¹C]clozapine ([¹¹C]CLZ) for imaging Designer Receptors Exclusively Activated by Designer Drugs (DREADDs). This study used PET to quantitatively and separately measure the signal from transfected receptors, endogenous receptors/targets, and non-displaceable binding in other brain regions to better understand this superiority. A genetically-modified muscarinic type-4 human receptor (hM₄Di) was injected into the right amygdala of a male rhesus macaque. [¹¹C]DCZ and [¹¹C]CLZ PET scans were conducted 2-24 months later. Uptake was quantified relative to the concentration of parent radioligand in arterial plasma at baseline (n = 3 scans/radioligand) and after receptor blockade (n = 3 scans/radioligand). Both radioligands had greater uptake in the transfected region and displaceable uptake in other brain regions. Displaceable uptake was not uniformly distributed, perhaps representing off-target binding to endogenous receptor(s). After correction, [¹¹C]DCZ signal was 19% of that for [¹¹C]CLZ, and background uptake was 10% of that for [¹¹C]CLZ. Despite stronger [¹¹C]CLZ binding, the signal-to-background ratio for [¹¹C]DCZ was almost two-fold greater than for [¹¹C]CLZ. Both radioligands had comparable DREADD selectivity. All reference tissue models underestimated signal-to-background ratio in the transfected region by 40%-50% for both radioligands. Thus, the greater signal-to-background ratio of [¹¹C]DCZ was due to its lower background uptake.

Total-Body PET Kinetic Modeling and Potential Opportunities Using Deep Learning

The uEXPLORER total-body PET/CT system provides a very high level of detection sensitivity and simultaneous coverage of the entire body for dynamic imaging for quantification of tracer kinetics. This article describes the fundamentals and potential benefits of total-body kinetic modeling and parametric imaging focusing on the noninvasive derivation of blood input function, multiparametric imaging, and high-temporal resolution kinetic modeling. Along with its attractive properties, total-body kinetic modeling also brings significant challenges, such as the large scale of total-body dynamic PET data, the need for organ and tissue appropriate input functions and kinetic models, and total-body motion correction. These challenges, and the opportunities using deep learning, are discussed.

Dynamic 18F-FDG PET imaging of liver lesions: evaluation of a two-tissue compartment model with dual blood input function

Background

Dynamic PET with kinetic modeling was reported to be potentially helpful in the assessment of hepatic malignancy. In this study, a kinetic modeling analysis was performed on hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) from dynamic FDG positron emission tomography/computer tomography (PET/CT) scans.

Methods

A reversible two-tissue compartment model with dual blood input function, which takes into consideration the blood supply from both hepatic artery and portal vein, was used for accurate kinetic modeling of liver dynamic ¹⁸F-FDG PET imaging. The blood input functions were directly measured as the mean values over the VOIs on descending aorta and portal vein respectively. And the contribution of hepatic artery to the blood input function was optimization-derived in the process of model fitting. The kinetic model was evaluated using dynamic PET data acquired on 24 patients with identified hepatobiliary malignancy. 38 HCC or ICC identified lesions and 24 healthy liver regions were analyzed.

Results

Results showed significant differences in kinetic parameters \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${K}_{1}-{k}_{4}$$\end{document}K1-k4, blood supplying fraction \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${f}_{A}$$\end{document}fA, and metabolic rate constant \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${K}_{i}$$\end{document}Ki between malignant lesions and healthy liver tissue. And significant differences were also observed in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${K}_{1}$$\end{document}K1, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${k}_{3}$$\end{document}k3, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${f}_{A}$$\end{document}fA and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${K}_{i}$$\end{document}Ki between HCC and ICC lesions. Further investigations of the effect of SUV measurements on the derived kinetic parameters were conducted. And results showed comparable effectiveness of the kinetic modeling using either SUVmean or SUVmax measurements.

Conclusions

Dynamic 18F-FDG PET imaging with optimization-derived hepatic artery blood supply fraction dual-blood input function kinetic modeling can effectively distinguish malignant lesions from healthy liver tissue, as well as HCC and ICC lesions.

GABAA Receptors in the Mongolian Gerbil: a PET Study Using [18F]Flumazenil to Determine Receptor Binding in Young and Old Animals

PURPOSE

Plastic changes in the central auditory system involving the GABAergic system accompany age-related hearing loss. Such processes can be investigated with positron emission tomography (PET) imaging using [¹⁸F]flumazenil ([¹⁸F]FMZ). Here, [¹⁸F]FMZ PET-based modeling approaches allow a simple and reliable quantification of GABA_A receptor binding capacity revealing regional differences and age-related changes.

PROCEDURES

Sixty-minute list-mode PET acquisitions were performed in 9 young (range 5-6 months) and 11 old (range 39-42 months) gerbils, starting simultaneously with the injection of [¹⁸F]FMZ via femoral vein. Non-displaceable binding potentials (BPnd) with pons as reference region were calculated for auditory cortex (AC), inferior colliculus (IC), medial geniculate body (MGB), somatosensory cortex (SC), and cerebellum (CB) using (i) a two-tissue compartment model (2TCM), (ii) the Logan plot with image-derived blood-input (Logan (BI)), (iii) a simplified reference tissue model (SRTM), and (iv) the Logan reference model (Logan (RT)). Statistical parametric mapping analysis (SPM) comparing young and old gerbils was performed using 3D parametric images for BPnd based on SRTM. Results were verified with in vitro autoradiography from five additional young gerbils. Model assessment included the Akaike information criterion (AIC). Hearing was evaluated using auditory brainstem responses.

RESULTS

BPnd differed significantly between models (p < 0.0005), showing the smallest mean difference between 2TCM as reference and SRTM as simplified procedure. SRTM revealed the lowest AIC values. Both volume of distribution (r² = 0.8793, p = 0.018) and BPnd (r² = 0.8216, p = 0.034) correlated with in vitro autoradiography data. A significant age-related decrease of receptor binding was observed in auditory (AC, IC, MGB) and other brain regions (SC and CB) (p < 0.0001, unpaired t test) being confirmed by SPM using pons as reference (p < 0.0001, uncorrected).

CONCLUSION

Imaging of GABA_A receptor binding capacity in gerbils using [¹⁸F]FMZ PET revealed SRTM as a simple and robust quantification method of GABA_A receptors. Comparison of BPnd in young and old gerbils demonstrated an age-related decrease of GABA_A receptor binding.

First-in-human neuroimaging of soluble epoxide hydrolase using [18F]FNDP PET

PURPOSE

Soluble epoxide hydrolase (sEH) is an enzyme with putative effect on neuroinflammation through its influence on the homeostasis of polyunsaturated fatty acids and related byproducts. sEH is an enzyme that metabolizes anti-inflammatory epoxy fatty acids to the corresponding, relatively inert 1,2-diols. A high availability or activity of sEH promotes vasoconstriction and inflammation in local tissues that may be linked to neuropsychiatric diseases. We developed [¹⁸F]FNDP to study sEH in vivo with positron emission tomography (PET).

METHODS

Brain PET using bolus injection of [¹⁸F]FNDP followed by emission imaging lasting 90 or 180 min was completed in healthy adults (5 males, 2 females, ages 40-53 years). The kinetic behavior of [¹⁸F]FNDP was evaluated using a radiometabolite-corrected arterial plasma input function with compartmental or graphical modeling approaches.

RESULTS

[¹⁸F]FNDP PET was without adverse effects. Akaike information criterion favored the two-tissue compartment model (2TCM) in all ten regions of interest. Regional total distribution volume (V_T) values from each compartmental model and Logan analysis were generally well identified except for corpus callosum V_T using the 2TCM. Logan analysis was assessed as the choice model due to stability of regional V_T values from 90-min data and due to high correlation of Logan-derived regional V_T values with those from the 2TCM. [¹⁸F]FNDP binding was higher in human cerebellar cortex and thalamus relative to supratentorial cortical regions, which aligns with reported expression patterns of the epoxide hydrolase 2 gene in human brain.

CONCLUSION

These data support further use of [¹⁸F]FNDP PET to study sEH in human brain.

Short- and long-term memory of moving amoeboid cells

Amoeboid cells constantly change shape and extend protrusions. The direction of movement is not random, but is correlated with the direction of movement in the preceding minutes. The basis of this correlation is an underlying memory of direction. The presence of memory in movement is known for many decades, but its molecular mechanism is still largely unknown. This study reports in detail on the information content of directional memory, the kinetics of learning and forgetting this information, and the molecular basis for memory using Dictyostelium mutants. Two types of memory were characterized. A short-term memory stores for ~20 seconds the position of the last pseudopod using a local modification of the branched F-actin inducer SCAR/WAVE, which enhances one new pseudopod to be formed at the position of the previous pseudopod. A long term memory stores for ~2 minutes the activity of the last ~10 pseudopods using a cGMP-binding protein that induces myosin filaments in the rear of the cell; this inhibits pseudopods in the rear and thereby enhances pseudopods in the global front. Similar types of memory were identified in human neutrophils and mesenchymal stem cells, the protist Dictyostelium and the fungus B.d. chytrid. The synergy of short- and long-term memory explains their role in persistent movement for enhanced cell dispersal, food seeking and chemotaxis.

A methodological investigation of healthy tissue, hepatocellular carcinoma, and other lesions with dynamic 68Ga-FAPI-04 PET/CT imaging

Background

The study aimed to establish a ⁶⁸Ga-FAPI-04 kinetic model in hepatic lesions, to determine the potential role of kinetic parameters in the differentiation of hepatocellular carcinoma (HCC) from non-HCC lesions.

Material and methods

Time activity curves (TACs) were extracted from seven HCC lesions and five non-HCC lesions obtained from ⁶⁸Ga-FAPI-04 dynamic positron emission tomography (PET) scans of eight patients. Three kinetic models were applied to the TACs, using image-derived hepatic artery and/or portal vein as input functions. The maximum standardized uptake value (SUV_max) was taken for the lesions, the hepatic artery, and for the portal veins—the mean SUV for all healthy regions. The optimum model was chosen after applying the Schwartz information criteria to the TACs, differences in model parameters between HCC, non-HCC lesions, and healthy tissue were evaluated with the ANOVA test.

Results

A reversible two-tissue compartment model using both the arterial as well as venous input function was most preferred and showed significant differences in the kinetic parameters V_ND, V_T, and BP_ND between HCC, non-HCC lesions, and healthy regions (p < 0.01).

Conclusion

Several model parameters derived from a two-tissue compartment kinetic model with two image-derived input function from vein and aorta and using SUV_max allow a differentiation between HCC and non-HCC lesions, obtained from dynamically performed PET scans using FAPI.

Unified control of amoeboid pseudopod extension in multiple organisms by branched F-actin in the front and parallel F-actin/myosin in the cortex

The trajectory of moving eukaryotic cells depends on the kinetics and direction of extending pseudopods. The direction of pseudopods has been well studied to unravel mechanisms for chemotaxis, wound healing and inflammation. However, the kinetics of pseudopod extension-when and why do pseudopods start and stop- is equally important, but is largely unknown. Here the START and STOP of about 4000 pseudopods was determined in four different species, at four conditions and in nine mutants (fast amoeboids Dictyostelium and neutrophils, slow mesenchymal stem cells, and fungus B.d. chytrid with pseudopod and a flagellum). The START of a first pseudopod is a random event with a probability that is species-specific (23%/s for neutrophils). In all species and conditions, the START of a second pseudopod is strongly inhibited by the extending first pseudopod, which depends on parallel filamentous actin/myosin in the cell cortex. Pseudopods extend at a constant rate by polymerization of branched F-actin at the pseudopod tip, which requires the Scar complex. The STOP of pseudopod extension is induced by multiple inhibitory processes that evolve during pseudopod extension and mainly depend on the increasing size of the pseudopod. Surprisingly, no differences in pseudopod kinetics are detectable between polarized, unpolarized or chemotactic cells, and also not between different species except for small differences in numerical values. This suggests that the analysis has uncovered the fundament of cell movement with distinct roles for stimulatory branched F-actin in the protrusion and inhibitory parallel F-actin in the contractile cortex.

Kinetic modeling of 68Ga-PSMA-11 and validation of simplified methods for quantification in primary prostate cancer patients

BACKGROUND

The positron emission tomography (PET) ligand ⁶⁸Ga-Glu-urea-Lys(Ahx)-HBED-CC (⁶⁸Ga-PSMA-11) targets the prostate-specific membrane antigen (PSMA), upregulated in prostate cancer cells. Although ⁶⁸Ga-PSMA-11 PET is widely used in research and clinical practice, full kinetic modeling has not yet been reported nor have simplified methods for quantification been validated. The aims of our study were to quantify ⁶⁸Ga-PSMA-11 uptake in primary prostate cancer patients using compartmental modeling with arterial blood sampling and to validate the use of standardized uptake values (SUV) and image-derived blood for quantification.

RESULTS

Fifteen patients with histologically proven primary prostate cancer underwent a 60-min dynamic ⁶⁸Ga-PSMA-11 PET scan of the pelvis with axial T1 Dixon, T2, and diffusion-weighted magnetic resonance (MR) images acquired simultaneously. Time-activity curves were derived from volumes of interest in lesions, normal prostate, and muscle, and mean SUV calculated. In total, 18 positive lesions were identified on both PET and MR. Arterial blood activity was measured by automatic arterial blood sampling and manual blood samples were collected for plasma-to-blood ratio correction and for metabolite analysis. The analysis showed that ⁶⁸Ga-PSMA-11 was stable in vivo. Based on the Akaike information criterion, ⁶⁸Ga-PSMA-11 kinetics were best described by an irreversible two-tissue compartment model. The rate constants K₁ and k₃ and the net influx rate constants K_i were all significantly higher in lesions compared to normal tissue (p < 0.05). K_i derived using image-derived blood from an MR-guided method showed excellent agreement with K_i derived using arterial blood sampling (intraclass correlation coefficient = 0.99). SUV correlated significantly with K_i with the strongest correlation of scan time-window 30-45 min (rho 0.95, p < 0.001). Both K_i and SUV correlated significantly with serum prostate specific antigen (PSA) level and PSA density.

CONCLUSIONS

⁶⁸Ga-PSMA-11 kinetics can be described by an irreversible two-tissue compartment model. An MR-guided method for image-derived blood provides a non-invasive alternative to blood sampling for kinetic modeling studies. SUV showed strong correlation with K_i and can be used in routine clinical settings to quantify ⁶⁸Ga-PSMA-11 uptake.