Omission of serial arterial blood sampling in neuroreceptor imaging with independent component analysis

We have previously proposed a statistical method for extracting a plasma time-activity curve (pTAC) from dynamic PET images, named EPICA, for kinetic analysis of cerebral glucose metabolism. We assumed that the dynamic PET images consist of a blood-related component and a tissue-related component which are spatially independent in a statistical sense. The aim of this study is to investigate the utility of EPICA in imaging total distribution volume (DVt) and binding potential (BP) with Logan plots in a neuroreceptor mapping study. We applied EPICA to dynamic [(11)C]MPDX PET images in 25 subjects, including healthy subjects and patients with brain diseases, and validated the estimated pTACs. [11C]MPDX is a newly developed radiopharmaceutical for mapping cerebral adenosine A1 receptors. EPICA successfully extracted pTAC for all 25 subjects. Parametric images of DVts were estimated by applying Logan plots with the EPICA-estimated pTAC and then used to define a reference region. The BPs estimated using EPICA were evaluated in 18 subjects by ROI-based comparison with those obtained using the nonlinear least squares method (NLSM). The calculated BPs were identical to the estimates using NLSM in each subject. We conclude that EPICA is a promising technique that generates parametric images of DVt and BP in neuroreceptor mapping without requiring arterial blood sampling.