RT Journal Article
SR Electronic
T1 New Approaches for Modeling Radiopharmaceutical Pharmacokinetics Using Continuous Distributions of Rates
JF Journal of Nuclear Medicine
JO J Nucl Med
FD Society of Nuclear Medicine
SP 1622
OP 1628
DO 10.2967/jnumed.115.160515
VO 56
IS 10
A1 Igor Shuryak
A1 Ekaterina Dadachova
YR 2015
UL http://jnm.snmjournals.org/content/56/10/1622.abstract
AB Radiopharmaceutical pharmacokinetics are usually approximated by sums of discrete first-order rates, using 3 or more parameters. We hypothesized that pharmacokinetic processes can be modeled even better by continuous probability distributions (CPD) of rates, using only 1–2 parameters. Methods: To test this hypothesis, we used biodistribution data for 188Re-labeled melanin-specific antibody in blood, kidneys, liver, bone marrow, and lungs of melanoma xenograft–bearing mice. We used 3 discrete-rate models (monoexponential, monoexponential with constant, and biexponential) and 4 CPD models (stretched-exponential, modified stretched-exponential, simplified versions of stretched-exponential, and modified stretched-exponential). They were compared by sample-size-corrected Akaike information criterion. Total time integrals of radioactivity were computed for each model and averaged across all models. Results: The ratio of weights of evidence for CPD versus discrete-rate models was high for blood (12.2) and lungs (2.7), almost unity (0.99) for bone marrow, and slightly lower for kidneys (0.81) and liver (0.73). In all organs or tissues except lungs, model-averaged time integrals were 12.7%–54.0% higher than biexponential model estimates. Conclusion: Simple CPD models often outperform more complex discrete-rate models on pharmacokinetic data. Radioactivity time integrals are more robustly estimated by multimodel inference than using any single model.