Deconvolution of plasma pharmacokinetics from dynamic heart imaging data obtained by SPECT/CT imaging

Plasma pharmacokinetic (PK) data is required as an input function for graphical analysis (e.g., Patlak plot) 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 is often used as a surrogate of plasma PK. However, accumulation of radiolabel (representing both intact and degraded tracer) in the heart tissue may interfere with accurate prediction of plasma PK from the heart data. 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 125I-amyloid beta 40 (125I-A{beta}40) and 125I-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 naive datasets of dynamic heart imaging. In agreement with our previous observations made by conventional serial plasma sampling, the deconvolved plasma PK of 125I-A{beta}40 and 125I-insulin in young mice exhibited lower area under the curve (AUC) than the aged mice. Further, Patlak plot parameters (Ki) extracted using deconvolved plasma PK as input function successfully recapitulated age-dependent blood-to-brain influx kinetics changes for both 125I-A{beta}40 and 125I-insulin. 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 or PET imaging data to characterize distribution kinetics of tracers where simultaneous plasma sampling is not feasible.