Predictive model for a Rb-82 generator bolus times as a function of generator lifetime

Background: While both myocardial perfusion SPECT and PET imaging provide valuable information regarding three-dimensional distribution of radiotracers into myocardium, there are a number of physical differences where PET has a clear advantage over SPECT. PET has high spatial and temporal resolution, reliable attenuation and scatter correction, short imaging protocols utilizing short-lived positron emitting radiotracers to acquire 3-D acquisition simultaneously which offers tracer kinetic models to obtain absolute myocardial blood flow (MBF) measurements for rest and stress and relative perfusion and function analysis as well. Rb-82 cardiac PET is largely used to study myocardial perfusion and to calculate the MBF and coronary flow reserve (CFR). Although the Rb-82 activity is determined by the patient weight, the infusion volume and activity concentration varies with the age of the Rb-82 generator. We sought to predict the needed bolus volume of Rb-82 to help evaluate the accuracy of MBF findings, despite the other factors that may affect the MBF due to IV size, location and arm position.

Methods: Data was collected from de-identified tickets of a particular brand of Rb-82 generator, calibrated as 100 mCi, which produced 157 clinical elutions over the course of one month. The extracted data included the date, time, total eluted activity, length of time for the elution, and the eluted activity flow rate (in mCi/mL/sec) at each second during the elution. The number of seconds to reach 4 bolus activity levels (20, 30, 40, and 45 mCi) was also recorded for each elution. The activity flow rate for the largest bolus was fitted to determine the functional form. The time to reach each bolus level per elution was fitted as a function of the generator age and 95% confidence limits were created.

Results: The activity flow rate curve was fitted with a growth-saturation model of the form y(t) = A · (t + B) · EXP(-C · t), allowing a calculation of bolus volume. We expected the amplitude “A” to purely depend on the age of the generator; however, it was observed to also be influenced by the time since last elution, and possibly other clinical factors. Elution times to reach the 4 bolus levels were plotted vs. generator age. The log of the bolus times was fitted linearly and 95% confidence limits were created symmetrically around the fit by y-shifting the curve to encompass 95% of the data (90% of the data for 40 and 45 mCi due to lower statistics). The 95% CL band allowed a prediction of elution time to achieve each bolus size for future generators, as a function only of generator age.

Conclusions: A predictive model was created for elution times needed to create a bolus of activity from this brand of Rb-82 generator as a function of generator age. The value of this model is in determining if the necessary amount of activity can be extracted from a generator before hitting one of the backup infusion settings, given a generator age. Some sites may also wish to control the bolus duration for better MBF calculations, since predicting the time for the injection to complete may determine if MBF and CFR calculations are meaningful. Unfortunately, although the eluted activity rate was well fitted by a growth-saturation curve, the amplitude of the curve varied in uncontrollable ways. We plan to investigate in the future if a more precise prediction of injection time than the 95% confidence bands can be made, possibly by controlling other IV and clinical factors.