title: Noise reduction in the simplified reference tissue model for neuroreceptor functional imaging.
abstract: The Simplified Reference Tissue Model (SRTM) produces functional images of receptor binding parameters using an input function derived from a reference region and assuming a model with one tissue compartment. Three parameters are estimated: binding potential (BP), relative delivery (R1), and the reference region clearance constant k'2. Since k'2 should not vary across brain pixels, the authors developed a two-step method (SRTM2) using a global value of k'2. Whole-brain simulations were performed using human input functions and rate constants for [18F]FCWAY, [11C]flumazenil, and [11C]raclopride, and parameter SD and bias were determined for SRTM and SRTM2. The global mean of k'2 was slightly biased (2% to 6%), but the median was unbiased (<1%) and was used as the global value. Binding potential noise reductions with SRTM2 were 4% to 14%, 20% to 53%, and 10% to 30% for [18F]FCWAY, [11C]flumazenil, and [11C]raclopride, respectively, with larger reductions for shorter scans. R1 noise reduction was larger than that of BP. Simulations were also performed to assess bias when the reference and/or tissue regions followed a two-tissue compartment model. Owing to the constrained k'2, SRTM2 showed somewhat larger biases due to violations of the one-compartment model assumption. These studies demonstrate that SRTM2 should be a useful method to improve the quality of neuroreceptor functional images.
authors.affiliation: Positron Emission Tomography Department, W. G. Magnuson Clinical Center, National Institutes of Health, Bethesda, Maryland 20892-1180, U.S.A.
authors.forename: Yanjun
authors.initials: Y
authors.lastname: Wu
authors.forename: Richard E
authors.initials: RE
authors.lastname: Carson
mesh_terms: D016477:Artifacts; D001921:Brain / Q000000981:diagnostic imaging* / Q000502:physiology; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D012015:Reference Standards; D014055:Tomography, Emission-Computed / Q000379:methods* / Q000592:standards*