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BackgroundKinetic modeling of 18F-florbetaben provides important quantification of brain amyloid deposition in research and clinical settings but its use is limited by the requirement of arterial blood data for quantitative PET. The total-body EXPLORER PET scanner supports the dynamic acquisition of a full human body simultaneously and permits noninvasive image-derived input functions (IDIFs) as an alternative to arterial blood sampling. This study quantified brain amyloid burden with kinetic modeling, leveraging dynamic 18F-florbetaben PET in aorta IDIFs and the brain in an elderly cohort.Methods18F-florbetaben dynamic PET imaging was performed on the EXPLORER system with tracer injection (300 MBq) in 3 individuals with Alzheimer's disease (AD), 3 with mild cognitive impairment, and 9 healthy controls. Image-derived input functions were extracted from the descending aorta with manual regions of interest based on the first 30 s after injection. Dynamic time-activity curves (TACs) for 110 min were fitted to the two-tissue compartment model (2TCM) using population-based metabolite corrected IDIFs to calculate total and specific distribution volumes (VT, Vs) in key brain regions with early amyloid accumulation. Non-displaceable binding potential ([Formula: see text] was also calculated from the multi-reference tissue model (MRTM).ResultsAmyloid-positive (AD) patients showed the highest VT and VS in anterior cingulate, posterior cingulate, and precuneus, consistent with [Formula: see text] analysis. [Formula: see text]and VT from kinetic models were correlated (r² = 0.46, P

Abstract Background The purpose of this study was to assess the feasibility of using a minimally invasive simultaneous estimation method (SIME) to quantify the binding of the 18-kDa translocator protein tracer [18F]FEPPA. Arterial sampling was avoided by extracting an image-derived input function (IDIF) that was metabolite-corrected using venous blood samples. The possibility of reducing scan duration to 90 min from the recommended 2–3 h was investigated by assuming a uniform non-displaceable distribution volume (V ND) to simplify the SIME fitting. Results SIME was applied to retrospective data from healthy volunteers and was comprised of both high-affinity binders (HABs) and mixed-affinity binders (MABs). Estimates of global V ND and regional total distribution volume (V T) from SIME were not significantly different from values obtained using a two-tissue compartment model (2CTM). Regional V T estimates were greater for HABs compared to MABs for both the 2TCM and SIME, while the SIME estimates had lower inter-subject variability (41 ± 17% reduction). Binding potential (BPND) values calculated from regional V T and brain-wide V ND estimates were also greater for HABs, and reducing the scan time from 120 to 90 min had no significant effect on BPND. The feasibility of using venous metabolite correction was evaluated in a large animal model involving a simultaneous collection of arterial and venous samples. Strong linear correlations were found between venous and arterial measurements of the blood-to-plasma ratio and the remaining [18F]FEPPA fraction. Lastly, estimates of BPND and the specific distribution volume (i.e., V S = V T − V ND) from a separate group of healthy volunteers (90 min scan time, venous-scaled IDIFs) agreed with estimates from the retrospective data for both genotypes. Conclusions The results of this study demonstrate that accurate estimates of regional V T, BPND and V S can be obtained by applying SIME to [18F]FEPPA data. Furthermore, the application of SIME enabled the scan time to be reduced to 90 min, and the approach worked well with IDIFs that were scaled and metabolite-corrected using venous blood samples.

Abstract Background Antiepileptic drugs, levetiracetam (LEV) and brivaracetam (BRV), bind to synaptic vesicle glycoprotein 2A (SV2A). In their anti-seizure activity, speed of brain entry may be an important factor. BRV showed faster entry into the human and non-human primate brain, based on more rapid displacement of SV2A tracer 11C-UCB-J. To extract additional information from previous human studies, we developed a nonlinear model that accounted for drug entry into the brain and binding to SV2A using brain 11C-UCB-J positron emission tomography (PET) data and the time-varying plasma drug concentration, to assess the kinetic parameter K 1 (brain entry rate) of the drugs. Method Displacement (LEV or BRV p.i. 60 min post-tracer injection) and post-dose scans were conducted in five healthy subjects. Blood samples were collected for measurement of drug concentration and the tracer arterial input function. Fitting of nonlinear differential equations was applied simultaneously to time-activity curves (TACs) from displacement and post-dose scans to estimate 5 parameters: K 1 (drug), K 1(11C-UCB-J, displacement), K 1(11C-UCB-J, post-dose), free fraction of 11C-UCB-J in brain (f ND(11C-UCB-J)), and distribution volume of 11C-UCB-J (V T(UCB-J)). Other parameters (K D(drug), K D(11C-UCB-J), f P(drug), f P(11C-UCB-J, displacement), f P(11C-UCB-J, post-dose), f ND(drug), k off(drug), k off(11C-UCB-J)) were fixed to literature or measured values. Results The proposed model described well the TACs in all subjects; however, estimates of drug K 1 were unstable in comparison with 11C-UCB-J K 1 estimation. To provide a conservative estimate of the relative speed of brain entry for BRV vs. LEV, we determined a lower bound on the ratio BRV K 1/LEV K 1, by finding the lowest BRV K 1 or highest LEV K 1 that were statistically consistent with the data. Specifically, we used the F test to compare the residual sum of squares with fixed BRV K 1 to that with floating BRV K 1 to obtain the lowest possible BRV K 1; the same analysis was performed to find the highest LEV K 1. The lower bound of the ratio BRV K 1/LEV K 1 was ~ 7. Conclusions Under appropriate conditions, this advanced nonlinear model can directly estimate entry rates of drugs into tissue by analysis of PET TACs. Using a conservative statistical cutoff, BRV enters the brain at least sevenfold faster than LEV.

Background: The purpose of this study was to assess the feasibility of using a minimally invasive simultaneous estimation method (SIME) to quantify the binding of the 18-kDa translocator protein tracer [18F]FEPPA. Arterial sampling was avoided by extracting an image-derived input function (IDIF) that was metabolite-corrected using venous blood samples. The possibility of reducing scan duration to 90 min from the recommended 2–3 h was investigated by assuming a uniform non-displaceable distribution volume (VND) to simplify the SIME fitting. Results: SIME was applied to retrospective data from healthy volunteers and was comprised of both high-affinity binders (HABs) and mixed-affinity binders (MABs). Estimates of global VND and regional total distribution volume (VT) from SIME were not significantly different from values obtained using a two-tissue compartment model (2CTM). Regional VT estimates were greater for HABs compared to MABs for both the 2TCM and SIME, while the SIME estimates had lower inter-subject variability (41 ± 17% reduction). Binding potential (BPND) values calculated from regional VT and brain-wide VND estimates were also greater for HABs, and reducing the scan time from 120 to 90 min had no significant effect on BPND. The feasibility of using venous metabolite correction was evaluated in a large animal model involving a simultaneous collection of arterial and venous samples. Strong linear correlations were found between venous and arterial measurements of the blood-to-plasma ratio and the remaining [18F]FEPPA fraction. Lastly, estimates of BPND and the specific distribution volume (i.e., VS = VT − VND) from a separate group of healthy volunteers (90 min scan time, venous-scaled IDIFs) agreed with estimates from the retrospective data for both genotypes. Conclusions: The results of this study demonstrate that accurate estimates of regional VT, BPND and VS can be obtained by applying SIME to [18F]FEPPA data. Furthermore, the application of SIME enabled the scan time to be reduced to 90 min, and the approach worked well with IDIFs that were scaled and metabolite-corrected using venous blood samples. [ABSTRACT FROM AUTHOR]

Background: Antiepileptic drugs, levetiracetam (LEV) and brivaracetam (BRV), bind to synaptic vesicle glycoprotein 2A (SV2A). In their anti-seizure activity, speed of brain entry may be an important factor. BRV showed faster entry into the human and non-human primate brain, based on more rapid displacement of SV2A tracer 11C-UCB-J. To extract additional information from previous human studies, we developed a nonlinear model that accounted for drug entry into the brain and binding to SV2A using brain 11C-UCB-J positron emission tomography (PET) data and the time-varying plasma drug concentration, to assess the kinetic parameter K1 (brain entry rate) of the drugs. Method: Displacement (LEV or BRV p.i. 60 min post-tracer injection) and post-dose scans were conducted in five healthy subjects. Blood samples were collected for measurement of drug concentration and the tracer arterial input function. Fitting of nonlinear differential equations was applied simultaneously to time-activity curves (TACs) from displacement and post-dose scans to estimate 5 parameters: K1 (drug), K1(11C-UCB-J, displacement), K1(11C-UCB-J, post-dose), free fraction of 11C-UCB-J in brain (fND(11C-UCB-J)), and distribution volume of 11C-UCB-J (VT(UCB-J)). Other parameters (KD(drug), KD(11C-UCB-J), fP(drug), fP(11C-UCB-J, displacement), fP(11C-UCB-J, post-dose), fND(drug), koff(drug), koff(11C-UCB-J)) were fixed to literature or measured values. Results: The proposed model described well the TACs in all subjects; however, estimates of drug K1 were unstable in comparison with 11C-UCB-J K1 estimation. To provide a conservative estimate of the relative speed of brain entry for BRV vs. LEV, we determined a lower bound on the ratio BRV K1/LEV K1, by finding the lowest BRV K1 or highest LEV K1 that were statistically consistent with the data. Specifically, we used the F test to compare the residual sum of squares with fixed BRV K1 to that with floating BRV K1 to obtain the lowest possible BRV K1; the same analysis was performed to find the highest LEV K1. The lower bound of the ratio BRV K1/LEV K1 was ~ 7. Conclusions: Under appropriate conditions, this advanced nonlinear model can directly estimate entry rates of drugs into tissue by analysis of PET TACs. Using a conservative statistical cutoff, BRV enters the brain at least sevenfold faster than LEV. [ABSTRACT FROM AUTHOR]

Abstract 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 K 1 and k 3 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 Ki 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.

Abstract Background [11C]-acetate positron emission tomography is used to assess oxidative metabolism in various tissues including the heart, tumor, and brown adipose tissue. For brown adipose tissue, a monoexponential decay model is commonly employed. However, no systematic assessment of kinetic models has been performed to validate this model or others. The monoexponential decay model and various compartmental models were applied to data obtained before and during brown adipose tissue activation by cold exposure in healthy men. Quality of fit was assessed visually and by analysis of residuals, including the Akaike information criterion. Stability and accuracy of compartmental models were further assessed through simulations, along with sensitivity and identifiability of kinetic parameters. Results Differences were noted in the arterial input function between the warm and cold conditions. These differences are not taken into account by the monoexponential decay model. They are accounted for by compartmental models, but most models proved too complex to be stable. Two and three-tissue models with no more than four distinct kinetic parameters, including blood volume fraction, provided the best compromise between fit quality and stability/accuracy. Conclusion For healthy men, a three-tissue model with four kinetic parameters, similar to a heart [11C]-palmitate model seems the most appropriate based on model stability and its ability to describe the main [11C]-acetate pathways in BAT cells. Further studies are required to validate this model in women and people with metabolic disorders.

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 Ki were all significantly higher in lesions compared to normal tissue (p < 0.05). Ki derived using image-derived blood from an MR-guided method showed excellent agreement with Ki derived using arterial blood sampling (intraclass correlation coefficient = 0.99). SUV correlated significantly with Ki with the strongest correlation of scan time-window 30–45 min (rho 0.95, p < 0.001). Both Ki 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 Ki and can be used in routine clinical settings to quantify 68Ga-PSMA-11 uptake. [ABSTRACT FROM AUTHOR]

Abstract Background Reference tissue-based quantification of brain PET data does not typically include correction for signal originating from blood vessels, which is known to result in biased outcome measures. The bias extent depends on the amount of radioactivity in the blood vessels. In this study, we seek to revisit the well-established Logan plot and derive alternative formulations that provide estimation of distribution volume ratios (DVRs) that are corrected for the signal originating from the vasculature. Results New expressions for the Logan plot based on arterial input function and reference tissue were derived, which included explicit terms for whole blood radioactivity. The new methods were evaluated using PET data acquired using [11C]raclopride and [18F]MNI-659. The two-tissue compartment model (2TCM), with which signal originating from blood can be explicitly modeled, was used as a gold standard. DVR values obtained for [11C]raclopride using the either blood-based or reference tissue-based Logan plot were systematically underestimated compared to 2TCM, and for [18F]MNI-659, a proportionality bias was observed, i.e., the bias varied across regions. The biases disappeared when optimal blood-signal correction was used for respective tracer, although for the case of [18F]MNI-659 a small but systematic overestimation of DVR was still observed. Conclusions The new method appears to remove the bias introduced due to absence of correction for blood volume in regular graphical analysis and can be considered in clinical studies. Further studies are however required to derive a generic mapping between plasma and whole-blood radioactivity levels.

Background: Reference tissue-based quantification of brain PET data does not typically include correction for signal originating from blood vessels, which is known to result in biased outcome measures. The bias extent depends on the amount of radioactivity in the blood vessels. In this study, we seek to revisit the well-established Logan plot and derive alternative formulations that provide estimation of distribution volume ratios (DVRs) that are corrected for the signal originating from the vasculature. Results: New expressions for the Logan plot based on arterial input function and reference tissue were derived, which included explicit terms for whole blood radioactivity. The new methods were evaluated using PET data acquired using [C]raclopride and [F]MNI-659. The two-tissue compartment model (2TCM), with which signal originating from blood can be explicitly modeled, was used as a gold standard. DVR values obtained for [C]raclopride using the either blood-based or reference tissue-based Logan plot were systematically underestimated compared to 2TCM, and for [F]MNI-659, a proportionality bias was observed, i.e., the bias varied across regions. The biases disappeared when optimal blood-signal correction was used for respective tracer, although for the case of [F]MNI-659 a small but systematic overestimation of DVR was still observed. Conclusions: The new method appears to remove the bias introduced due to absence of correction for blood volume in regular graphical analysis and can be considered in clinical studies. Further studies are however required to derive a generic mapping between plasma and whole-blood radioactivity levels. [ABSTRACT FROM AUTHOR]

Background: The pathogenesis and immune response to Middle East respiratory syndrome (MERS) caused by a recently discovered coronavirus, MERS-CoV, have not been fully characterized because a suitable animal model is currently not available. 18F-Fluorodeoxyglucose ([18F]-FDG)-positron emission tomography/computed tomography (PET/CT) as a longitudinal noninvasive approach can be beneficial in providing biomarkers for host immune response. [18F]-FDG uptake is increased in activated immune cells in response to virus entry and can be localized by PET imaging. We used [18F]-FDG-PET/CT to investigate the host response developing in nonhuman primates after MERS-CoV exposure and applied kinetic modeling to monitor the influx rate constant (Ki) in responsive lymphoid tissue. Methods: Multiple [18F]-FDG-PET and CT images were acquired on a PET/CT clinical scanner modified to operate in a biosafety level 4 environment prior to and up to 29 days after MERS-CoV aerosol exposure. Time activity curves of various lymphoid tissues were reconstructed to follow the [18F]-FDG uptake for approximately 60 min (3,600 s). Image-derived input function was used to calculate Ki for lymphoid tissues by Patlak plot. Results: Two-way repeated measures analysis of variance revealed alterations in Ki that was associated with the time point (p < 0.001) after virus exposure and the location of lymphoid tissue (p = 0.0004). As revealed by a statistically significant interaction (p < 0.0001) between these two factors, the pattern of Ki changes over time differed between three locations but not between subjects. A distinguished pattern of statistically significant elevation in Ki was observed in mediastinal lymph nodes (LNs) that correlated to Ki changes in axillary LNs. Changes in LNs Ki were concurrent with elevations of monocytes in peripheral blood. Conclusions: [18F]-FDG-PET is able to detect subtle changes in host immune response to contain a subclinical virus infection. Full quantitative analysis is the preferred approach rather than semiquantitative analysis using standardized uptake value for detection of the immune response to the virus. [ABSTRACT FROM AUTHOR]

Background: The pathogenesis and immune response to Middle East respiratory syndrome (MERS) caused by a recently discovered coronavirus, MERS-CoV, have not been fully characterized because a suitable animal model is currently not available. F-Fluorodeoxyglucose ([F]-FDG)-positron emission tomography/computed tomography (PET/CT) as a longitudinal noninvasive approach can be beneficial in providing biomarkers for host immune response. [F]-FDG uptake is increased in activated immune cells in response to virus entry and can be localized by PET imaging. We used [F]-FDG-PET/CT to investigate the host response developing in nonhuman primates after MERS-CoV exposure and applied kinetic modeling to monitor the influx rate constant ( K) in responsive lymphoid tissue . Methods: Multiple [F]-FDG-PET and CT images were acquired on a PET/CT clinical scanner modified to operate in a biosafety level 4 environment prior to and up to 29 days after MERS-CoV aerosol exposure. Time activity curves of various lymphoid tissues were reconstructed to follow the [F]-FDG uptake for approximately 60 min (3,600 s). Image-derived input function was used to calculate K for lymphoid tissues by Patlak plot. Results: Two-way repeated measures analysis of variance revealed alterations in K that was associated with the time point ( p < 0.001) after virus exposure and the location of lymphoid tissue ( p = 0.0004). As revealed by a statistically significant interaction ( p < 0.0001) between these two factors, the pattern of K changes over time differed between three locations but not between subjects. A distinguished pattern of statistically significant elevation in K was observed in mediastinal lymph nodes (LNs) that correlated to K changes in axillary LNs. Changes in LNs K were concurrent with elevations of monocytes in peripheral blood. Conclusions: [F]-FDG-PET is able to detect subtle changes in host immune response to contain a subclinical virus infection. Full quantitative analysis is the preferred approach rather than semiquantitative analysis using standardized uptake value for detection of the immune response to the virus. [ABSTRACT FROM AUTHOR]

Background: Recently, we reported an information density theory and an analysis of three-parameter plus shorter scan than conventional method (3P+) for the amyloid-binding ligand [ 11C]Pittsburgh compound B (PIB) as an example of a non-highly reversible positron emission tomography (PET) ligand. This article describes an extension of 3P + analysis to noninvasive ‘3P++’ analysis (3P + plus use of a reference tissue for input function). Methods: In 3P++ analysis for [ 11C]PIB, the cerebellum was used as a reference tissue (negligible specific binding). Fifteen healthy subjects (NC) and fifteen Alzheimer's disease (AD) patients participated. The k3 (index of receptor density) values were estimated with 40-min PET data and three-parameter reference tissue model and were compared with that in 40-min 3P + analysis as well as standard 90-min four-parameter (4P) analysis with arterial input function. Simulation studies were performed to explain k3 biases observed in 3P++ analysis. Results: Good model fits of 40-min PET data were observed in both reference and target regions-of-interest (ROIs). High linear intra-subject (inter-15 ROI) correlations of k3 between 3P++ ( Y-axis) and 3P + ( X-axis) analyses were shown in one NC ( r2 = 0.972 and slope = 0.845) and in one AD ( r2 = 0.982, slope = 0.655), whereas inter-subject k3 correlations in a target region (left lateral temporal cortex) from 30 subjects (15 NC + 15 AD) were somewhat lower ( r2 = 0.739 and slope = 0.461). Similar results were shown between 3P++ and 4P analyses: r2 = 0.953 for intra-subject k3 in NC, r2 = 0.907 for that in AD and r2 = 0.711 for inter-30 subject k3. Simulation studies showed that such lower inter-subject k3 correlations and significant negative k3 biases were not due to unstableness of 3P++ analysis but rather to inter-subject variation of both k2 (index of brain-to-blood transport) and k3 (not completely negligible) in the reference region. Conclusions: In [ 11C]PIB, the applicability of 3P++ analysis may be restricted to intra-subject comparison such as follow-up studies. The 3P++ method itself is thought to be robust and may be more applicable to other non-highly reversible PET ligands with ideal reference tissue. [ABSTRACT FROM AUTHOR]

Background: [11C]-acetate positron emission tomography is used to assess oxidative metabolism in various tissues including the heart, tumor, and brown adipose tissue. For brown adipose tissue, a monoexponential decay model is commonly employed. However, no systematic assessment of kinetic models has been performed to validate this model or others. The monoexponential decay model and various compartmental models were applied to data obtained before and during brown adipose tissue activation by cold exposure in healthy men. Quality of fit was assessed visually and by analysis of residuals, including the Akaike information criterion. Stability and accuracy of compartmental models were further assessed through simulations, along with sensitivity and identifiability of kinetic parameters. Results: Differences were noted in the arterial input function between the warm and cold conditions. These differences are not taken into account by the monoexponential decay model. They are accounted for by compartmental models, but most models proved too complex to be stable. Two and three-tissue models with no more than four distinct kinetic parameters, including blood volume fraction, provided the best compromise between fit quality and stability/accuracy. Conclusion: For healthy men, a three-tissue model with four kinetic parameters, similar to a heart [11C]-palmitate model seems the most appropriate based on model stability and its ability to describe the main [11C]-acetate pathways in BAT cells. Further studies are required to validate this model in women and people with metabolic disorders. [ABSTRACT FROM AUTHOR]