Physiologic smoothing of blood time-activity curves for PET data analysis

Blood or plasma time-activity curves (TACs) are used as the input function for mathematical models of tracer kinetics in several applications including PET. Uncertainty associated with both the blood data and the PET tissue data can result in uncertainty in the estimates of metabolic rates, blood flow, etc.

This article presents an approach to reduce the uncertainty in the blood TAC by fitting a model to the curve. The model includes a choice of bolus or infusion input and has three compartments (plasma, interstitial fluid and tissue fluid) with exchange between them. There is a parameter for loss from the plasma compartment. To test the utility of smoothing blood TACs with this approach, a program was set up, using the fluorodeoxyglucose (FDG) model, with simulated noisy blood and tissue TACs. The smoothed blood TAC was compared to a linearly interpolated TAC as the input function with a compartmental model parameter estimation program and with graphical analysis.

With a well sampled blood TAC (19 points), the model approach is somewhat more accurate than linear interpolation if the s.d. of noise added to the data exceeded 10%. With sparsely sampled blood TACs (five points) or with a large gap in the blood TAC, the modeled approach was markedly better. For graphical analysis, the model smoothed TAC was also more accurate, although, in general, the results were not as sensitive to the input function.

This approach, using a physiologically reasonable model to smooth the blood TAC, is a useful aid in PET data analysis, particularly when the data are quite noisy or when there are large gaps in the data.