Simultaneous estimation of physiological parameters and the input function : in vivo PET data

Abstract

Dynamic imaging with positron emission tomography (PET) is widely used for the in vivo measurement of regional cerebral metabolic rate for glucose (rCMRGlc) with [[sup 18]F]fluorodeoxy-D-glucose (FDG) and is used for the clinical evaluation of neurological disease. However, in addition to the acquisition of dynamic images, continuous arterial blood sampling is the conventional method to obtain the tracer time-activity curve in blood (or plasma) for the numeric estimation of rCMRGlc in mg glucose/100-g tissue/min. The insertion of arterial lines and the subsequent collection and processing of multiple blood samples are impractical for clinical PET studies because it is invasive, has the remote, but real potential for producing limb ischemia, and it exposes personnel to additional radiation and risks associated with handling blood. In this paper, based on our previously proposed method for extracting kinetic parameters from dynamic PET images, we developed a modified version (post-estimation method) to improve the numerical identifiability of the parameter estimates when we deal with data obtained from clinical studies. We applied both methods to dynamic neurological FDG PET studies in three adults. We found that the input function and parameter estimates obtained with our noninvasive methods agreed well with those estimated from the gold standard method of arterial blood sampling and that rCMRGlc estimates were highly correlated (r = 0.973). More importantly, no significant difference was found between rCMRGlc estimated by our methods and the gold standard method (P > 0.16). We suggest that our proposed noninvasive methods may offer an advance over existing methods.