A novel blood-cell-two-compartment model for transferring a whole blood time activity curve to plasma in rodents

Determination of the Input Function at the Entry of the Tissue of Interest and Its Impact on PET Kinetic Modeling Parameters

Quantitative positron emission tomography (PET) imaging is employed with several measurement protocols all relying on the a priori determination of the input function (IF). The standard technique to determine IF is by blood sampling. However, a unique IF determined in a subject for a given PET study, either defined by sampling or in the images, and commonly utilized for all analyzed tissues in that study equally at rest and during interventions, is expected to provoke biases in the rate constants and in tissue blood volume. The determination of a specific IF at the site of the tissue to be analyzed enhances PET accuracy and renders PET imaging less invasive.

FDG kinetic modeling in small rodent brain PET: optimization of data acquisition and analysis

BACKGROUND

Kinetic modeling of brain glucose metabolism in small rodents from positron emission tomography (PET) data using 2-deoxy-2-[(18) F]fluoro-d-glucose (FDG) has been highly inconsistent, due to different modeling parameter settings and underestimation of the impact of methodological flaws in experimentation. This article aims to contribute toward improved experimental standards. As solutions for arterial input function (IF) acquisition of satisfactory quality are becoming available for small rodents, reliable two-tissue compartment modeling and the determination of transport and phosphorylation rate constants of FDG in rodent brain are within reach.

METHODS

Data from mouse brain FDG PET with IFs determined with a coincidence counter on an arterio-venous shunt were analyzed with the two-tissue compartment model. We assessed the influence of several factors on the modeling results: the value for the fractional blood volume in tissue, precision of timing and calibration, smoothing of data, correction for blood cell uptake of FDG, and protocol for FDG administration. Kinetic modeling with experimental and simulated data was performed under systematic variation of these parameters.

RESULTS

Blood volume fitting was unreliable and affected the estimation of rate constants. Even small sample timing errors of a few seconds lead to significant deviations of the fit parameters. Data smoothing did not increase model fit precision. Accurate correction for the kinetics of blood cell uptake of FDG rather than constant scaling of the blood time-activity curve is mandatory for kinetic modeling. FDG infusion over 4 to 5 min instead of bolus injection revealed well-defined experimental input functions and allowed for longer blood sampling intervals at similar fit precisions in simulations.

CONCLUSIONS

FDG infusion over a few minutes instead of bolus injection allows for longer blood sampling intervals in kinetic modeling with the two-tissue compartment model at a similar precision of fit parameters. The fractional blood volume in the tissue of interest should be entered as a fixed value and kinetics of blood cell uptake of FDG should be included in the model. Data smoothing does not improve the results, and timing errors should be avoided by precise temporal matching of blood and tissue time-activity curves and by replacing manual with automated blood sampling.