One-tissue compartment model for myocardial perfusion quantification with N-13 ammonia PET provides matching results: A cross-comparison between Carimas, FlowQuant, and PMOD

Purpose To cross-compare three software packages (SPs)—Carimas, FlowQuant, and PMOD—to quantify myocardial perfusion at global, regional, and segmental levels. Materials and Methods Stress N-13 ammonia PET scans of 48 patients with HCM were analyzed in three centers using Carimas, FlowQuant, and PMOD. Values agreed if they had an ICC > 0.75 and a difference < 20% of the median across all observers. Results When using 1TCM on the global level, the agreement was good, and the maximum difference between 1TCM MBF values was 17.2% (ICC = 0.83). On the regional level, the agreement was acceptable except in the LCx region (25.5% difference, ICC = 0.74) between FlowQuant and PMOD. Carimas-1TCM agreed well with PMOD-1TCM and FlowQuant-1TCM. Values obtained with FlowQuant-1TCM had a somewhat lesser agreement with PMOD-1TCM, especially at the segmental level. Conclusions The global and regional MBF values (with one exception) agree well between the different software packages. There is significant variability in segmental values, mainly located in the LCx region and segments. Out of the studied tools, Carimas can be used interchangeably with both PMOD and FlowQuant for 1TCM implementation on all levels—global, regional, and segmental.

Estimation of renal perfusion based on measurement of rubidium-82 clearance by PET/CT scanning in healthy subjects

Background Changes in renal blood flow (RBF) may play a pathophysiological role in hypertension and kidney disease. However, RBF determination in humans has proven difficult. We aimed to confirm the feasibility of RBF estimation based on positron emission tomography/computed tomography (PET/CT) and rubidium-82 (82Rb) using the abdominal aorta as input function in a 1-tissue compartment model. Methods Eighteen healthy subjects underwent two dynamic 82Rb PET/CT scans in two different fields of view (FOV). FOV-A included the left ventricular blood pool (LVBP), the abdominal aorta (AA) and the majority of the kidneys. FOV-B included AA and the kidneys in their entirety. In FOV-A, an input function was derived from LVBP and from AA, in FOV-B from AA. One-tissue compartmental modelling was performed using tissue time activity curves generated from volumes of interest (VOI) contouring the kidneys, where the renal clearance of 82Rb is represented by the K1 kinetic parameter. Total clearance for both kidneys was calculated by multiplying the K1 values with the volume of VOIs used for analysis. Intra-assay coefficients of variation and inter-observer variation were calculated. Results For both kidneys, K1 values derived from AA did not differ significantly from values obtained from LVBP, neither were significant differences seen between AA in FOV-A and AA in FOV-B, nor between the right and left kidneys. For both kidneys, the intra-assay coefficients of variation were low (~ 5%) for both input functions. The measured K1 of 2.80 ml/min/cm3 translates to a total clearance for both kidneys of 766 ml/min/1.73 m2. Conclusion Measurement of renal perfusion based on PET/CT and 82Rb using AA as input function in a 1-tissue compartment model is feasible in a single FOV. Based on previous studies showing 82Rb to be primarily present in plasma, the measured K1 clearance values are most likely representative of effective renal plasma flow (ERPF) rather than estimated RBF values, but as the accurate calculation of total clearance/flow is very much dependent on the analysed volume, a standardised definition for the employed renal volumes is needed to allow for proper comparison with standard ERPF and RBF reference methods.

Estimation of renal perfusion based on measurement of Rubidium-82 clearance by PET/CT scanning in healthy subjects

Background: Changes in renal blood flow (RBF) may play a pathophysiological role in hypertension and kidney disease. However, RBF determination in humans has proven difficult. We aimed to confirm the feasibility of RBF estimation based on positron emission tomography/ computed tomography (PET/CT) and rubidium-82 (82Rb) using the abdominal aorta as input function in a 1-tissue compartment model. Methods: Eighteen healthy subjects underwent two dynamic 82Rb PET/CT scans in two different fields of view (FOV). FOV-A included the left ventricular blood pool (LVBP), the abdominal aorta (AA) and the majority of the kidneys. FOV-B included AA and the kidneys in their entirety. In FOV-A, an input function was derived from LVBP and from AA; in FOV-B from AA. 1-tissue compartmental modeling was performed using tissue time activity curves generated from volumes of interest contouring the kidneys, where the renal clearance of 82Rb is represented by the K1 kinetic parameter. To investigate the correct interpretation of K1, we assumed to first estimate effective renal plasma flow (ERPF) by extrapolating clearance values (ml/min/cm3) to whole kidney values (ml/min) using the estimated total kidney volume. Thereafter, RPF was estimated from ERPF using an assumed extraction fraction (0.89). Lastly, RBF was estimated from RPF using measured haematocrit values. Intra-assay coefficients of variation and inter-observer variation were calculated.Results: For both kidneys, K1 values derived from AA did not differ significantly from values obtained from LVBP, neither were significant differences seen between AA in FOV-A and AA in FOV-B, nor between the right and left kidneys. For both kidneys, the intra-assay coefficients of variation were low (~ 5%) for both input functions. The measured K1 of 2.80 ml/min/cm3 suggests, for young healthy subjects, an estimated total renal perfusion normalized to body surface area of 860 ± 129 ml/min/1.73 m2 and subsequently an estimated RBF of 1494 ± 221 ml/min/1.73 m2. Conclusion: RBF estimation based on PET/CT and 82Rb using AA as input function in a 1-tissue compartment model is feasible in a single FOV. The measured K1 clearance values are most likely representative of ERPF rather than estimated RBF values.

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 (SUVmax) 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 VND, VT, and BPND 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 SUVmax allow a differentiation between HCC and non-HCC lesions, obtained from dynamically performed PET scans using FAPI.

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. For input functions and the lesions, the according voxel with the maximum standardized uptake value (SUVmax) was taken, for the healthy tissue mean SUV values. 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 VND, VT and BPND 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 SUVmax allow a differentiation between HCC and non-HCC lesions, obtained from dynamically performed PET scans using FAPI.

[11C]mHED PET follows a two-tissue compartment model in mouse myocardium with norepinephrine transporter (NET)-dependent uptake, while [18F]LMI1195 uptake is NET-independent

Purpose Clinical positron emission tomography (PET) imaging of the presynaptic norepinephrine transporter (NET) function provides valuable diagnostic information on sympathetic outflow and neuronal status. As data on the NET-targeting PET tracers [11C]meta-hydroxyephedrine ([11C]mHED) and [18F]LMI1195 ([18F]flubrobenguane) in murine experimental models are scarce or lacking, we performed a detailed characterization of their myocardial uptake pattern and investigated [11C]mHED uptake by kinetic modelling. Methods [11C]mHED and [18F]LMI1195 accumulation in the heart was studied by PET/CT in FVB/N mice. To test for specific uptake by NET, desipramine, a selective NET inhibitor, was administered by intraperitoneal injection. [11C]mHED kinetic modelling with input function from an arteriovenous shunt was performed in three mice. Results Both tracers accumulated in the mouse myocardium; however, only [11C]mHED uptake was significantly reduced by excess amount of desipramine. Myocardial [11C]mHED uptake was half-saturated at 88.3 nmol/kg of combined mHED and metaraminol residual. After [11C]mHED injection, a radiometabolite was detected in plasma and urine, but not in the myocardium. [11C]mHED kinetics followed serial two-tissue compartment models with desipramine-sensitive K1. Conclusion PET with [11C]mHED but not [18F]LMI1195 provides information on NET function in the mouse heart. [11C]mHED PET is dose-independent in the mouse myocardium at < 10 nmol/kg of combined mHED and metaraminol. [11C]mHED kinetics followed serial two-tissue compartment models with K1 representing NET transport. Myocardial [11C]mHED uptake obtained from PET images may be used to assess cardiac sympathetic integrity in mouse models of cardiovascular disease.

Estimation of renal perfusion based on measurement of Rubidium-82 clearance by PET/CT scanning in healthy subjects

BackgroundChanges in renal blood flow (RBF) may play a pathophysiological role in hypertension and kidney disease. However, RBF determination in humans has proven difficult. We aimed to confirm the feasibility of RBF estimation based on positron emission tomography/ computed tomography (PET/CT) and rubidium-82 (82Rb) using the abdominal aorta as input function in a 1-tissue compartment model. MethodsEighteen healthy subjects underwent two dynamic 82Rb PET/CT scans in two different fields of view (FOV). FOV-A included the left ventricular blood pool (LVBP), the abdominal aorta (AA) and the majority of the kidneys. FOV-B included AA and the kidneys in their entirety. In FOV-A, an input function was derived from LVBP and from AA; in FOV-B from AA. 1-tissue compartmental modeling was performed using tissue time activity curves generated from volumes of interest contouring the kidneys, where the renal clearance of 82Rb is represented by the K1 kinetic parameter. To investigate the correct interpretation of K1, we assumed to first estimate effective renal plasma flow (ERPF) by extrapolating clearance values (ml/min/cm3) to whole kidney values (ml/min) using the estimated total kidney volume. Thereafter, RPF was estimated from ERPF using an assumed extraction fraction (0.89). Lastly, RBF was estimated from RPF using measured haematocrit values. Intra-assay coefficients of variation and inter-observer variation were calculated.ResultsFor both kidneys, K1 values derived from AA did not differ significantly from values obtained from LVBP, neither were significant differences seen between AA in FOV-A and AA in FOV-B, nor between the right and left kidneys. For both kidneys, the intra-assay coefficients of variation were low (~ 5%) for both input functions. The measured K1 of 2.04 ml/min/cm3 suggests an estimated total renal perfusion normalized to body surface area of 628 ± 95 ml/min/1.73 m2 and subsequently an estimated RBF of 1091 ± 162 ml/min/1.73 m2. ConclusionRBF estimation based on PET/CT and 82Rb using AA as input function in a 1-tissue compartment model is feasible in a single FOV. The measured K1 clearance values are most likely representative of ERPF rather than estimated RBF values.

First-in-human imaging and kinetic analysis of vesicular acetylcholine transporter density in the heart using [18F]FEOBV PET

In contrast to cardiac sympathetic activity which can be assessed with established PET tracers, there are currently no suitable radioligands to measure cardiac parasympathetic (cholinergic) activity. A radioligand able to measure cardiac cholinergic activity would be an invaluable clinical and research tool since cholinergic dysfunction has been associated with a wide array of pathologies (e.g., chronic heart failure, myocardial infarction, arrythmias). [18F]Fluoroethoxybenzovesamicol (FEOBV) is a cholinergic radiotracer that has been extensively validated in the brain. Whether FEOBV PET can be used to assess cholinergic activity in the heart is not known. Hence, this study aimed to evaluate the properties of FEOBV for cardiac PET imaging and cholinergic activity mapping. PET data were collected for 40 minutes after injection of 230 ± 50 MBq of FEOBV in four healthy participants (1 female; Age: 37 ± 10; BMI: 25 ± 2). Dynamic LV time activity curves were fitted with Logan graphical, 1-tissue compartment, and 2-tissue compartment models, yielding similar distribution volume estimates for each participant. Our initial data show that FEOBV PET has favorable tracer kinetics for quantification of cholinergic activity and is a promising new method for assessing parasympathetic function in the heart.