Abstract
Plasma pharmacokinetic (PK) data are required as an input function for graphical analysis of single positron emission computed tomography/computed tomography (SPECT/CT) and positron emission tomography/CT (PET/CT) data to evaluate tissue influx rate of radiotracers. Dynamic heart imaging data are often used as a surrogate of plasma PK. However, accumulation of radiolabel in the heart tissue may cause overprediction of plasma PK. Therefore, we developed a compartmental model, which involves forcing functions to describe intact and degraded radiolabeled proteins in plasma and their accumulation in heart tissue, to deconvolve plasma PK of (125)I-amyloid beta 40 ((125)I-Aβ (40)) and (125)I-insulin from their dynamic heart imaging data. The three-compartment model was shown to adequately describe the plasma concentration-time profile of intact/degraded proteins and the heart radioactivity time data obtained from SPECT/CT imaging for both tracers. The model was successfully applied to deconvolve the plasma PK of both tracers from their naïve datasets of dynamic heart imaging. In agreement with our previous observations made by conventional serial plasma sampling, the deconvolved plasma PK of (125)I-Aβ (40) and (125)I-insulin in young mice exhibited lower area under the curve than aged mice. Further, Patlak plot parameters extracted using deconvolved plasma PK as input function successfully recapitulated age-dependent plasma-to-brain influx kinetics changes. Therefore, the compartment model developed in this study provides a novel approach to deconvolve plasma PK of radiotracers from their noninvasive dynamic heart imaging. This method facilitates the application of preclinical SPECT/PET imaging data to characterize distribution kinetics of tracers where simultaneous plasma sampling is not feasible. SIGNIFICANCE STATEMENT: Knowledge of plasma pharmacokinetics (PK) of a radiotracer is necessary to accurately estimate its plasma-to-brain influx. However, simultaneous plasma sampling during dynamic imaging procedures is not always feasible. In the current study, we developed approaches to deconvolve plasma PK from dynamic heart imaging data of two model radiotracers, (125)I-amyloid beta 40 ((125)I-Aβ (40)) and (125)I-insulin. This novel method is expected to minimize the need for conducting additional plasma PK studies and allow for accurate estimation of the brain influx rate.